System and method for analyzing sensor data and collecting it intelligently

Abstract

A method for controlling a plasma tool is described. The method includes receiving, by a processor, a first set of metric data from the plasma tool. The method further includes analyzing the first set of metric data to determine a first location and a first time window for capturing a second set of metric data. The method includes providing, by the processor, the first location and the first time window to a data processing system of the plasma tool. The method also includes receiving a second set of metric data captured at the first location and for the first time window. The method includes analyzing the second set of metric data to generate variable data and controlling the plasma tool according to the variable data.

Description

Technical Field

[0001] Embodiments described in the present disclosure relate to systems and methods for analyzing and intelligently collecting sensor data.

Background Art

[0002] The description of the background art provided herein is for the purpose of generally presenting the context of the present disclosure. The research by the inventors named at the present time, within the scope described in this background art section, cannot be regarded as prior art separately at the time of filing, whether explicitly or implicitly, in the same way as the aspects of the description that cannot be regarded as prior art against the present disclosure.

[0003] In a plasma tool, one or more radio frequency (RF) generators are connected to an impedance matching network. The impedance matching network is connected to a plasma chamber. An RF signal is supplied from the RF generator to the impedance matching network. When the impedance matching network receives the RF signal, it outputs the RF signal to the plasma chamber. Also, a plurality of process gases are supplied through a showerhead of the plasma chamber to a gap in the plasma chamber. When the RF signal is supplied from the impedance matching circuit to the plasma chamber and the process gas is supplied, a wafer is processed in the plasma chamber.

[0004] During the processing of the wafer, a large amount of data is collected.

[0005] The embodiments described in the present disclosure arise in this context.

Summary of the Invention

[0006] Embodiments of the present disclosure provide a sensor-independent apparatus, method, and computer program for analyzing and intelligently collecting sensor data. The present embodiments may be implemented in many ways, for example, in a process, apparatus, system, a piece of hardware, or a method on a computer-readable medium. Some embodiments will be described later.

[0007] In one embodiment, a method of collecting and analyzing metric data is described. The method includes providing, by a processor, a position and a time window for capturing metric data to a data processing system of a plasma tool. The method further includes receiving, at the position and with respect to the time window, the captured metric data, analyzing the metric data to generate variable data, and controlling the plasma tool according to the variable data.

[0008] In one embodiment, a method of controlling a plasma tool is described. The method includes receiving, by a processor, a first set of metric data from the plasma tool. The method further includes analyzing the first set of metric data to determine a first position and a first time window for capturing a second set of metric data. The method includes providing, by the processor, the first position and the first time window to a data processing system of the plasma tool. The method also includes receiving the second set of metric data captured at the first position and with respect to the first time window. The method includes analyzing the second set of metric data to generate variable data and controlling the plasma tool according to the variable data.

[0009] In one embodiment, a controller for controlling a plasma tool is described. The controller includes a processor. The processor receives a first set of metric data from the plasma tool, analyzes the first set of metric data to determine a first position and a first time window used to capture a second set of metric data, and provides the first position and the first time window to a data processing system of the plasma tool. The processor further receives a second set of metric data captured at the first position and with respect to the first time window, analyzes the second set of metric data to generate variable data, and controls the plasma tool according to the variable data. The controller includes a memory device connected to the processor.

[0010] In one embodiment, a plasma system is described. The plasma system includes a plasma source configured to generate a radio frequency (RF) signal. The plasma system further includes a data processing device. The plasma system includes a controller connected to the data processing device and the plasma source. The controller receives a first set of metric data related to the RF signal from an RF sensor, then analyzes the first set of metric data to determine a first position and a first time window used to capture a second set of metric data, provides the first position and the first time window to the data processing system, and receives a second set of metric data captured at the first position and with respect to the first time window. The controller analyzes the second set of metric data to generate variable data and controls the plasma source according to the variable data.

[0011] Some advantages of the systems and methods described herein include providing a location and a time window in which digital metric data is to be collected. The time window extends across a state of the digital metric data, or a sub-state of the digital metric data, or a slice of the digital metric data. By providing the location and the time window, the process can be accurately controlled as needed. Further, by providing the location and the time window, the amount of memory space used to store the digital metric data is reduced. Without the location and the time window being provided, large amounts of digital metric data are stored and the memory space increases.

[0012] Additional advantages of the systems and methods described herein include generating statistical values from the digital metric data. The statistical values are stored in a memory device instead of the digital metric data. Variables are then controlled based on the statistical values. By storing the statistical values instead of the digital metric data, the amount of memory space for storing the digital metric data is reduced.

[0013] Further advantages of the systems and methods described herein include achieving in-chamber matching and between-chamber matching. In-chamber matching is achieved between a first set of digital metric data collected at a location with respect to a time window and a second set of digital metric data collected at the location with respect to the time window. For example, the first set of digital metric data is sampled at the location during a first cycle of a clock signal, and the second set of digital metric data is collected at the location during a second cycle of the clock signal. Further, between-chamber matching is achieved between a first set of digital metric data collected at a location with respect to a time window from a first plasma tool and a second set of digital metric data collected at the location with respect to the time window from a second plasma tool. For example, the first set of digital metric data is sampled at the location during a cycle of a clock signal, and the second set of digital metric data is collected at the location during the same cycle of the clock signal.

[0014] Additional advantages of the systems and methods described herein include sampling the edges of analog metric data at a higher rate compared to the steady state of the analog metric data. The steady state does not change as frequently as the edges. Therefore, variables can be accurately controlled by sampling the edges at a higher frequency compared to the frequency of sampling of the steady state.

[0015] Further advantages of the systems and methods described herein include allocating a large number of sample sets within a payload when it is determined that a first set of digital metric data has a number of states, such as a steady state or an edge. The first set of digital metric data has a greater number of states compared to the number of states of a second set of digital metric data. Additional advantages of the systems and methods described herein include allocating a large number of packets to a steady state having a longer duration compared to another steady state.

[0016] Other aspects will become apparent from the following detailed description in conjunction with the accompanying drawings.

Brief Description of the Drawings

[0017] Embodiments are understood by reference to the following description in conjunction with the accompanying drawings.

[0018]

FIG. 1A

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FIG. 1B

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FIG. 2A

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FIG. 2B

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FIG. 2C

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FIG. 5A

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FIG. 14C-2

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FIG. 15

[0058] The following embodiments describe a system and method for analyzing sensor data and collecting it intelligently. It will be apparent that these embodiments may be practiced without some or all of these specific details. In other instances, well-known process operations are not described in detail so as not to unnecessarily obscure these embodiments.

[0059] In one embodiment, metric metric data is received by a processor of an analysis controller. The processor of the analysis controller analyzes the metric data to determine a location and a time window at which additional metric data should be received. The processor transmits a signal indicating the location and the time window to a data processing system (DPS). Upon receiving the signal, an analog-to-digital converter (ADC) of the data processing system samples the metric data with respect to the time window at that location and outputs additional metric data, for example, by converting it from an analog format to a digital format, and transmits the additional metric data to the processor of the analysis controller. The processor of the analysis controller can control the variables of a radio frequency (RF) generator based on the additional metric data collected with respect to the time window at that location, for example, sampled data.

[0060] FIG. 1A is a diagram of one embodiment of a plasma system 100 for illustrating the collection of sensor data from a plurality of RF sensors a1 to a(n + m), where n is a positive integer and m is a positive integer. The plasma system may also be referred to herein as a plasma tool. System 100 includes RF generators (RFGs) a1 to a(n + m), where n and m are positive integers. System 100 further includes RF sensors a1 to a(n + m), a plurality of matching systems 108 and 110, an RF coil 112, and a plasma chamber 114. As an example, RF coil 112 includes a single RF coil having a plurality of turns. System 100 further includes a DPS 102, an analysis controller 106, and a process controller 116. The DPS may also be referred to herein as a data processing device.

[0061] As an example, each RF generator operates at a certain frequency. For example, RF generator RFGa1 operates at a low frequency, RF generator RFGa2 operates at a medium frequency, and RF generator RFGan operates at a high frequency. By way of illustration, RF generator RFGa1 generates an RF signal having a frequency of 400 kilohertz (kHz), RF generator RFGa2 generates an RF signal having a frequency of 27 megahertz (MHz), and RF generator RFGan generates an RF signal having a frequency of 60 MHz. As another illustration, RF generator RFGa1 generates an RF signal having a frequency of 2 MHz, and the remaining RF generators RFGa2 and RFGan generate RF signals having the same frequencies as those in the previous illustration.

[0062] The matching system described herein includes one or more branch circuits. As an example, the matching system has a housing or enclosure. Examples of the matching system include an impedance matching network, an impedance matching circuit, and a match. By way of illustration, each branch circuit of the matching system includes one or more electrical circuit components such as transistors, resistors, and capacitors. Further by way of illustration, each branch circuit includes a series circuit, a shunt, or a combination thereof. The shunt is connected to the series circuit at one end and to the ground potential at the opposite end. As an example, the series circuit includes two or more electrical circuit components connected in series with each other, and the shunt includes two or more electrical circuit components connected in series with each other.

[0063] The matching system 108 has a plurality of inputs Ia1 to Ian and an output O108. As an example, each input and output of the matching system is a connector. As an example, the inputs Ia1 to Ian are connected to the output O108 via the branch circuits of the matching system 108. By way of illustration, input Ia1 is connected to output O108 via the first branch circuit of the matching system 108, and input Ia2 is connected to output O108 via the second branch circuit of the matching system 108.

[0064] Similarly, the matching system 110 has a plurality of inputs Ia(n+1) to Ia(n+m) and an output O110. As an example, the inputs Ia(n+1) to Ia(n+m) are connected to the output O110 via the branch circuits of the matching system 110. Illustratively, the input Ia(n+1) is connected to the output O110 via the first branch circuit of the matching system 110, and the input Ia(n+2) is connected to the output O110 via the second branch circuit of the matching system 110.

[0065] Each of the RF generators RFGa1 to RFGan is connected to the corresponding input of the matching system 108 via the corresponding RF cable. For example, the output Oa1 of the RF generator RFGa1 is connected to the input Ia1 of the matching system 108 via the RF cable RFCa1, the output Oa2 of the RF generator RFGa2 is connected to the input Ia2 of the matching system 108 via the RF cable RFCa2, and the output Oan of the RF generator RFGan is connected to the input Ian of the matching system 108 via the RF cable RFCan. The output O108 of the matching system 108 is connected to the RF coil 112 via the RF transmission line 138.

[0066] Similarly, each of the RF generators RFGa(n+1) to RFGa(n+m) is connected to the corresponding input of the matching system 110 via the corresponding RF cable. For example, the output Oa(n+1) of the RF generator RFGa(n+1) is connected to the input Ia(n+1) of the matching system 110 via the RF cable RFCa(n+1), and the output O a (n+2) of the RF generator RFGa(n+2) is connected to the input Ia(n+2) of the matching system 110 via the RF cable RFCa(n+2), and the output Oa(n+m) of the RF generator RFGa(n+m) is connected to the input Ia(n+m) of the matching system 110 via the RF cable RFCa(n+m). The output O110 of the matching system 110 is connected to the chuck 118 via the RF transmission line 142.

[0067] Examples of RF sensors used in this specification include voltage - current probes, directional couplers, complex current sensors, complex voltage sensors, and phase - amplitude sensors. By way of example, an RF sensor measures metrics such as complex voltage and current (complex V and I), or forward power, or reflected power, or voltage, or current, or impedance, or combinations of two or more of them. Complex voltage and current include the amplitude of the voltage, the amplitude of the current, and the phase between the voltage and the current. A complex current sensor measures complex current, and complex current includes the amplitude of the current and the phase of the current. A complex voltage sensor measures complex voltage, and complex voltage includes the amplitude of the voltage and the phase of the voltage. As an example, forward power is supplied from a plasma source to a plasma chamber, and reflected power is reflected back from the plasma source to an RF generator. Examples of plasma sources will be described later. A directional coupler is an example of a power sensor that measures supplied power and reflected power. As an example, an RF cable RFCan passes from the input port of a directional coupler through a channel in the directional coupler to the output port of the directional coupler. As another example, an RF cable RFCan passes from the input port of a VI probe through a channel in the VI probe to the output port of the VI probe.

[0068] As an example, one or more of the RF sensors a1 to a(n + m) measure a different metric from the rest of the RF sensors a1 to a(n + m). For example, RF sensor a1 measures complex voltage and current, and RF sensor an measures complex voltage. As another example, RF sensor a(n + 1) measures complex current, and RF sensor a(n + m) measures complex voltage.

[0069] The plasma chamber 114 is an inductively coupled plasma chamber having an RF coil 112. For example, the RF coil 112 is disposed above the dielectric window 120 of the plasma chamber 114. The plasma chamber 114 further includes a chuck 11 8 which is an example of a substrate support. 8 An example of the chuck 11 8supports a substrate S such as a semiconductor wafer for processing within the plasma chamber 114. The substrate S is disposed on the upper surface of the chuck 11 8 . The chuck 11 8 includes a lower electrode made of a metal such as aluminum or an alloy of aluminum. The chuck 11 8 faces the dielectric window 120, and a gap is formed between the chuck 11 8 and the dielectric window 120.

[0070] The plasma chamber 114 has a side wall SW, a bottom wall BW, and an upper wall TW. The side wall SW is located between the upper wall TW and the bottom wall BW. As an example, a part of the upper wall TW is formed by the dielectric window 120.

[0071] The DPS 102 includes an ADC 104 and a transceiver 122. The ADC 104 is connected to the transceiver 122. Also, the analysis controller 106 includes a processor 124, a memory device 126, a transceiver 128, and a communication controller (CC) 130. As an example, the communication controller applies a network communication protocol to transfer data to another communication controller, for example, by executing etc. Examples of network communication protocols include the User Datagram Protocol (UDP), User Datagram Protocol over Internet Protocol (UDP / IP), and Transmission Control Protocol over IP (TCP / IP). As an example, the transceiver transfers data (e.g., receives or transmits etc.) by applying a transfer protocol in a parallel or serial manner etc., or by applying the Universal Serial Bus (USB) protocol. The processor 124 is connected to the transceiver 128, the communication controller 130, and the memory device 126.

[0072] As an example, the processor is a central processing unit (CPU), or a microprocessor, or a microcontroller, or an application specific integrated circuit (ASIC), or a programmable logic device (PLD). Examples of memory devices include random access memory and read only memory. By way of illustration, the memory device is a flash memory, a solid state memory, or a hard disk, or a redundant array of independent disks.

[0073] The process controller 116 includes a processor 132, a memory device 134, and a communication controller 136. The processor 132 is connected to the memory device 134 and the communication controller 136.

[0074] An example of an RF transmission line includes an RF rod surrounded by an RF sheath. There is an insulating material between the RF rod and the RF sheath. Another example of an RF transmission line is a combination of an RF rod and one or more RF straps. By way of illustration, the RF rod is surrounded by an RF sheath, connected to an RF coil via an RF strap, and connected to an output O108 via an RF strap. As another illustration, the RF rod is surrounded by an RF sheath, connected to a chuck 11 8 via an RF strap, and connected to an output O110 via an RF strap.

[0075] Each RF sensor is connected to an RF cable between the RF generator and the matching system. For example, RF sensor a1 is connected at point Pa1 on RF cable RFCa1 between RF generator RFGa1 and input Ia1, RF sensor a2 is connected at point Pa2 on RF cable RFCa2 between RF generator RFGa2 and input Ia2, and RF sensor an is connected at point Pan on RF cable RFCan between RF generator RFGan and input Ian. As another example, RF sensor a(n + 1) is connected at point Pa(n + 1) on RF cable RFCa(n + 1) between RF generator RFGa(n + 1) and input Ia(n + 1), RF sensor a(n + 2) is connected at point Pa(n + 2) on RF cable RFCa(n + 2) between RF generator RFGa(n + 2) and input Ia(n + 2), and RF sensor a(n + m) is connected at point Pa(n + m) on RF cable RFCa(n + m) between RF generator RFGa(n + m) and input Ia(n + m).

[0076] RF sensors a1 to a(n + m) are connected to ADC104 of DPS102. DPS102 is connected to analysis controller 106, and analysis controller 106 is connected to process controller 116. For example, transceiver 122 is connected to transceiver 128 via a parallel transfer cable, a serial transfer cable, or a USB cable. The parallel transfer cable transfers data in a parallel manner such as the simultaneous mode. The serial transfer cable transfers data in a serial manner such as the continuous mode. The USB cable transfers data using the USB protocol. Also, in this example, communication controller 130 is connected to communication controller 136.

[0077] Processor 124 is connected to the RF generator via a corresponding transfer cable. For example, processor 124 is connected to RF generator RFGa1 via transfer cable TCa1, connected to RF generator RFGa2 via transfer cable TCa2, and connected to RF generator RFGan via transfer cable TCan. Also, processor 124 is connected to RF generator RFGa(n + 1) via transfer cable TCa(n + 1), connected to RF generator RFGa(n + 2) via transfer cable TCa(n + 2), and connected to RF generator RFGa(n + m) via transfer cable TCa(n + m). Examples of transfer cables are provided above.

[0078] As an example, process controller 116 is managed by an entity different from the entity that manages analysis controller 106. Illustratively, process controller 116 is managed by manufacturer A of one or more components of plasma system 100, and analysis controller 106 is managed by a customer of that manufacturer. The customer uses the components of plasma system 100 to manufacture substrates.

[0079] Processor 124 accesses a recipe that includes variables such as frequency or power or a combination thereof. The recipe is accessed from memory device 126. The recipe is for each of RF generators RFGa1 to RFGa(n + m). For example, RF generator RFGa1 is controlled based on a first recipe, and RF generator RFGan is controlled based on a second recipe. Processor 124 transmits a recipe signal including the corresponding recipe to RF generators RFGa1 to RFGa(n + m).

[0080] After transmitting the recipe signal, the processor 124 transmits a trigger signal, such as a single digital pulse, to the RF generators RFGa1 to RFGa(n+m). Upon receiving the trigger signal, each RF generator RFGa1 to RFGa(n+m) generates an RF signal based on the corresponding recipe. For example, the RF generators RFGa1 to RFGa(n+m) generate corresponding RF signals 140a1, 140a2, 140an, 140a(n+1), 140a(n+2), and 140a(n+m) according to the corresponding recipe. For example, the RF generator RFGan generates the RF signal 140an based on the nth recipe, and the RF generator RFGa(n+m) generates the RF signal 140a(n+m) based on the (n+m)th recipe.

[0081] The matching system 108 receives the RF signals 140a1 to 140an at the inputs Ia1 to Ian, modifies the impedances of the RF signals 140a1 to 140an, and outputs a modified impedance signal. The matching system 108 matches the impedance of the load connected to the output O108 with the impedance of the source connected to the inputs Ia1 to Ian to modify the impedances of the RF signals 140a to 140an. An example of the load connected to the output O108 is the RF transmission line 138 and the plasma chamber 114, and an example of the source connected to the inputs Ia1 to Ian is the RF cables RFCa1 to RFCan and the RF generators RFGa1 to RFGan. The modified impedance signals are combined at the output O108 to output a modified RF signal 144. The modified RF signal 144 is transmitted from the output O108 to the RF coil 112 via the RF transmission line 138.

[0082] Similarly, the matching system 110 receives the RF signals 140a(n+1) to 140a(n+m) at the inputs Ia(n+1) to Ia(n+m), modifies the impedances of the RF signals 140a(n+1) to 140a(n+m), and outputs a modified impedance signal. The matching system 1 10The impedance of the load connected to output O110 is matched with the impedance of the sources connected to inputs Ia(n+1)~Ia(n+m) to correct the impedance of RF signals 140a(n+1)~140a(n+m). An example of the load connected to output O110 is RF transmission line 142 and plasma chamber 104, and an example of the sources connected to inputs Ia(n+1)~Ia(n+m) are RF cables RFCa(n+1)~RFCa(n+m) and RF generators RFGa(n+1)~RFGa(n+m). The corrected impedance signal is synthesized at output O110 to output corrected RF signal 146. Corrected RF signal 146 is transmitted from output O110 to the lower electrode of chuck 118 via RF transmission line 142. In addition to corrected RF signals 144 and 146, when one or more process gases such as an oxygen-containing gas, or a fluorine-containing gas, or a nitrogen-containing gas, or a combination thereof are supplied to plasma chamber 114, plasma is generated or maintained in plasma chamber 114.

[0083] When plasma is generated or maintained in plasma chamber 114, RF sensors a1~a(n+m) sense the data of RF signals 140a1~140a(n+m) transferred via RF cables RFC1~RFCa(n+m) to output analog metric data and provide the analog metric data to ADC104. For example, RF sensor a1 senses or measures the data of RF signal 140a1 to output analog metric data 142a1, RF sensor a2 senses the data of RF signal 140a2 to output analog metric data 142a2, and RF sensor an senses the data of RF signal 140an to output analog metric data 142an. Also, RF sensor a(n+1) senses the data of RF signal 140a(n+1) to output analog metric data 142a(n+1), RF sensor a(n+2) senses the data of RF signal 140a(n+2) to output analog metric data 142a(n+2), and RF sensor a(n+m) senses the data of RF signal 140a(n+m) to output analog metric data 142a(n+m).

[0084] RF sensors a1 to a(n+m) transmit analog metric data 142a1 to 142a(n+m) to ADC104 via a transfer cable. ADC104 collects the analog metric data 142a1 to 142a(n+m) and outputs digital metric data 144, for example, by sampling. For example, ADC104 converts the analog metric data 142a1 to 142a(n+m) received from RF sensors a1 to a(n+m) from analog format to digital format and outputs digital metric data 144.

[0085] The transceiver 122 of DPS102 applies a transfer protocol to the digital metric data 144 to generate a data transfer unit 146 and transmits the data transfer unit 146 to the transceiver 128. Note that the analog metric data or digital metric data described in this specification is metric data.

[0086] The transceiver 128 acquires the data transfer unit 146, applies a transfer protocol to the data transfer unit 146 to extract the digital metric data 144. The transceiver 128 provides the digital metric data 144 to the processor 124. The processor 124 of the analysis controller 106 analyzes the digital metric data 144 to determine whether to control the ADC 104 to change the position and time window at which additional analog metric data output by one or more of the RF sensors a1 to a(n+m) is to be collected by the ADC 104. For example, the processor 124 determines that the additional analog metric data output by the RF sensor a1 should be converted from analog to digital with respect to the changed position and the changed time window. In this example, the processor 124 sends a control signal to the ADC 104 via the transceiver 128 of the analysis controller 106 and the transceiver 122 of the DPS 102, indicating the changed position and the changed time window. The ADC 104 receives the changed position and the changed time window and converts the additional analog metric data output by the RF sensor a1 from analog to digital with respect to the changed position and the changed time window.

[0087] As another example, the processor 124 of the analysis controller 106 analyzes the digital metric data 144 and determines to control the ADC 104 to change the first position and the first time window at which additional analog metric data output by the RF sensor an should be collected by the ADC 104. In this example, the processor 124 transmits a control signal to the ADC 104 via the transceiver 128 of the analysis controller 106 and the transceiver 122 of the DPS 102, indicating the changed first position and the changed first time window. The ADC 104 receives the changed first position and the changed first time window, and converts the additional analog metric data output by the RF sensor an from analog format to digital format with respect to the changed first time window at the changed first position. Also, in this example, the processor 124 of the analysis controller 106 analyzes the digital metric data 144 and determines to control the ADC 104 to change the first position and the first time window at which additional analog metric data output by the RF sensor a(n+m) should be collected by the ADC 104. In this example, the processor 124 transmits a control signal to the ADC 104 via the transceiver 128 of the analysis controller 106 and the transceiver 122 of the DPS 102, indicating the changed first position and the changed first time window. The ADC 104 receives the changed first position and the changed first time window, and converts the additional analog metric data output by the RF sensor a(n+m) from analog format to digital format with respect to the changed first time window at the changed first position.

[0088] As yet another example, the processor 124 of the analysis controller 106 analyzes the digital metric data 144 and determines to control the ADC 104 to change the first position and the first time window at which additional analog metric data output by the RF sensor an is to be collected by the ADC 104. In this example, the processor 124 transmits a control signal to the ADC 104 via the transceiver 128 of the analysis controller 106 and the transceiver 122 of the DPS 102, indicating the changed first position and the changed first time window. The ADC 104 receives the changed first position and the changed first time window and converts the additional analog metric data output by the RF sensor an from analog format to digital format with respect to the changed first time window at the changed first position. Also in this example, the processor 124 of the analysis controller 106 analyzes the digital metric data 144 and determines to control the ADC 104 to change the second position and the second time window at which additional analog metric data output by the RF sensor a(n+m) is to be collected by the ADC 104. In this example, the processor 124 transmits a control signal to the ADC 104 via the transceiver 128 of the analysis controller 106 and the transceiver 122 of the DPS 102, indicating the changed second position and the changed second time window. The ADC 104 receives the changed second position and the changed second time window and converts the additional analog metric data output by the RF sensor a(n+m) from analog format to digital format with respect to the changed second time window at the changed second position. In this example, the first position is different from the second position, and the first time window is different from the second time window. By way of illustration, the first position is located temporally before or after the second position, and the first time window has a period that is before or after the period of the second time window. Further by way of illustration, the second time window partially overlaps the first time window but does not completely overlap the first time window. Further description of the functionality of the system 100 will be described later with reference to FIGS. 2A and 2B.

[0089] In one embodiment, a clock source, such as a clock oscillator or a digital clock, generates a clock signal and supplies the clock signal to the ADC 104 for, e.g., sampling, to convert the analog metric data 142a1 to 142a(n+m) received from the RF sensors a1 to a(n+m) from analog form to digital form. The analog metric data 142a1 to 142a(n+m) is converted from analog form to digital form in synchronization with the clock signal. For example, the analog metric data 142a1 to 142a(n+m) is converted at each instance of the rising time or the falling time of the clock signal. As an example, the clock source is the processor 124. As another example, the clock source is the processor 132. In this example, the processor 132 provides the clock signal to the ADC 104 via the communication controller 136, the communication controller 130, the processor 124, the transceiver 128, and the transceiver 122. As yet another example, the processor 124 or the processor 132 receives the clock signal from the Internet and supplies the clock signal to the ADC 104.

[0090] In one embodiment, the RF sensor is disposed within the RF generator or within the matching system. For example, the RF sensor a1 is disposed within the RF generator RFGa1 or within the matching system 108.

[0091] In one embodiment, the analysis controller 106 is connected to the process controller 116 via a computer network such as a wide area network (WAN) or a local area network (LAN) or a combination thereof. An example of the WAN is the Internet, and an example of the LAN is an intranet.

[0092] In one embodiment, instead of the analysis controller 106 and the process controller 116, a single controller is used.

[0093] In one embodiment, the transceiver, which may also be referred to herein as a data transceiver, and vice versa.

[0094] In one embodiment, the variable is voltage instead of power.

[0095] In one embodiment, system 100 includes more or fewer RF generators in addition to those illustrated in FIG. 1A. For example, instead of RF generators RFGa1 to RFGan, a single RF generator is used and chuck 118 is connected to ground potential. As another example, instead of RF generators RFGa(n + 1) to RFGa(n + m), a single RF generator is used and RF coil 112 is connected to ground potential.

[0096] In one embodiment, instead of plasma chamber 114, a capacitively coupled plasma (CCP) chamber is used. For example, instead of RF coil system 1 12 and dielectric window 120, an upper electrode is used. The upper electrode is a plate made of a metal such as aluminum or an alloy thereof. The upper wall of the CCP chamber is located above the upper electrode.

[0097] In one embodiment, instead of the matching system, a separate matching system is connected to the RF generators in FIG. 1A. For example, the first matching system is connected to RF generator RFGa1 and the second matching system is connected to RF generator RFGa2. As another example, the first matching system is connected to RF generator RFGa(n + 1) and the second matching system is connected to RF generator RFGa(n + 2).

[0098] In one embodiment, one of RF sensors a1 to a(n + m) is connected at any point between the output of the corresponding RF generator and the input of the corresponding matching system. For example, RF sensor a1 is connected at output Oa1 of RF generator RFGa1 or input Ia1 of matching system 108. As another example, RF sensor a(n + m) is connected at output Oa(n + m) or input Ia(n + m).

[0099] In one embodiment, one or more additional RF sensors are connected to the RF transmission line 138. For example, the first RF sensor is connected at the output O108. As another example, the first RF sensor is connected to the RF rod of the RF transmission line 138, and the second RF sensor is connected at the output O108. As yet another example, the RF sensor is connected in proximity to the RF coil 112 as compared to the output O108. The one or more additional RF sensors are connected to the ADC104 to provide analog metric data to the ADC104. The ADC104 samples the analog metric data, outputs digital metric data, and transmits the digital metric data to the processor 124. The processor 124 determines the value of the variable based on the digital metric data.

[0100] In one embodiment, instead of the processor 124, the processor 132 analyzes the digital metric data 144 and determines to control the ADC104 to change one or more positions and one or more time windows at which additional analog metric data output by one or more of the RF sensors a1 to a(n + m) should be collected by the ADC104. For example, the processor 124 provides the digital metric data 144 to the communication controller 130. The communication controller 130 applies a network communication protocol to the digital metric data 144 to generate one or more data packets and transmits the data packets to the communication controller 136. Upon receiving the one or more data packets, the communication controller 136 applies the network communication protocol to extract the digital metric data 144 and provides the digital metric data 144 to the processor 132 for analysis. Instead of the processor 124, the processor 132 generates a control signal and transmits it to the ADC104 via the communication controller 136, the communication controller 130, the processor 124, the transceiver 128, and the transceiver 122 of the DPS102.

[0101] In one embodiment, one or more additional RF sensors are connected to an RF transmission line connected to the edge ring. The edge ring surrounds the chuck 118 and is connected to the matching system via the RF transmission line. One or more additional RF sensors are connected to the ADC 104 to provide analog metric data to the ADC 104. The ADC 104 samples the analog metric data to output digital metric data and transmits the digital metric data to the processor 124. The processor 124 determines the value of the variable based on the digital metric data.

[0102] In one embodiment, a plurality of RF coils are also arranged in addition to the plasma chamber 104. For example, the first RF coil is arranged on the dielectric window 120, and the second RF coil is arranged at a level lower than the level of the upper wall TW so as to surround the side wall SW. In this example, the first matching system is connected to the first RF coil via the first RF transmission line, and the second matching system is connected to the second RF coil via the second RF transmission line. Also, in this example, one or more RF generators are connected to the first matching system, and one or more RF generators are connected to the second matching system.

[0103] In one embodiment, instead of plasma chamber 114, another plasma chamber is used in system 100. The other plasma chamber includes an edge ring surrounding chuck 118. The edge ring is made of metal. One or more RF generators are connected to the edge ring via a matching system in the same manner as RF generators a(n+1) to a(n+m) are connected to chuck 118 via matching system 110. Also, one or more RF sensors similar to RF sensors a(n+1) to a(n+m) are connected to the RF cable connecting the RF generator to the edge ring. The one or more RF sensors measure data regarding the RF signals transmitted by the one or more RF generators, output analog metric data, and provide the analog metric data to ADC 104. ADC 104 generates digital metric data from the analog metric data in the same manner as described above and provides the digital metric data to processor 124. Processor 124 analyzes the digital metric data and determines to control ADC 104 to change one or more positions and one or more time windows at which additional analog metric data output by the one or more RF sensors should be collected by ADC 104.

[0104] FIG. 1B is a diagram of one embodiment of a matchless plasma system 150. The matchless plasma system 150 is similar to plasma system 100 except that it does not include match systems 108 and 110 (FIG. 1A). Also, the matchless plasma system 150 includes a plasma chamber 152. The matchless plasma system 150 further includes a plurality of matchless plasma sources (MPSs) a1 to a(n+m), RF sensors a1 to a(n+m), DPS 102, analysis controller 106, and process controller 116.

[0105] The plasma chamber 152 includes a chuck 118, a dielectric window 120, and a plurality of RF coils 154A, 154B, and 154C. The RF coils 154A, 154B, and 154C are disposed on the dielectric window 120. The plasma chamber 152 includes an edge ring 156 such as an extension of the lower electrode. The edge ring 156 surrounds the chuck 118.

[0106] The matchless plasma source MPSa1 is connected to the RF coil 154C via an RF connection 158a1. Examples of RF connections include conductors, RF straps, cylinders, and combinations thereof. Similarly, the matchless plasma source MPSa2 is connected to the RF coil 154B via an RF connection 158a2, and the matchless plasma source MPSan is connected to the RF coil 154A via an RF connection 158an. Also, the matchless plasma source MPSa(n + 1) is connected to the chuck 118 via an RF connection 158a(n + 1), and the matchless plasma source MPSa(n + m) is connected to the chuck 118 via an RF connection 158a(n + m).

[0107] The RF sensor a1 is connected to a point PT1 on the RF connection 158a1. For example, the RF sensor a1 is connected to a point on the conductor of the RF connection 158a1. Similarly, the RF sensor a2 is connected to a point PT2 on the RF connection 158a2, the RF sensor an is connected to a point PTn on the RF connection 158an, the RF sensor a(n + 1) is connected to a point PT(n + 1) on the RF connection 158a(n + 1), and the RF sensor a(n + m) is connected to a point PT(n + m) on the RF connection 158a(n + m). The RF sensors a1, a2, an, a(n + 1), and a(n + m) are connected to the ADC 104 by the method described above with reference to FIG. 1A.

[0108] The matchless plasma source MPSa1 generates an RF signal 140a1 and transmits the RF signal 140a1 to the RF coil 154C. Similarly, the matchless plasma source MPSa2 generates an RF signal 140a2 and transmits the RF signal 140a2 to the RF coil 154B, and the matchless plasma source MPSan generates an RF signal 140an and transmits the RF signal 140an to the RF coil 154A. Also, the matchless plasma source MPSa(n + 1) generates an RF signal 140a(n + 1) and transmits the RF signal 140a(n + 1) to the chuck 118, and the matchless plasma source MPSa(n + m) generates an RF signal 140a(n + m) and transmits the RF signal 140a(n + m) to the edge ring 156.

[0109] In addition to the RF signals 140a1 to 140a(n + m), when one or more process gases are supplied to the plasma chamber 152, plasma is generated or maintained in the plasma chamber 152. When the plasma is generated or maintained, the RF sensors a1 to a(n + m) measure the data of the RF signals 140a1 to 140a(n + m) transferred through the RF connections 158a1 to 158a(n + m) and output analog metric data. For example, the RF sensor a1 measures the data of the RF signal 140a1 and outputs analog metric data 142a1, the RF sensor a2 measures the data of the RF signal 140a2 and outputs analog metric data 142a2, the RF sensor an measures the data of the RF signal 140an and outputs analog metric data 142an, the RF sensor a(n + 1) measures the data of the RF signal 140a(n + 1) and outputs analog metric data 142a(n + 1), and the RF sensor a(n + m) measures the data of the RF signal 140a(n + m) and outputs analog metric data 142a(n + m). The remaining operations performed on the analog metric data 142a1 to 142a(n + m) have been described above with reference to FIG. 1A.

[0110] In one embodiment, instead of plasma chamber 152, another plasma chamber including a different number of RF coils, such as a greater or lesser number than that illustrated in FIG. 1B, is used. For example, another plasma chamber excludes RF coil 154B or RF coil 154A.

[0111] FIG. 2A is a diagram of one embodiment of system 200 for illustrating the functionality of RF sensor 201, DPS 102, and analysis controller 106. RF sensor 201 is an example of any one of RF sensors a1 to a(n+m) (FIG. 1A or FIG. 1B). ADC 104 includes ADC processor 210 and memory device 212. ADC processor 210 is connected to memory device 212. Transceiver 122 of DPS 102 is connected to ADC processor 210.

[0112] ADC processor 210 receives analog metric data 202 sensed by RF sensor 201, collects the analog metric data 202, and outputs digital metric data 204, for example, by sampling. For example, ADC processor 210 converts analog metric data 202 from analog format to digital format. By way of illustration, ADC processor 210 samples analog metric data 202 at a sampling rate (SR) and outputs digital metric data 204. As another example, ADC processor 210 captures snapshots of analog metric data 202 at various times and outputs digital metric data 204. Analog metric data 202 is an example of analog metric data output from any one of RF sensors a1 to a(n+m) (FIGS. 1A and 1B). For example, analog metric data 202 is an example of analog metric data 142an or 142a(n+m) (FIGS. 1A and 1B).

[0113] The ADC processor 210 stores the digital metric data 204 in the memory device 212. The ADC processor 210 accesses the digital metric data 204 from the memory device 212 and provides the digital metric data 204 to the transceiver 122.

[0114] Transceiver 122 applies a transfer protocol to digital metric data 204 to generate one or more data transfer units, and provides the one or more data transfer units to transceiver 128 of DPS 102. Transceiver 128 applies a transfer protocol to extract digital metric data 204 from the one or more data transfer units and transmits the digital metric data 204 to processor 124 of analysis controller 106. Processor 124 analyzes the digital metric data 204 to determine the location and time window at which additional analog metric data 222 (FIG. 2B) should be collected. For example, processor 124 determines that the digital metric data 204 has rising edges and falling edges. In this example, processor 124 decides to collect additional analog metric data 222 with respect to a time window that starts at the start position of the rising edge and ends at the end of the rising edge. Also, in this example, processor 124 decides to collect additional analog metric data 222 with respect to a time window that starts at the start position of the falling edge and ends at the end of the falling edge. The end of the falling edge can be an endpoint or a process point of the processing of substrate S. Processor 124 decides not to sample additional analog metric data 222 outside the time window. By way of illustration, when the location is A1 as illustrated below with reference to FIG. 2E and the time window is between times t1 and t2 as also illustrated below with reference to FIG. 2E, no additional analog metric data 222 outside the time window is collected. Further by way of illustration, referring to FIG. 2E below, no additional analog metric data 222 between time t0 and time t1 and between time t2 and t4 is collected during cycle 1 of the clock signal. Also, in a further illustration, no additional analog metric data 222 between time t4 and time t5 and between time t6 and time t7 is collected during cycle 2 of the clock signal. In a further illustration, additional analog metric data 222 is collected with respect to the time window between time t5 and time t6 at location A1 during cycle 2.In this example, the falling edge is continuous with the rising edge. Illustratively, there is no edge between the rising edge and the falling edge. As another example, the processor 124 determines to collect additional analog metric data 222 at a position between the end of the rising edge and the start of the falling edge. In this example, the additional analog metric data 222 is collected with respect to a time window in which the analog metric data 222 has a steady state.

[0115] Note that the additional analog metric data 222 is a continuation of the analog metric data 202. For example, the additional analog metric data 222 is output from the RF sensor 202 within one or more cycles of the clock signal after the analog metric data 202 is output from the RF sensor 202.

[0116] The processor 124 generates a control signal 206 having a position and a time window. The processor 124 transmits the control signal 206 to the transceiver 128 of the analysis controller 106. The control signal 206 is transferred from the transceiver 128 to the transceiver 122 of the DPS 102. The transceiver 122 provides the control signal 206 to the ADC processor 210. The processing of the control signal 206 by the ADC processor 210 will be described later with reference to FIG. 2B.

[0117] In one embodiment, note that the functions described herein as being executed by the processor 124 of the analysis controller 106 are instead executed by the processor 132 (FIGS. 1A and 1B) of the process controller 116. For example, instead of the processor 124, the processor 132 analyzes the digital metric data 204 to determine the positions and time windows at which additional analog metric data 222 should be sampled. In this example, to analyze the digital metric data 204 to determine the positions and time windows, the digital metric data 204 is transmitted from the processor 124 to the processor 132 (FIGS. 1A and 1B) of the process controller 116 via the communication controllers 130 and 136.

[0118] FIG. 2B is a diagram of one embodiment of the system 220 for illustrating the use of additional digital metric data 224 by the analysis controller 106. The system 220 includes a DPS 102, an analysis controller 106, a process controller 116, and a plasma source 226. As an example of the plasma source 226, any of the RF generators RFGa1 to RFGa(n+m) (FIG. 1A) may be mentioned. By way of illustration, when the RF sensor 201 is the RF sensor an, the plasma source 226 is the RF generator an, and when the RF sensor 201 is the RF sensor a(n+m), the plasma source 226 is the RF generator RFGa(n+m) (FIG. 1A). As another example of the plasma source 226, any of the matchless plasma sources MPSa1 to MPSa(n+m) (FIG. 1B) may be mentioned. By way of illustration, when the RF sensor 201 is the RF sensor an, the plasma source 226 is the matchless plasma source MPSan, and when the RF sensor 201 is the RF sensor a(n+m), the plasma source 226 is the matchless plasma source MPSa(n+m) (FIG. 1B).

[0119] When receiving a control signal 206 (FIG. 2A) indicating a position and a time window, the ADC processor 210 samples additional analog metric data 222 regarding the time window at that position and outputs additional digital metric data 224. The ADC processor 210 provides the additional digital metric data 224 to the transceiver 122. The transceiver 122 applies a transfer protocol to the additional digital metric data 224 to generate one or more data transfer units and transmits the one or more data transfer units to the transceiver 128 of the analysis controller 106.

[0120] The transceiver 128 applies a transfer protocol to the one or more data transfer units to obtain the additional digital metric data 224 from the data transfer units and provides the additional digital metric data 224 to the process controller 116 via the processor 124 and the communication controller 130. For example, the processor 124 of the analysis controller 106 receives the additional digital metric data 224 from the transceiver 128 of the analysis controller 106 and provides the additional digital metric data 224 to the communication controller 130. In this example, the communication controller 130 applies a network communication protocol to the additional digital metric data 224 to generate one or more data packets and transfers the one or more data packets to the communication controller 136 of the process controller 116. Further, in this example, the communication controller 136 applies a network communication protocol to the one or more data packets to extract the additional digital metric data 224 from the data packets and transmits the additional digital metric data 224 to the processor 132.

[0121] Processor 132 generates instructions to control plasma source 226 based on additional digital metric data 224. For example, processor 132 generates one or more values of a variable based on additional digital metric data 224. Illustratively, when it is determined that the amplitude of additional digital metric data 224 is greater than a predetermined threshold, processor 132 generates one or more values of a variable to increase or decrease the amplitude of the metric. As another illustration, when it is determined that the amplitude of additional digital metric data 224 is less than a predetermined threshold, processor 132 generates one or more values of a variable to increase or decrease the amplitude of the metric.

[0122] Instructions including one or more values of a variable are transmitted from processor 132 to processor 124 of analysis controller 106 via communication controllers 136 and 130. Upon receiving the instructions, processor 124 controls plasma source 226 according to one or more values of the variable. For example, processor 124 controls RF generator RFGan to modify the frequency or power of RF generator RFGan, or the duty cycle of the state, or the number of states of the operation, or a combination thereof. As another example, processor 124 controls RF generator RFGa(n+m) to modify the frequency or power of RF generator RFGa(n+m), or the duty cycle of the state, or the number of states of the operation, or a combination thereof. As another example, processor 124 controls matchless plasma source MPSan to modify the frequency or power of matchless plasma source MPSan, or the duty cycle of the state, or the number of states of the operation, or a combination thereof. As yet another example, processor 124 controls matchless plasma source MPSa(n+m) to modify the frequency or power of matchless plasma source MPSa(n+m), or the duty cycle of the state, or the number of states of the operation, or a combination thereof.

[0123] Referring to FIG. 2A, the processor 124 determines to modify the location and time window at which additional digital metric data 224 is collected. For example, the processor 124 determines that additional analog metric data 222 is collected at a first location and with respect to a first time window, such as by sampling, or performing a conversion from analog to digital format. In this example, the first location is the start point of a first edge, such as a rising edge or a falling edge. Also, in this example, the processor 124 analyzes the additional digital metric data 224 and determines that the additional digital metric data 224 is changing at a rate faster than a predetermined rate during the first time window. When it is determined that the additional digital metric data 224 is changing at a rate faster than the predetermined rate, the processor 124 determines to modify the first location to a second location between the first edge and a second edge. The second edge is consecutive to the first edge. The second location is between the end of the first edge and the start of the second edge. Also, in this example, the processor 124 determines to modify the first time window to a second time window, where the second time window is a period that is larger or smaller than the first time window. In this example, the processor 124 generates a control signal 228 (FIG. 2A) that includes the second location and the second time window, and transmits the control signal 228 to the ADC processor 210 via the transceiver 128 and the transceiver 122. In response to receiving the control signal 228, the ADC processor 210 samples additional analog metric data 230 received from the RF sensor 210 at the second location and with respect to the second time window, and outputs additional digital metric data 232.

[0124] In this example, the ADC processor 210 transmits additional digital metric data 232 to the transceiver 122. The transceiver 122 applies a transfer protocol to the additional digital metric data 232 to generate one or more transfer units and transmits the transfer units to the transceiver 128. The transceiver 122 applies the transfer protocol to the transfer units to extract the additional digital metric data 232 and provides the additional digital metric data 232 to the processor 124. The processor 124 transmits the additional digital metric data 232 to the processor 132 via the communication controllers 130 and 136 in the same manner as the additional digital metric data 224 (FIG. 2B) is transmitted to the processor 132. In this example, the processor 132 controls the plasma source 226 based on the additional digital metric data 232 in the same manner as the processor 132 controls the plasma source 226 according to the additional digital metric data 224.

[0125] As another example, the processor 124 determines that the analog metric data 202 is collected at a first position with respect to a first time window. The first position is at the end of a first edge such as a rising edge or a falling edge. The first time window ends before the start of a second edge consecutive to the first edge. In this example, the processor 124 analyzes the digital metric data 204 and determines that the digital metric data 204 changes at a rate slower than a predetermined rate during the first time window. When it is determined that the digital metric data 204 changes at a rate slower than the predetermined rate, the processor 124 determines to correct the first position to a second position, and the second position is the start time of the first edge or the start time of the second edge. The second edge is consecutive to the first edge. Also, in this example, the processor 124 determines to correct the first time window to a second time window, and the second time window is a period larger or smaller than the first time window. By way of illustration, the second time window is up to the end of the first edge or the end of the second edge.

[0126] In one embodiment, instead of processor 132, processor 124 controls plasma source 226 based on additional digital metric data 224. For example, the additional digital metric data 224 is not sent from analysis controller 106 to process controller 116. Rather, in this example, processor 124 controls any one of RF generators RFGa1 to RFGa(n + m) or any one of matchless plasma sources MPSa1 to MPS(n + m) based on the additional digital metric data 224.

[0127] In one embodiment, instead of processor 132, processor 124 controls plasma source 226 based on further digital metric data 232. For example, the further digital metric data 232 is not sent from analysis controller 106 to process controller 116. Rather, in this example, processor 124 controls any one of RF generators RFGa1 to RFGa(n + m) or any one of matchless plasma sources MPSa1 to MPS(n + m) based on the further digital metric data 232.

[0128] Figure 2C is a diagram of one embodiment of system 250 for illustrating that received digital metric data 204 is analyzed by processor 124 of analysis controller 106 to determine the location and time window in the memory device of analysis controller 106 where portions of digital metric data 204 should be stored. System 250 includes RF sensor 201, DPS 102, and analysis controller 106. Processor 124 receives digital metric data 204 and determines the location and time window based on digital metric data 204. Processor 124 stores portion 252 of digital metric data 204 at the location and in the time window in memory device 126 of analysis controller 106. Processor 124 does not store the remaining portion of digital metric data 204 in memory device 126 of analysis controller 106. For example, processor 124 does not store portions of digital metric data 204 that are outside the location and time window.

[0129] In one embodiment, processor 124 stores digital metric data 204 in memory device 126 for a preset period and erases portions of digital metric data 204 that are outside the location and time window after the preset period.

[0130] Note that in one embodiment, the functions described herein as being performed by processor 124 of analysis controller 106 are instead performed by processor 132 of process controller 116. For example, instead of processor 124, processor 132 analyzes digital metric data 204 to determine the location and time window where portion 252 should be stored in memory device 134 of process controller 116. In this example, for the analysis of digital metric data 204, digital metric data 204 is transmitted from analysis controller 106 to process controller 116 via communication controller 130 of analysis controller 106 and communication controller 136 of process controller 116.

[0131] FIG. 2D is a diagram of one embodiment of system 270 for illustrating that portion 252 is sent from analysis controller 106 to process controller 116 to control plasma source 226. System 270 includes analysis controller 106, a process controller, and plasma source 226.

[0132] Processor 124 of analysis controller 106 accesses portion 252 from memory device 134. Processor 124 sends portion 252 to communication controller 130. Communication controller 130 applies a network communication protocol to portion 252 to generate one or more data packets and sends the data packets to communication controller 136 of process controller 136. Process controller 136 applies a network communication protocol to the data packets to extract portion 252 and provides portion 252 to processor 132. Processor 132 generates an instruction including one or more values of variables for controlling plasma source 226 based on portion 252. Processor 132 sends the instruction to processor 124 of analysis controller 106 via communication controllers 136 and 130. Processor 124 controls plasma source 226 according to the instruction.

[0133] FIG. 2E is a diagram for illustrating a method 280 of determining values of variables regarding a state using additional digital metric data 224 (FIG. 2B). The method 280 is illustrated with respect to a graph 282. The graph 282 includes a plot 284 of metric versus time t. The time t has units such as microseconds (μs) or milliseconds (ms). The plot 284 is of metric data such as digital metric data 204 (FIG. 2A). For example, the plot 284 is constructed by a processor 124 of the analysis controller 106 from digital metric data 204 generated from analog metric data 202 (FIG. 2A). By way of illustration, the processor 124 combines samples such as sample points of the digital metric data 204 to generate the plot 284. As an example, the plot 284 is the envelope of the forward power of an RF signal 290 supplied by an RF generator or a matchless plasma source. For example, the plot 284 is the envelope of the forward power or supply power of RF signals 140an or 140a(n+m) (FIGS. 1A and 1B). As another example, the plot 284 is the envelope of the delivered power of the RF signal 290. The metric of the plot 284 is y plotted on the y-axis, and the time t is plotted on the x-axis.

[0134] The x-axis of the graph 282 is divided into a plurality of time intervals or periods. For example, the x-axis of the graph 282 is divided into a first time interval between time t0 and time t1, a second time interval between time t1 and time t2, a third time interval between time t2 and time t3, a fourth time interval between time t3 and time t4, a fifth time interval between time t4 and time t5, a sixth time interval between time t5 and time t6, a seventh time interval between time t6 and time t7, an eighth time interval between time t7 and time t8, a ninth time interval between time t8 and time t9, and a tenth time interval between time t9 and time t10, etc. The time intervals of the x-axis of the graph 282 are equal. For example, the first time interval is equal to the second time interval, and the second time interval is equal to the third time interval. The third time interval is equal to the fourth time interval, and so on.

[0135] Each time along the x-axis of graph 282 provides a position. For example, time t0 is position A0. Similarly, time t1 is position A1, time t2 is position A2, and time t3 is position A3. The positions are repeated in each cycle of the clock signal. For example, positions A0 to A3 occur during cycle 1 of the clock signal, and positions A0 to A3 occur again during cycle 2 of the clock signal. Cycle 2 is consecutive to cycle 1. Positions A0 to A3 are the times when the metric of RF signal 290 is collected by ADC processor 210 (Figure 2A), and for example, sampling or conversion from analog form to digital form is performed to output sample points.

[0136] As shown in Figure 2E, the metric data of plot 284 is repeated for each cycle of the clock signal. For example, the metric data of plot 284 has states S1, S2, S3, and S4 during cycle 1 of the clock signal. During state S1, the metric data of plot 284 has values in the range from value M7 to -M7. During state S2, the metric data has values in the range from value M5 to -M5. During state S3, the metric data has values in the range from value M3 to -M3. During state S4, the metric data has values in the range from value M1 to -M1. Value M3 is greater than value M1, value M5 is greater than value M3, and value M7 is greater than value M5. Value M1 is a positive value. The states S1 to S4 of the metric data of plot 284 are repeated during cycle 2 of the clock signal. In this way, the states S1 to S4 of the metric data of plot 284 are repeated during additional clock cycles of the clock signal. The metric data of plot 284 transitions from state S1 to state S2, from state S2 to state S3, and from state S3 to state S4 during cycle 1 of the clock signal. The metric data of plot 284 transitions from state S4 during cycle 1 of the clock signal to state S1 during cycle 2 of the clock signal, and the transitions from state S2 to S4 are repeated during cycle 2 of the clock signal.

[0137] Method 280 is executed by processor 124 (FIG. 1A) of analysis controller 106. In operation 286 of method 280, processor 124 obtains metric data of plot 284 regarding a time window such as the time interval between times t1 and t2 starting from position A1. For example, a portion of the metric data of plot 284 is obtained from ADC processor 210 (FIG. 2A) by processor 124 of analysis controller 106. The portion of the metric data of plot 284 between times t1 and t2 starting from position A1 represents state S2 of the metric data. Also, the portion of the metric data of plot 284 is an example of additional digital metric data 224 (FIG. 2B).

[0138] In operation 288 of method 280, processor 124 of analysis controller 106 controls a variable regarding state S2 based on the metric data regarding state S2 of plot 284. For example, processor 124 determines whether the metric data regarding state S2 is within a predetermined range from a pre-stored value of the metric. The predetermined range and the pre-stored value of the metric are stored in memory device 126 of analysis controller 106. In response to determining that the metric data collected regarding state S2 is not within the predetermined range from the pre-stored value of the metric, processor 124 controls a variable of plasma source 226 (FIG. 2B). The processor of analysis controller 106 controls plasma source 226 until the metric data regarding state S2 obtained from ADC processor 210 is within the predetermined range from the pre-stored value of the metric. By way of illustration, the variable is controlled to achieve a processing speed, such as an etching speed or a deposition speed, for processing substrate S within plasma chamber 114 of FIG. 1A or plasma chamber 152 of FIG. 1B.

[0139] The variable related to state S2 is of the RF signal 290 generated by the plasma source 226 (FIG. 2B), and the plasma source 226 corresponds to the RF sensor 201 (FIG. 2A) (e.g., in a one-to-one relationship, etc.). For example, when the metric data of plot 284 is generated based on the analog metric data 202 (FIG. 2A) output from the RF sensor an, the variable is of the RF signal 140an generated by the RF generator RFGan (FIG. 1A) or the matchless plasma source MPSan (FIG. 1B). As another example, when the metric data of plot 284 is generated based on the analog metric data 202 received from the RF sensor a(n + m), the variable is of the RF signal 140a(n + m) generated by the RF generator RFGa(n + m) (FIG. 1A) or the matchless plasma source MPSa(n + m) (FIG. 1B). The RF sensor 201 measures data regarding the RF signal 290, outputs the metric data of plot 284, and one or more values of the variable are determined based on the metric data.

[0140] In one embodiment, the method 280 is executed by the processor 132 of the process controller 116 instead of the processor 124 of the analysis controller 106. For example, the processor 124 transmits, via the communication controllers 130 and 136, the metric data regarding the time window between times t1 and t2 at position A1 to the processor 132 of the process controller 116. When acquiring the metric data regarding the time window between times t1 and t2 at position A1 from the processor 124, the processor 132 of the process controller 116 executes the operation 288 of the method 280.

[0141] In one embodiment, instead of the position A1 that defines the start of state S2, a position associated with a falling transition, such as a falling edge, between two consecutive states of plot 284 is used to execute method 200. For example, the position is at the start of the falling transition between states S1 and S2, or occurs during the falling transition between states S1 and S2. Also, in this embodiment, a time window from the position is used instead of the time window between times t1 and t2. For example, the time window is from the start of the falling transition to the time within the falling transition. As another example, the time window is from a position within the falling transition to the end of the falling transition. Note that the falling transition occurs from a state with a higher metric level to a state with a lower metric level. The state with the lower metric level has a smaller amount of power or voltage compared to the amount of power or voltage of the state with the higher metric level.

[0142] Similarly, in one embodiment, a position associated with a rising transition, such as a rising edge, between two consecutive states of a plot of metric data is used to execute method 200. For example, the position is at the start of the rising transition between two consecutive states. In this example, there is no state between the two consecutive states. Also, in this embodiment, a time window from the position is used. For example, the time window is from the start of the rising transition to the time within the rising transition. As another example, the time window is from a position within the rising transition to the end of the rising transition. Note that the rising transition occurs from a state with a lower metric level to a state with a higher metric level. The state with the lower metric level has a smaller amount of power or voltage compared to the amount of power or voltage of the state with the higher metric level.

[0143] In one embodiment, instead of state S2, another state such as state S1, S3, or S4 can be used to execute method 200. For example, in operation 286, instead of obtaining the metric data of plot 284 for the time window between times t1 and t2 starting from position A1, the metric data of plot 284 for the time window between times t2 and t3 starting from position A2 is obtained. Operation 288 is executed based on the metric data of plot 284 for the time window between times t2 and t3 at position A2.

[0144] In one embodiment, instead of state S2, a sub - state or a slice can be used to execute method 200. Examples of sub - states and slices are provided below.

[0145] In one embodiment, when the processor 124 of the analysis controller 106 determines that the metric data regarding state S2 obtained in operation 286 is not within a predetermined range, it determines that the plasma system having the plasma source 226 is malfunctioning. In this embodiment, the processor 124 controls the display device of the analysis controller 106 to display an alarm indicating that the plasma system is malfunctioning, or controls the speaker of the analysis controller 106 to sound an alarm indicating that the plasma system is malfunctioning. The display device and the speaker of the analysis controller 106 are connected to the processor 124.

[0146] In one embodiment, a processor such as processor 124 or processor 132 determines parameters from metric data obtained in operation 286. For example, the processor determines ion energy, wafer bias, reflectivity, or processing speed. Examples of processing speed include etching speed or deposition speed. In this example, reflectivity is the ratio of reverse power to forward power. By way of example, the processor accesses a table from a memory device such as memory device 126 or 134 to determine one or more parameter values corresponding to the metric for which metric data was obtained in operation 286, for example, having a unique relationship. As another example, the processor calculates reflectivity based on forward power and reverse power. The processor determines whether one or more parameter values are within a preset range stored in the memory device. The processor controls the plasma source 226 until one or more parameter values are within the preset range.

[0147] In one embodiment, one or more RF generators are controlled in operation 288 based on metrics measured by RF sensor 201. For example, one or more of RF generators RFGa1, RFGa2, and RFGan are controlled based on metrics measured by RF sensor an (FIG. 1A). As another example, one or more of RF generators RFGa(n + 1), RFGa(n + 2), and RFGa(n + m) are controlled based on metrics measured by RF sensor a2 (FIG. 1A).

[0148] FIG. 3A is a diagram of one embodiment of method 300 for illustrating the use of statistical values of metrics to determine values of variables. Method 300 includes operation 286 and is executed by processor 124 (FIG. 2B) of analysis controller 106. For example, processor 124 receives digital metric data 224 (FIG. 2B) regarding position A1 and a time window between times t1 and t2 from ADC processor 210 of DPS 102 (FIG. 2C).

[0149] In method 300, operation 304 is executed after operation 286. In operation 304, when digital metric data 224 regarding the time window between times t1 and t2 at position A1 is received, a statistical value of the digital metric data 224 is determined. For example, processor 124 of analysis controller 106 calculates a statistical value from the digital metric data 224. Examples of statistical values include the average value of the digital metric data 224, the median value of the digital metric data 224, the maximum value of the digital metric data 224, and the minimum value of the digital metric data 224. The statistical value is determined to reduce the amount of digital metric data 224 for determining variables of plasma source 226.

[0150] In operation 306 of method 300, processor 124 controls a variable based on the statistical value. For example, if it is determined that the statistical value determined in operation 304 is outside a preset range, processor 124 controls the variables of plasma source 226 until the statistical value of the metric is within the preset range. If it is determined that the statistical value determined in operation 304 is within the preset range, the value of the variable is maintained by processor 124. Illustratively, processor 124 controls plasma source 226 until the statistical value of the digital metric data 224 regarding state S2 obtained from ADC processor 210 is within the preset range. As another example, the variable is controlled by processor 124 until the statistical value of the processing speed for processing substrate S in plasma chamber 114 of FIG. 1A or plasma chamber 152 of FIG. 1B is achieved.

[0151] In one embodiment, when the processor of analysis controller 106 determines that the statistical value determined in operation 304 is outside a preset range, it determines that the plasma system having plasma source 226 is malfunctioning.

[0152] In one embodiment, method 300 is performed with respect to positions other than position A1 within cycle 1 of the clock signal and for time windows other than the time window between times t1 and t2. For example, method 300 is performed with respect to position A2 and for the time window between times t2 and t3 (FIG. 2E).

[0153] In one embodiment, method 300 is performed by processor 132 of process controller 116 instead of processor 124. In this embodiment, method 300 includes operation 286 of obtaining, from processor 124 of analysis controller 106, the value of the metric for position A1 and for the time window between times t1 and t2 (FIG. 2E).

[0154] In one embodiment, instead of position A1, the position associated with the falling transition is used to perform method 300.

[0155] Similarly, in one embodiment, instead of position A1, the position associated with the rising transition is used to perform method 300.

[0156] In one embodiment, instead of state S2, a sub - state or slice can be used to perform method 300.

[0157] FIG. 3B is an embodiment of a flowchart of method 330 for illustrating the use of consensus among metrics sensed by a plurality of RF sensors. Method 330 is performed by processor 124 of analysis controller 106.

[0158] In operation 332 of method 330, a metric set 1 for a time window between times t1 and t2 at position A1 is obtained in the same manner as operation 286 (Figure 2E) is executed. Metric set 1 includes digital metric data output from ADC processor 210 (Figure 2A). ADC processor 210 outputs the digital metric data of metric set 1 by sampling the analog metric data received from RF sensor a1.

[0159] In operation 334 of method 330, a statistical value 1 of the metric is determined from metric set 1 in the same manner as operation 304 (Figure 3A) is executed. For example, processor 124 calculates the average value or median value of the metric from metric set 1.

[0160] In operation 336 of method 330, a metric set 2 for a time window between times t1 and t2 at position A1 is obtained in the same manner as metric set 1 is obtained (Figure 2E). For example, ADC processor 210 receives analog metric data from RF sensor a2 and samples the analog metric data to output the digital metric data of metric set 2. In this example, processor 124 of analysis controller 106 obtains metric set 2 from ADC processor 210. Metric set 2 has an amplitude different from that of metric set 1. By way of example, metric set 2 has a different amplitude at position A1 and a different amplitude between times t1 and t2 compared to that of metric set 1.

[0161] In operation 338 of method 330, a statistical value 2 of the metric is determined from metric set 2 in the same manner as processor 124 determines statistical value 1 from metric set 1. For example, processor 124 calculates the average value or median value of the metric from metric set 2.

[0162] In operation 340 of method 330, a metric set 3 for a time window between times t1 and t2 at position A1 is obtained in the same manner as metric set 1 is obtained (FIG. 2E). For example, ADC processor 210 receives analog metric data from RF sensor a3, samples the analog metric data, and outputs digital metric data for metric set 3. In this example, processor 124 of analysis controller 106 obtains metric set 3 from ADC processor 210. Metric set 3 has an amplitude different from that of metric set 1. By way of illustration, metric set 3 has a different amplitude at position A1 and a different amplitude between times t1 and t2 as compared to those of metric set 1 and metric set 2.

[0163] In operation 342 of method 330, a metric statistic 3 is determined from metric set 3 in the same manner as processor 124 determines statistic 1 from metric set 1. For example, processor 124 calculates the average value or median value of the metrics from metric set 3.

[0164] In operation 344 of method 330, it is determined by processor 124 whether there is a consensus among a majority of the statistics determined in operations 334, 338, and 342. For example, processor 124 determines whether at least two of the three statistics 1 to 3 are within a pre-stored range. The pre-stored range is stored in memory device 126 of analysis controller 106. If it is determined that at least two of the three statistics 1 to 3 are within the pre-stored range, processor 124 determines that there is a consensus among a majority of the statistics 1 to 3 and executes operation 346. On the other hand, if it is determined that at least two of the three statistics 1 to 3 are outside the pre-stored range, processor 124 determines that there is no consensus among a majority of the statistics 1 to 3 and executes operation 348.

[0165] In operation 346 of method 330, when it is determined that a consensus exists, the processor 124 controls the variables of the plasma source 226 (FIG. 2B). For example, if it is determined that statistical values 1 and 2 are within a pre-stored range, the processor 124 controls the variable of RF generator RFGa1 or the variable of RF generator RFGa2 or both variables. In this example, the variable of RF generator RFGa1 is controlled until statistical value 1 is within the preset range, and the variable of RF generator RFGa2 is controlled until statistical value 2 is within the preset range. As another example, if it is determined that statistical values 1 and 2 are within a pre-stored range, the processor 124 controls the variable of matchless plasma source MPSa1 or the variable of matchless plasma source MPSa2 or both variables. In this example, the variable of matchless plasma source MPSa1 is controlled until statistical value 1 is within the preset range, and the variable of matchless plasma source MPSa2 is controlled until statistical value 2 is within the preset range.

[0166] In operation 348 of method 330, the value of the variable is not controlled based on statistical values 1 to 3. For example, the processor 124 determines not to control the value of the variable by applying statistical values 1 to 3. Rather, in this example, the processor 124 generates an instruction to change one or more of RF sensors a1 to a3. By way of illustration, the instruction is displayed on the display device of the analysis controller 106 by the processor 124 or output as a sound via the speaker of the analysis controller 106. As another example, the processor 124 determines to change the position where a metric set should be collected by RF sensor a1, the position where a metric set should be collected by RF sensor a2, and the position where a metric set should be collected by RF sensor a3 from position A1, or change the time window from the time window between times t1 and t2, or change a combination thereof. By way of illustration, the position is changed from A1 to A2 (FIG. 2E), or the time window is changed from the time window between times t1 and t2 to the time window between times t2 and t3.

[0167] In one embodiment, method 330 is executed by processor 132 of process controller 116 instead of processor 124. For example, processor 132 obtains metric sets 1, 2, and 3 from processor 124 via communication controllers 130 and 136 and executes method 330.

[0168] In one embodiment, the statistical value is a value generated by a virtual sensor implemented within the RF sensor. For example, the processor of RF sensor a1 generates the statistical value. As another example, a combination of the processor of RF sensor a1 and processor 124 generates the statistical value. As another example, a combination of the processor of RF sensor a1 and processor 132 generates the statistical value.

[0169] In one embodiment, method 330 is executed on the analog metric data output from RF sensors a(n + 1) to a(n + 3) instead of RF sensors a1 to a3.

[0170] In one embodiment, method 330 is executed on any other number of metric sets. For example, method 330 is executed on the analog metric data output from RF sensors a1 to an. As another example, method 330 is executed on the analog metric data output from RF sensors a(n + 1) to a(n + m).

[0171] FIG. 3C is a flowchart of one embodiment of method 350 for illustrating the use of statistical values of metrics instead of all values of metrics obtained with respect to position and time window. Method 350 is executed by processor 124.

[0172] Method 350 includes operation 286. In operation 352 of the method, the processor 124 determines whether the number of metric values in the time window between position A1 and times t1 and t2 is greater than a predetermined threshold. As an example, the processor 124 counts the number of values, such as samples, of the digital metric data 224 (FIG. 2B) for the time window between times t1 and t2 at position A1 and compares the number of values with a predetermined threshold. As another example, a counter and a comparator of the analysis controller 106 are connected to the processor 124. In this example, when receiving the values of the digital metric data 224 in the time window between position A1 and times t1 and t2, the processor 124 provides the values to the counter. Further, in this example, the counter counts the number of values in the time window between position A1 and times t1 and t2 and outputs the count, and the comparator receives the count from the counter. In this example, the comparator determines whether the count is greater than a predetermined threshold. The predetermined threshold is stored in the memory device 126.

[0173] When it is determined that a count, such as the number of metric values in the time window between position A1 and times t1 and t2, is greater than a predetermined threshold, operation 304 of method 350 is executed. Operation 306 of method 350 is executed after operation 304 is executed. On the other hand, when it is determined that the number of metric values in the time window between position A1 and times t1 and t2 is not greater than the predetermined threshold, operation 288 of method 350 is executed.

[0174] In one embodiment, method 350 is executed by the processor 132 (FIG. 2D) of the process controller 116 instead of the processor 124. In this embodiment, the predetermined threshold is stored in the memory device 134 of the process controller 116.

[0175] In one embodiment, operation 352 is performed by the counters and comparators of process controller 116 instead of the counters and comparators of analysis controller 106. The counters and comparators of process controller 116 are connected to processor 132. When processor 132 receives the values of the metrics in the time window between position A1 and times t1 and t2 from processor 124, processor 132 provides the values to the counter of process controller 116. The counter of process controller 116 and the comparator of process controller 116 perform the same aforementioned operations as performed by the counters and comparators of analysis controller 106.

[0176] FIG. 4 is a diagram of one embodiment of method 400 for illustrating that the position and time window for collecting analog metric data can vary with a predetermined number of cycles of a clock signal. Method 400 is performed by processor 124 of analysis controller 106. Digital metric data is acquired at a certain position and time window during each of a predetermined number of cycles of the clock signal, such as cycle 1. Processor 124 modifies the position or the time window or a combination thereof with respect to a preset number of cycles, such as cycle 2 or cycle 3 or both cycles 2 and 3, during which additional digital metric data is to be acquired. Cycle 3 of the clock signal is consecutive to cycle 2. The predetermined number of cycles and the preset number of cycles are stored in memory device 126 of analysis controller 106.

[0177] Method 400 is illustrated with respect to graph 282. Method 400 includes an operation 402 in which digital metric data is acquired by processor 124 from ADC processor 104 (FIG. 2C) for each of a predetermined number of cycles of a clock signal. For example, in operation 402, digital metric data regarding a time window between times t1 and t2 starting from position A1 of plot 284 is output from ADC processor 210 and transmitted to processor 124. Times t1 and t2 occur during cycle 1 of the clock signal. Note that the time window between times t1 and t2 corresponds to state S2 of the metric data of plot 284. As another example, operation 402 is the same as operation 286 (FIG. 2E) except that it is applied to a predetermined number of cycles of the clock signal.

[0178] Method 400 further includes an operation 404 of controlling a variable during a preset number of cycles of the clock signal following the predetermined number of cycles of the clock signal. The variable is controlled based on the digital metric data acquired during operation 402. For example, operation 404 is the same as operation 288 (FIG. 2E) except that it is executed based on the digital metric data acquired during cycle 1 of the clock signal. By way of illustration, during state S2 of the metric data of plot 284, processor 124 controls the variable of plasma source 226 based on the metric data acquired in operation 402. State S2 of the metric data occurs during a preset number of cycles, such as cycle 2 of the clock signal.

[0179] Method 400 also includes operation 406 of obtaining metric data of plot 284 regarding a time window between times t4 and t5 starting from position A0 for each of a preset number of cycles of the clock signal. For example, instead of sampling analog metric data 222 (FIG. 2B) during cycle 2 of the clock signal to generate plot 284 regarding a time window between times t5 and t6 at position A1, the analog metric data 222 is sampled by ADC processor 104 regarding a time interval between times t4 and t5. The analog metric data 222 is sampled by ADC processor 104 regarding a time interval between times t4 and t5 at position A0, outputs digital metric data 224, which is transmitted from ADC processor 104 to processor 124 of analysis controller 106. Note that the time window between times t4 and t5 corresponds to state S1 of the metric data of plot 284, and the time window between times t5 and t6 corresponds to state S2 of the metric data of plot 284.

[0180] Method 400 includes operation 408 of controlling a variable of plasma source 226 based on the metric data obtained during operation 406. For example, operation 408 is the same as operation 288 (FIG. 2E), except that it is executed based on the metric data of state S1 sampled during cycle 2 of the clock signal. The variable is controlled during a pre-stored number of cycles of the clock signal following a preset number of cycles of the clock signal. The preset number of cycles is stored in memory device 126 of analysis controller 106.

[0181] In one embodiment, method 400 is executed by processor 132 of process controller 116 instead of processor 124 of analysis controller 106. For example, during operation 402, the digital metric data used to generate plot 284 is output from ADC processor 104 during cycle 1 of the clock signal, sent from ADC processor 104 to processor 124, and further sent from analysis controller 106 to processor 132 of process controller 116. In this embodiment, the predetermined number of cycles of the clock signal, the preset number of cycles of the clock signal, and the pre-stored number of cycles of the clock signal are stored in memory device 134 of process controller 116.

[0182] In one embodiment, method 400 is executed according to each sub-state or each slice instead of each state of the metric data of plot 284.

[0183] Operations 406 and 408 are described with reference to the time window between position A0 and times t4 and t5, but note that in one embodiment, operations 406 and 408 are applicable to other positions such as position A2 and other time windows such as the time window between times t6 and t7.

[0184] FIG. 5A is one embodiment of graph 500 for illustrating the states, sub-states, and slices of the metric data of a metric. As an example, the time interval of a slice of metric data is in microseconds. By way of illustration, a slice of the metric data of a metric occurs at a time interval from 5 microseconds (μs) to 7 microseconds. As another illustration, the slice occurs at a time interval of 6 microseconds. As another illustration, the slice occurs at a time interval of 6.5 microseconds. As yet another illustration, the slice occurs at a time interval of 7 microseconds. Note that a sub-state has a smaller time interval than a state, and a slice has a smaller time interval than a sub-state.

[0185] Graph 500 includes a plot 502 of a metric versus time t. The metric of plot 502 is plotted on the y-axis and the time t is plotted on the x-axis. Plot 502 is an example of digital metric data 204 (FIG. 2C). For example, plot 502 is constructed from sample points of digital metric data 204 by processor 124 (FIG. 1A) of analysis controller 106 or by processor 132 of process controller 116.

[0186] During cycle 1 of the clock signal, the metric data of plot 502 has state S1. For example, during the time window between time t0 and time t0.5, the metric data of plot 502 has a plurality of metric values in the range from metric value M0.5 to metric value M8. By way of illustration, plot 502 includes metric values M0.5, M1, M2, M3, M4, M5, M6, M7, and M8 during state S1. Metric value M0.5 is half of metric value M1 and time t0.5 is at the midpoint of the time interval between time t0 and t1. As another illustration, the metric data of plot 502 transitions from metric value M0.5 to metric value M8 during state S1 of the metric data of plot 502. The transition from metric value M0.5 to metric value M8 is an example of a rising transition.

[0187] Metric value M1 is greater than metric value M0 and less than metric value M2. Metric value M2 is less than metric value M3. Metric value M4 is greater than metric value M3, metric value M5 is greater than metric value M4. Metric value M6 is greater than metric value M5, metric value M7 is greater than metric value M6. Metric value M8 is greater than metric value M7.

[0188] Also, during cycle 1 of the clock signal, the metric data of plot 502 has state S2. As an example, during the time window between time t0.5 and time t1.5, the metric data of plot 502 has a plurality of metric values, and each of the metric values is in the range from metric value M7.5 to metric value M8. Time t1.5 is at the midpoint of the time interval between time t1 and time t2. Metric value M7.5 is between metric value M8 and metric value M7. For example, metric value M7.5 is at the midpoint between metric values M7 and M8. The state S2 of the metric data of plot 502 is an example of a steady state.

[0189] During cycle 1 of the clock signal, the metric data of plot 502 has state S3. For example, during the time window between time t1.5 and time t2, the metric data of plot 502 has a plurality of metric values in the range from metric value M8 to metric value M4. Metric value M8 is greater than metric value M7.5. The metric data of plot 502 transitions from metric value M8 to metric value M4 during state S1 of the metric data. The transition from metric value M8 to metric value M4 is an example of a falling transition.

[0190] Furthermore, during cycle 1 of the clock signal, the metric data of plot 502 has state S4. For example, during the time window between time t2 and time t2.5, the metric data of plot 502 has metric value M4. Time t2.5 is at the midpoint of the time interval between time t2 and t3. The state S4 of the metric data of plot 502 is an example of a steady state.

[0191] Furthermore, during cycle 1 of the clock signal, the metric data of plot 502 has state S5. For example, during the time window between time t2.5 and time t3, the metric data of plot 502 has a plurality of metric values in the range from metric value M4 to metric value M1.3. The metric value M1.3 is greater than the metric value M1 and less than the metric value M2. The metric value M1.3 is 30% greater than the metric value M1. The metric data of plot 502 transitions from metric value M4 to metric value M1.3 during state S5 of the metric data. The transition from metric value M4 to metric value M1.3 is an example of a falling transition.

[0192] During cycle 1 of the clock signal, the metric data of plot 502 has state S6. For example, during the time window between time t3 and time t4, the metric data of plot 502 has a plurality of metric values in the range from metric value M1.3 to metric value M0.5.

[0193] The states S1 - S6 of the metric data of plot 502 are repeated during each additional cycle of plot 502. For example, during each of cycles 2 and 3 of the clock signal, the metric data of plot 502 has states S1 - S6.

[0194] During cycle 2 of the clock signal, the sub-states within each state of the metric data of plot 502 are illustrated, and each of the sub-states has a time interval smaller than the state. For example, during state S2 of cycle 2 of the clock signal, the metric data of plot 502 has a sub-state S2a. Illustratively, during the time window between time t4.5 and time t4.75, the metric data of plot 502 has a metric value M8. Time t4.5 is at 50 percent of the time interval between time t4 and t5, and time t4.75 is at 75 percent of the time interval between time t4 and t5. In sub-state S2a of state S2 of cycle 2 of the clock signal, the metric value of the metric data ranges from M8 to M7.8, where metric value M7.8 is between metric values M7.5 and M8. As another example, during state S2 of cycle 2 of the clock signal, the metric data of plot 502 has a sub-state S2b. Illustratively, during the time window between time t4.75 and time t5.3, the metric data of plot 502 has a metric value M7.5. Time t5.3 is at 30 percent of the time interval between time t5 and t6. During sub-state S2b, the metric value of the metric data ranges from M7.8 to M7.5. As yet another example, during state S2 of cycle 2 of the clock signal, the metric data of plot 502 has a sub-state S2a. Illustratively, during the time window between time t5.3 and time t5.5, the metric data of plot 502 has a metric value M8. Time t5.5 is at the midpoint of the time interval between time t5 and t6.

[0195] As yet another example, during state S6 of cycle 2 of the clock signal, the metric data of plot 502 has a sub-state S6a. By way of illustration, during the time window between time t7 and time t7.5, the metric data of plot 502 has a metric value M1. Time t7.5 is at the midpoint of the time interval between time t7 and time t8. In sub-state S6a, the metric value of the metric data ranges from M1.3 to M1. As another example, during state S6 of cycle 2 of the clock signal, the metric data of plot 502 has a sub-state S6b. By way of illustration, during the time window between time t7.5 and time t8, the metric data of plot 502 has a metric value M0.5. In sub-state S2b, the metric value of the metric data ranges from M1 to M0.5.

[0196] During cycle 3 of the clock signal, each sub-state or slice within each state of the metric data of plot 502 is illustrated, and each of the slices has a time interval smaller than the time interval during which the sub-state occurs. For example, during state S1 of cycle 3 of the clock signal, the metric data of plot 502 has a plurality of slices. By way of illustration, during the time window between time t8 and time t8.5, the metric data of plot 502 is divided into four parts. Each part of state S1 during cycle 3 occurs over an equal time interval. The first slice of state S1 during cycle 3 occurs over or is sampled during the time interval between time t8 and time t8.125, and the second slice of state S1 during cycle 3 occurs over or is sampled during the time interval between time t8.125 and time t8.25. Time 8.125 is at position A0.125 within cycle 3. As another example, during sub-state S2a of cycle 3 of the clock signal, the metric data of plot 502 has a plurality of slices. By way of illustration, during the time window between time t8.5 and time t8.75, the metric data of plot 502 is divided into two parts, including a first part and a second part. Each part of sub-state S2a of cycle 3 of the clock signal occurs over an equal time interval. The first part of sub-state S2a has a metric value within a sub-range of the range of metric values of sub-state S2a, and the second part of sub-state S2b has a metric value within a sub-range of the range of metric values of sub-state S2a. The metric values of the first part are in the range from M8 to M7.9, where the metric value M7.9 is smaller than the metric value M8 and larger than the metric value M7.8. The metric values of the second part are in the range from M7.9 to M7.8. As yet another example, during sub-state S6b of cycle 3 of the clock signal, the metric data of plot 502 has a plurality of slices. By way of illustration, during the time window between time t11.5 and time t12, the metric data of plot 502 is divided into four parts. Each part of sub-state S6b of cycle 3 of the clock signal occurs over an equal time interval.The fourth slice of sub-state S6b of cycle 3 starts at time t11.875 and ends at time t12. Time 11.875 is at position A3.875 within cycle 3.

[0197] Although various embodiments are described herein with reference to the state of metric data of a metric, it should be noted that this embodiment is applicable to sub-states. For example, method 280 is applied to sub-states S2a and S2b. In this example, instead of operation 286 of method 280 (FIG. 2E), the processor 124 of the analysis controller 106 acquires the metric data of plot 502 for a time window such as the time interval between times t4.5 and t4.75 starting at position A0.5. Position A0.5 is at time t4.5 during sub-state S2a, and time t4.75 is at position A0.75. By way of illustration, a portion of the metric data of plot 502 is acquired by the processor 124 from the ADC processor 210 (FIG. 2A). The portion of the metric data of plot 502 represents sub-state S2a of the metric data and is an example of additional digital metric data 224 (FIG. 2B).

[0198] Furthermore, in this example, instead of operation 288 of method 280, the processor 124 controls a variable during sub-state S2a based on the metric data for sub-state S2a of plot 502. For example, the processor 124 determines whether the metric data for sub-state S2a is within a predetermined range from a pre-stored value of the metric. In response to determining that the metric data collected for sub-state S2a is not within the predetermined range from the pre-stored value of the metric, the processor 124 controls a variable of the plasma source 226 (FIG. 2B). The processor of the analysis controller 106 controls the plasma source 226 until the metric data for sub-state S2a acquired from the ADC processor 210 is within the predetermined range from the pre-stored value of the metric. By way of illustration, the variable is controlled to achieve a processing speed for processing the substrate S within the plasma chamber 114 of FIG. 1A or the plasma chamber 152 of FIG. 1B.

[0199] In this example, the variable of the sub-state S2a is that of the RF signal generated by the plasma source 226 (FIG. 2B), and the plasma source 226 corresponds to the RF sensor 201. The RF sensor 201 measures data regarding the RF signal and outputs the metric data of the plot 502, and one or more values of the variable are determined based on the metric data. For example, when the metric data of the plot 502 is generated based on the analog metric data 202 (FIG. 2A) output from the RF sensor an, the variable is that of the RF signal 140an generated by the RF generator an (FIG. 1A) or the matchless plasma source MPSan (FIG. 1B). As another example, when the metric data of the plot 502 is generated based on the analog metric data 202 received from the RF sensor a(n+m), the variable is that of the RF signal 140a(n+m) generated by the RF generator a(n+m) (FIG. 1A) or the matchless plasma source MPSa(n+m) (FIG. 1B).

[0200] As another example, the method described in the previous example is executed by the processor 132 of the process controller 116 instead of the processor 124 of the analysis controller 106. For example, the processor 124 transmits the metric data regarding the time window between t4.5 and t4.75 at the position A0.5 to the processor 132 of the process controller 116 via the communication controllers 130 and 136. When acquiring the metric data regarding the time window between t4.5 and t4.75 at the position A0.5 from the processor 124, the processor 132 of the process controller 116 controls the variable of the plasma source 226.

[0201] In one embodiment, instead of sub-state S2a, another sub-state such as sub-state S2b, S6a, or S6b can be used to execute the method described in the previous embodiments. For example, instead of obtaining the metric data of plot 502 for the time window between times t4.5 and t4.75 starting at position A0.5, the metric data of plot 502 for the time window between times t4.75 and t5.3 starting at position A0.75 is obtained. Also, the metric data of plot 502 for the time window between times t4.75 and t5.3 starting at position A0.75 is an example of additional digital metric data 224 (FIG. 2B). The operation of controlling the variables of sub-state S2b is executed based on the metric data of plot 502 for the time window between times t4.75 and t5.3 at position A0.75.

[0202] In one embodiment, referring to FIG. 4, the method 400 described above is applied to the sub-state of plot 502. For example, instead of operation 402 of method 400, during cycle 1 of the clock signal, the metric data of plot 502 for the time window between times t0.5 and t0.75 starting at position A0.5 is obtained. Time t0.75 occurs before time t1 and after time t0.5. Illustratively, the metric data of plot 502 sampled by ADC processor 104 (FIG. 2C) for the time window between times t0.5 and t0.75 at position A0.5 is received by processor 124 of analysis controller 106 from DPS 102. Note that the time window between times t0.5 and t0.75 corresponds to sub-state S2a of the metric data of plot 502. As another example, the metric data of plot 502 regarding sub-state S2a is obtained during a predetermined number of cycles of the clock signal.

[0203] Continuing with the example, instead of operation 404 of method 400, an operation of controlling a variable is performed during a preset number of cycles of the clock signal following a predetermined number of cycles of the clock signal. The variable is controlled based on metric data acquired during a predetermined number of cycles with respect to sub-state S2a. By way of illustration, during sub-state S2a of cycle 2 of the metric data of plot 502, the processor 124 controls the variable of the plasma source 226 based on the metric data acquired during sub-state S2a of cycle 1. Cycle 2 is an example of a preset number of cycles.

[0204] Continuing further with the example, instead of operation 406 of method 400, an operation is to acquire the metric data of plot 502 regarding a time window between times t4.75 and t5.3 starting at position A0.75 for each of the preset number of cycles of the clock signal. By way of illustration, instead of sampling the metric data of plot 502 regarding a time window between times t4.5 and t4.75 at position A0.5 during cycle 2 of the clock signal, the metric data of plot 502 is sampled by the ADC processor 104 regarding a time interval between times t4.75 and t5.3. The metric data of plot 502 sampled by the ADC processor 104 regarding the time interval between times t4.75 and t5.3 at position A0.75 is transmitted from the ADC processor 104 to the processor 124 of the analysis controller 106. It should be noted that the time window between times t4.5 and t4.75 corresponds to sub-state S2a of the metric data of plot 502, and the time window between times t4.75 and t5.3 corresponds to sub-state S2b of the metric data of plot 502.

[0205] Continuing with the example, instead of operation 408 of method 400, an operation is performed to control a variable of the plasma source 226 based on metric data obtained during a preset number of cycles. By way of example, the variable is controlled during sub-state S2b of cycle 3 of the clock signal. In this example, the variable is controlled during a pre-stored number of cycles of the clock signal following a preset number of cycles of the clock signal.

[0206] In one embodiment, the method described in the previous embodiment is performed by the process controller 116 instead of the processor 124 of the analysis controller 106. For example, the metric data of plot 502 sampled by the ADC processor 104 during cycle 1 of the clock signal is received by the processor 132 of the process controller 116 from the analysis controller 106. In this embodiment, the predetermined number of cycles of the clock signal, the preset number of cycles of the clock signal, and the pre-stored number of cycles of the clock signal are stored in the memory device 134 of the process controller 116.

[0207] Although various embodiments are described herein with reference to the state of the metric data of the metric, it should be further noted that this embodiment is applicable to slices of the metric. For example, method 280 is applied to slices 1, 2, and 3. In this example, instead of operation 286 (FIG. 2E) of method 280, the processor 124 of the analysis controller 106 obtains the metric data of plot 502 regarding a time window such as the time interval between time t8.5 and time t8.625 starting at position A0.5. Time t8.625 is after time t8.5 and before time t8.75. Position A0.5 is at time t8.5 during sub-state S2a, and time t8.625 is at position A0.625. By way of example, the portion of the metric data of plot 502 is obtained by the processor 124 from the ADC processor 210 (FIG. 2A). The portion of the metric data of plot 502 represents slice 1 of sub-state S2a of the metric data and is an example of additional digital metric data 224 (FIG. 2B).

[0208] Further, in this example, instead of operation 288 of method 280, processor 124 controls a variable based on metric data regarding slice 1 of plot 502 Sub during the period of slice 1 of state S2a. For example, processor 124 determines whether the metric data collected during slice 1 of sub-state S2a is within a predetermined range from a pre-stored value of the metric. In response to determining that the metric data collected during slice 1 of sub-state S2a is not within the predetermined range from the pre-stored value of the metric, processor 124 controls a variable of plasma source 226 (FIG. 2B). The processor of analysis controller 106 controls plasma source 226 until the metric data collected during slice 1 of sub-state S2a obtained from ADC processor 210 is within the predetermined range from the pre-stored value of the metric. By way of illustration, the variable is controlled to achieve a processing speed for processing substrate S within plasma chamber 114 of FIG. 1A or plasma chamber 152 of FIG. 1B.

[0209] In this example, the variable controlled during slice 1 of sub-state S2a is that of the RF signal generated by plasma source 226 (FIG. 2B), and plasma source 226 corresponds to an RF sensor. The correspondence with the RF sensor is as described above regarding controlling the variable during sub-state S2a.

[0210] As another example, the method described in the previous example is executed by the processor 132 of the process controller 116 instead of the processor 124 of the analysis controller 106. For example, the processor 124 transmits metric data regarding the time window between times t8.5 and t8.625 at position A0.5 to the processor 132 of the process controller 116 via the communication controllers 130 and 136. Upon obtaining the metric data regarding the time window between times t8.5 and t8.625 at position A0.5 from the processor 124, the processor 132 of the process controller 116 controls the variables of the plasma source 226 based on the metric data.

[0211] In one embodiment, instead of slice 1, another slice such as slice 2 or slice 3 can be used to execute the method described in the previous embodiment. For example, instead of obtaining the metric data of plot 502 regarding the time window between times t8.5 and t8.625 starting at position A0.5, the metric data of plot 502 regarding the time window between times t8.625 and t8.75 starting at position A0.625 is obtained. Also, the metric data of plot 502 regarding the time window between times t8.625 and t8.75 starting at position A0.625 is an example of additional digital metric data 224 (FIG. 2B). The operation of controlling the variables during slice 2 is performed based on the metric data of plot 502 regarding the time window between times t8.625 and t8.75 at position A0.625.

[0212] In one embodiment, the method 400 described above with reference to FIG. 4 is applied to a slice of plot 502. For example, instead of operation 402 of method 400, during cycle 1 of the clock signal, metric data of plot 502 regarding a time window between time t0.5 and time t0.625, starting at position A0.5, is acquired. Time t0.625 occurs before time t0.75 and after time t0.5. By way of illustration, the metric data of plot 502 sampled by ADC processor 104 (FIG. 2C) regarding the time window between time t0.5 and time t0.625 at position A0.5 is received from DPS 102 by processor 124 of analysis controller 106. Note that the time window between time t0.5 and time t0.625 corresponds to slice 1 during sub-state S2a of the metric data of plot 502. As another example, during a predetermined number of cycles of the clock signal, metric data of plot 502 regarding slice 1 during sub-state S2a is acquired.

[0213] Continuing with the example, instead of operation 404 of method 400, an operation of controlling a variable is performed during a preset number of cycles of the clock signal following a predetermined number of cycles of the clock signal. The variable is controlled based on the metric data acquired during a predetermined number of cycles during slice 1 of sub-state S2a. By way of illustration, during slice 1 of sub-state S2a of cycle 2 of the metric data of plot 502, processor 124 controls the variable of plasma source 226 based on the metric data acquired during slice 1 of sub-state S2a of cycle 1. Slice 1 of sub-state S2a of cycle 2 occurs between time t4.5 and time 4.625. Time t4.625 occurs after time t4.5 and before time t4.75. Cycle 2 is an example of a preset number of cycles.

[0214] Continuing with the example, instead of operation 406 of method 400, an operation is performed to collect metric data for plot 502 regarding a slice different from the slice for which metric data is acquired during a predetermined number of cycles. The metric data is collected for different slices during a preset number of cycles. By way of illustration, the metric data is collected during cycle 2 regarding a time window between t4.625 and t4.75 starting at position A0.625. In this illustration, instead of sampling the metric data for plot 502 regarding the time window between t4.5 and t4.625 at position A0.5 during cycle 2 of the clock signal, the metric data for plot 502 is sampled by ADC processor 104 regarding the time interval between t4.625 and t4.75. The metric data for plot 502 sampled by ADC processor 104 regarding the time interval between t4.625 and t4.75 at position A0.625 is transmitted from ADC processor 104 to processor 124 of analysis controller 106. Note that the time window between t4.625 and t4.75 corresponds to slice 2 of sub-state S2a of plot 502's metric data.

[0215] Continuing with the example, instead of operation 408 of method 400, an operation is performed to control a variable of plasma source 226 based on metric data acquired during a preset number of cycles. By way of illustration, the variable is controlled during slice 2 of sub-state S2a of cycle 3 of the clock signal. In this example, the variable is controlled during a preset number of cycles of the clock signal following a preset number of cycles of the clock signal.

[0216] In one embodiment, the method described in the previous embodiment is executed by the process controller 116 instead of the processor 124 of the analysis controller 106. For example, the metric data of the plot 502 sampled by the ADC processor 104 during cycle 1 of the clock signal is received from the analysis controller 106 by the processor 132 of the process controller 116. In this embodiment, the predetermined number of cycles of the clock signal, the preset number of cycles of the clock signal, and the pre-stored number of cycles of the clock signal are stored in the memory device 134 of the process controller 116.

[0217] In one embodiment, the metric value M0 is a positive metric value.

[0218] In one embodiment, the metric value M0 is zero.

[0219] In one embodiment, each slice includes a pre-stored number of sample points that are sampled by the ADC processor 210 (FIG. 2A) during a time interval in the range of 6 microseconds to 7 microseconds. For example, each slice includes 512 samples that are sampled during a time interval of 6.5 microseconds.

[0220] In one embodiment, a state is defined by a position and a time window from the position. For example, state S1 includes position A0 and a time window between times t0 and t1. Also, a sub-state is defined by a position and a time window from the position. As an example, sub-state S2a includes position A0.5 at time t4.5 and a time window from that position. In this example, the time window extends from time t4.5 to time t4.75. Further, a slice is defined by a position and a time window from the position. As an example, slice 1 includes position A0.5 at time t4.5 and a time window from that position. In this example, the time window extends from time t4.5 to time t4.625.

[0221] Some embodiments are described herein with respect to metric values during a time interval related to a state, sub-state, or slice. Note, however, that in one embodiment, instead of a metric value, the metric may have a plurality of metric values related to a state, sub-state, or slice. For example, a metric value related to a state, sub-state, or slice is within a range of a predetermined standard deviation of one of the metric values.

[0222] FIG. 5B is a diagram of one embodiment of a desktop computer 510 for illustrating the selection of a location and a time window. Examples of the location and the time window include a state of a metric, a sub-state of a metric, and a slice of a metric. The desktop computer 510 is an example of the process controller 116 or the analysis controller 106 (FIG. 1A). The desktop computer 510 includes a monitor 512, a keyboard 514, and a mouse 516. The keyboard 514 is wirelessly connected to a computer processor disposed within the housing of the monitor 512. Also, the mouse 516 is wirelessly connected to the computer processor. The computer processor is an example of the processor 124 of the analysis controller 106 or the processor 132 of the process controller 116. The monitor 512 includes a display device such as a liquid crystal display (LCD) device, a light emitting diode (LED) device, or a plasma display device. The display device includes a display screen.

[0223] The graph 282 is displayed on the display screen by an image processing unit (GPU) of the monitor 512. The GPU is connected to the computer processor and controlled by the computer processor. The display screen displays a plot 284. As an example, the plot 284 is constructed by the computer processor by combining sample points or sample values of the digital metric data 204 and is rendered on the display screen by the GPU.

[0224] The GPU further renders on the display screen a field 511 for receiving the positions at which additional analog metric data 222 (FIG. 2B) is to be sampled by the ADC processor. The user uses the keyboard 514 and the mouse 516 to identify, for example, provide the positions at which the additional analog metric data 222 is to be sampled. An example of a position is the time at which the state of the metric begins. For example, the computer processor receives from the user within the field 511 any one of positions A0, A1, A2, and A3 at which the analog metric data 222 is to be collected during each cycle of the clock signal.

[0225] Furthermore, the GPU displays another field 513 for receiving a time window starting at the position received within the field 511. The user uses the keyboard 514 and the mouse 516 to identify, for example, provide a time window within the field 513, such as seconds, or milliseconds, or microseconds.

[0226] Upon receiving the position within the field 511 and the time window within the field 513, the computer processor generates a control signal 206 (FIG. 2A) indicating the position and the time window. Upon receiving the control signal 206 from the desktop computer 510, the ADC processor 210 (FIG. 2A) collects, for example, samples additional analog metric data 222 (FIG. 2B) with respect to the time window during each cycle of the clock signal at the position received within the field 511, and outputs additional digital metric data 224 (FIG. 2B). For example, analog metric data outside the time window is not sampled by the ADC processor 210 between each cycle of the clock signal to output the additional digital metric data 224.

[0227] FIG. 5C is a diagram of one embodiment of monitor 512 to illustrate that different positions or time windows or combinations thereof can be provided for different cycles of a clock signal. Monitor 512 displays graph 282. The GPU displays a field 540 for receiving an identification, such as an identification number, of the cycle of the clock signal for which additional analog metric data 222 (FIG. 2B) is to be sampled by the ADC processor. The user uses keyboard 514 and mouse 516 to identify, e.g., provide, one or more identifications of one or more cycles of the clock signal for which additional analog metric data 222 is to be sampled. For example, the computer processor receives numbers 1 and 3 from the user within field 540 and identifies cycles 1 and 3 of the clock signal for which analog metric data 222 is to be collected.

[0228] The GPU further displays a field 542 for receiving the position at which additional analog metric data 222 (FIG. 2B) is to be sampled by ADC processor 210 during cycle 1 of the clock signal. Cycle 1 is identified within field 540. The user uses keyboard 514 and mouse 516 to identify, e.g., provide, the position at which additional analog metric data 222 is to be sampled during cycle 1 of the clock signal.

[0229] The GPU further displays another field 544 for receiving the position at which additional analog metric data 222 (FIG. 2B) is to be sampled by ADC processor 210 during cycle 3 of the clock signal. Cycle 3 is identified within field 540. The user uses keyboard 514 and mouse 516 to identify, e.g., provide, the position at which additional analog metric data 222 is to be collected during cycle 3 of the clock signal.

[0230] Furthermore, the GPU displays another field 546 for receiving a first time window during which the analog metric data 222 is to be sampled during cycle 1 of the clock signal. The first time window covers the state, or sub-state, or slice of the analog metric data 222. The analog metric data 222 is to be sampled from the position received within field 542. The user uses the keyboard 514 and mouse 516 to identify, e.g., provide, the first time window within field 546.

[0231] Also, the GPU displays another field 550 for receiving a second time window during which the analog metric data 222 is to be sampled during cycle 3 of the clock signal. The user uses the keyboard 514 and mouse 516 to identify, e.g., provide, the second time window within field 550. The second time window covers the state, or sub-state, or slice of the analog metric data 222. The analog metric data 222 is to be sampled from the position received within field 544. The user uses the keyboard 514 and mouse 516 to identify, e.g., provide, the second time window within field 550.

[0232] Upon receiving Cycle 1 and 3 within Field 540, positions within Fields 542 and 544, and the first and second time windows within Fields 546 and 550, the computer processor generates a control signal 206 (Figure 2A) having the cycle, position, and the first and second time windows. Upon receiving the control signal 206 from the desktop computer 510, the ADC processor 210 (Figure 2A) samples additional analog metric data 222 (Figure 2B) starting at the position received within Field 542 during Cycle 1 of the clock signal and regarding the first time window within Field 546, and outputs additional digital metric data 224. For example, metric data outside the first time window received within Field 546 is not sampled by the ADC processor 210 during Cycle 1 of the clock signal to output additional digital metric data 224 (Figure 2B).

[0233] Also, in response to receiving the control signal 206 from the desktop computer 510, the ADC processor 210 (Figure 2A) starts from the position received within Field 544 during Cycle 3 of the clock signal and 50 samples additional analog metric data 222 (Figure 2B) regarding the second time window within Field 5, and outputs additional digital metric data 224. For example, metric data outside the second time window received within Field 550 is not sampled by the ADC processor 210 during Cycle 3 of the clock signal to output additional digital metric data 224 (Figure 2B).

[0234] In one embodiment, instead of cycle 1, multiple cycles such as cycles 1 and 2 of the clock signal are received within field 540. Also, instead of cycle 3, multiple cycles such as cycles 3, 4, and 5 of the clock signal are received within field 540. Further, for each of cycles 1, 2, 3, 4, and 5, a field is provided for receiving the position within the cycle at which digital metric data, such as digital metric data 224 (FIG. 2B), is to be output by ADC processor 210. Also, for each of cycles 1 to 5, a field is provided for receiving the time window within which digital metric data is to be output.

[0235] FIG. 6A is a diagram of one embodiment of system 600 for illustrating the use of a single digital pulse signal for sampling analog metric data received from RF sensors a1 to a(n + m) (FIGS. 1A and 1B). An example of a single digital pulse signal is a transistor-transistor logic (TTL) signal. By way of illustration, a single digital pulse signal is a TTL1 signal. In this illustration, the TTL1 signal periodically transitions between logic level 1 and logic level 0.

[0236] System 600 includes plasma sources from plasma source (PS) a1, plasma source a2, up to plasma source an. System 600 further includes plasma sources from plasma source PSa(n + 1), plasma source PSa(n + 2), up to plasma source PSa(n + m). Examples of plasma sources used herein include RF generators or matchless plasma sources. By way of illustration, examples of plasma source an include RF generator RFGan and matchless plasma source MPSan, and examples of plasma source PSa(n + m) include RF generator RFGa(n + m) and matchless plasma source MPSa(n + m).

[0237] System 600 further includes RF sensors a1 to a(n+m), a DPS 102, an analysis controller 106, and a process controller 116. As an example, system 600 includes the components of system 100 in FIG. 1A. As another example, system 600 includes the components of system 150 in FIG. 1B.

[0238] Plasma source PSa1 is an example of a master plasma source and generates a TTL1 signal. Plasma source PSa1 supplies the TTL1 signal to processor 124 of analysis controller 106. Processor 124 receives the TTL1 signal from plasma source a1 and transmits the TTL1 signal to ADC processor 210 of DPS 102. ADC processor 210 receives analog metric data such as analog metric data 222 (FIG. 2B) from RF sensors a1 to a(n+m), samples the analog metric data in synchronization with the TTL1 signal, and outputs digital metric data. For example, the analog metric data is sampled between each rising edge or each falling edge of the TTL1 signal or a combination thereof. The analog metric data is sampled with respect to a time window at the position of the metric data of the metric. The time window corresponds to the state of the metric, or a sub-state of the metric, or a slice of the metric.

[0239] In one embodiment, processor 124 generates a clock signal and transmits the clock signal to ADC processor 210. The metric data of the metric received from RF sensors a1 to an is sampled in synchronization with the clock signal. For example, the TTL1 signal is synchronized with the clock signal. By way of illustration, a pre-created number of cycles of the TTL1 signal occur during each cycle of the clock signal.

[0240] Also, in this embodiment, the clock signal is supplied by the analysis controller 106 to all components of the plasma system 600. Examples of the components of the plasma system 600 include plasma sources PSa1 to PSa(n+m), and the DPS 102. When a match system is used in the plasma system 600, the components of the plasma system 600 include the match system.

[0241] In one embodiment, the processor 124 of the analysis controller 106 generates a TTL1 signal according to the recipe information received from the user via the mouse 516 and the keyboard 514 (FIG. 5B). The processor 124 of the analysis controller 106 transmits the TTL1 signal to the ADC processor 210, and the ADC processor 210 samples the analog metric data in synchronization with the rising edge and the falling edge of the TTL1 signal.

[0242] In one embodiment, the processor 124 of the analysis controller 106 generates a TTL1 signal according to the recipe information received from the process controller 116. The processor 132 of the process controller 116 receives the recipe information from the user via the mouse 516 and the keyboard 514 (FIG. 5B). The processor 124 of the analysis controller 106 transmits the TTL1 signal to the ADC processor 210.

[0243] In one embodiment, the processor 132 of the process controller 116 generates a TTL1 signal according to the recipe information received from the user via the mouse 516 and the keyboard 514 (FIG. 5B). The processor 132 transmits the TTL1 signal to the processor 124 of the analysis controller 106. The processor 124 transmits the TTL1 signal to the ADC processor 210.

[0244] In one embodiment, any plasma source other than the plasma source PSa1 of the system 600 is a master plasma source that generates a TTL1 signal.

[0245] FIG. 6B is a diagram of one embodiment of system 650 for illustrating a different route than that illustrated in FIG. 6A for the reception of the TTL1 signal by the ADC processor 210. The system 650 includes plasma sources PSa1 to PSa(n+m), RF sensors a1 to a(n+m), the DPS 102, the analysis controller 106, and the process controller 116. As an example, the system 650 includes the components of the system 100 of FIG. 1A. As another example, the system 650 includes the components of the system 150 of FIG. 1B.

[0246] The plasma source PSa1 generates a TTL1 signal and transmits the TTL1 signal to the processor 124 of the analysis controller 106. The processor 124 transmits the TTL1 signal to the plasma source PSa2, and the plasma source PSa2 relays the TTL1 signal to the plasma source PSa3, and so on until the TTL1 signal is transmitted from the plasma source PSa(n+m-1) to the plasma source PSa(n+m). The plasma source PSa(n+m) transmits the TTL1 signal to the ADC processor 210. The ADC processor 210 samples the metric data of the metrics received from the RF sensors a1 to a(n+m) in synchronization with the TTL1 signal.

[0247] In one embodiment, instead of the plasma source PSa1, the processor 132 of the process controller 116 generates a TTL1 signal according to the recipe information received from the user via the mouse 516 and the keyboard 514 (FIG. 5B). The processor 132 transmits the TTL1 signal to the processor 124 of the analysis controller 106. The processor 124 transmits the TTL1 signal to the plasma source PSa1, and the plasma source PSa1 relays the TTL1 signal to the plasma source PSa2, and so on until the TTL1 signal is relayed to the plasma source PSa(n+m). The plasma source PSa(n+m) transmits the TTL1 signal to the ADC processor 210.

[0248] In one embodiment, the plasma source PSa1 generates a TTL1 signal, relays the TTL1 signal to the plasma source a2, and continues in the same manner until the TTL1 signal is replayed to the plasma source PSa(n+m). The TTL1 signal is not transmitted from the plasma source PSa1 to the processor 124.

[0249] In one embodiment, the clock signal is generated by the processor 124 and supplied by the analysis controller 106 to all components of the plasma system 650. Examples of components of the plasma system 650 include the plasma sources PSa1 to PSa(n+m) and the DPS 102. When a matching system is used in the plasma system 650, the components of the plasma system 650 include the matching system.

[0250] FIG. 7A is one embodiment of a graph 700 for illustrating a plot 702. The plot 702 is an example of a TTL1 signal (FIGS. 6A and 6B). The graph 700 includes the logic level of the plot 702 on the y-axis and time t on the x-axis. The plot 702 periodically transitions between a logic level 1 and a logic level 0. For example, the plot 702 transitions from a logic level 0 to a logic level 1 at time t0, remains at the logic level 1 between times t0 and t1.5, transitions from the logic level 1 to the logic level 0 at time t1.5, remains at the logic level 0 between times t1.5 and t4, transitions from the logic level 0 to the logic level 1 at time t4, remains at the logic level 1 between times t4 and t5.5, transitions from the logic level 1 to the logic level 0 at time t5.5, remains at the logic level 0 between times t5.5 and t8, and transitions from the logic level 0 to the logic level 1 at time t8.

[0251] FIG. 7B is an embodiment of a graph 704 for illustrating a plot 706 of metric data, such as analog metric data, of a metric output from an RF sensor a1 (FIGS. 6A and 6B). The graph 704 includes the metric level of the metric of the plot 706 on the y-axis and time t on the x-axis. The plot 706 periodically transitions between a metric level M4 and a metric level M0. For example, the plot 706 transitions from the metric level M0 to the metric level M4 at time t0, stays at the metric level M4 between time t0 and t1.5, transitions from the metric level M4 to the metric level M0 at time t1.5, stays at the metric level M0 between time t1.5 and t4, transitions from the metric level M0 to the metric level M4 at time t4, stays at the metric level M4 between time t4 and t5.5, transitions from the metric level M4 to the metric level M0 at time t5.5, stays at the metric level M0 between time t5.5 and t8, and transitions from the metric level M0 to the metric level M4 at time t8. The metric level M4 defines a state S1 of the metric measured by the RF sensor a1, and the metric level M0 defines a state S2 of the metric measured by the RF sensor a1.

[0252] Note that the metric level of a metric includes one or more metric values of the metric. For example, the metric level M4 has a metric value M4. As another example, the metric level M4 has a metric value M4 and additional values within a predetermined standard deviation of the metric value M4.

[0253] It should be further noted that the first metric level has metric values excluding the metric values of the second metric level. For example, the minimum value of the metric values of the first metric level is greater than the maximum value of the metric values of the second metric level. In this example, the first metric level is greater than the second metric level.

[0254] The metric data of plot 706 is sampled by the ADC processor 210 (FIGS. 6A and 6B) in synchronization with plot 702 (FIG. 7A), which is an example of the TTL1 signal. For example, plot 706 is periodically sampled at the rising edge of plot 702. Illustratively, the metric data of plot 706 is converted from analog form to digital form at time t0 during cycle 1 of the clock signal and at time t4 during cycle 2 of the clock signal. As another example, plot 706 is periodically sampled at the falling edge of plot 702. Illustratively, the metric data of plot 706 is converted from analog form to digital form at time t1.5 during cycle 1 of the clock signal and at time t5.5 during cycle 2 of the clock signal. As another example, plot 706 is periodically sampled at the falling edge of plot 702 and periodically sampled at the rising edge of plot 702.

[0255] In one embodiment, plot 706 is generated from the metric data of a metric measured by any one of RF sensors a2, a3, and a4 to a(n + m) instead of RF sensor a1.

[0256] FIG. 7C is an embodiment of a graph 708 for illustrating a plot 710 of metric data of a metric measured by an RF sensor a2 (FIGS. 6A and 6B). The graph 708 includes the metric level of the plot 710 on the y-axis and time t on the x-axis. The plot 710 periodically transitions between metric level M5, metric level M4, and metric level M1. For example, the plot 710 transitions from metric level M0 to metric level M5 at time t0, remains at metric M5 from time t0 to time t1, transitions from metric level M5 to metric level M4 at time t1, remains at metric level M4 from time t1 to time t2.5, transitions from metric level M4 to metric level M1 at time t2.5, remains at metric level M1 from time t2.5 to time t4, transitions from metric level M4 to metric level M5 at time t4, remains at metric level M5 from time t4 to time t5, transitions from metric level M5 to metric level M4 at time t5, remains at metric level M4 from time t5 to time t6.5, transitions from metric level M4 to metric level M1 at time t6.5, remains at metric level M1 from time t6.5 to time t8, and transitions from metric level M1 to metric level M5 at time t8. Metric level M5 defines state S1 of the metric measured by RF sensor a2, metric level M4 defines state S2 of the metric measured by RF sensor a2, and metric level M1 defines state S3 of the metric measured by RF sensor a2.

[0257] Metric data, such as analog metric data represented by plot 710, is sampled by an ADC processor 210 (Figs. 6A and 6B) in synchronization with plot 702 (Fig. 7A), which is an example of a TTL1 signal. For example, plot 710 is periodically sampled at the rising edge of plot 702. Illustratively, the metric data of plot 710 is converted from analog format to digital format at time t0 during cycle 1 of the clock signal and at time t4 during cycle 2 of the clock signal. As another example, plot 710 is periodically sampled at the falling edge of plot 702. Illustratively, the metric data of plot 710 is converted from analog format to digital format at time t1.5 during cycle 1 of the clock signal and at time t5.5 during cycle 2 of the clock signal. As another example, plot 710 is periodically sampled at the falling edge of plot 702 and periodically sampled at the rising edge of plot 702.

[0258] In one embodiment, plot 710 is generated from metric data of a metric measured by any one of RF sensors a1, a3, and a4 to a(n + m) instead of RF sensor a2.

[0259] FIG. 7D is an embodiment of a graph 712 for illustrating a plot 714 of metric data measured by an RF sensor an (FIGS. 6A and 6B). The graph 712 includes a metric level of the metric of the plot 714 on the y-axis and time t on the x-axis. The plot 714 periodically transitions among metric level M7, metric level M6, metric level M5, metric level M4, and metric level M1 during each cycle of the clock signal. For example, during cycle 1 of the clock signal, the plot 714 transitions from metric level M1 to metric level M7 at time t0, stays at metric level M7 from time t0 to time t0.5, transitions from metric level M7 to metric level M6 at time t0.5, stays at metric level M6 from time t0.5 to time t1, transitions from metric level M6 to metric level M5 at time t1, stays at metric level M5 from time t1 to time t2, transitions from metric level M5 to metric level M4 at time t2, stays at metric level M4 from time t2 to time t2.5, and transitions from metric level M4 to metric level M1 at time t2.5. Also, in this example, during cycle 1 of the clock signal, the plot 714 stays at metric level M1 from time t2.5 to time t4. In this example, during cycle 2 of the clock signal, the plot 714 transitions from metric level M1 to metric level M7 at time t4. In this example, the transition from metric level M7 to M1 is repeated during cycle 2 of the clock signal. Metric level M7 defines state S1 of the metric measured by RF sensor a3, metric level M6 defines state S2 of the metric measured by RF sensor a3, and metric level M5 defines state S3 of the metric measured by RF sensor a3. Also, metric level M4 defines state S4 of the metric measured by RF sensor a3, and metric level M1 defines state S5 of the metric measured by RF sensor a3.

[0260] The metric data of plot 714 is sampled by an ADC processor 210 (Figs. 6A and 6B) in synchronization with plot 702 (Fig. 7A), which is an example of a TTL1 signal. For example, plot 714 is periodically sampled at the rising edge of plot 702. Illustratively, the metric data of plot 714 is converted from an analog format to a digital format at time t0 during cycle 1 of the clock signal and at time t4 during cycle 2 of the clock signal. As another example, plot 714 is periodically sampled at the falling edge of plot 702. Illustratively, the metric data of plot 714 is converted from an analog format to a digital format at time t1.5 during cycle 1 of the clock signal and at time t5.5 during cycle 2 of the clock signal. As another example, plot 714 is periodically sampled at the falling edge of plot 702 and at the rising edge of plot 702. In the method illustrated with reference to Figs. 7A-7D, the metric data of the metrics received from RF sensors a1~an is sampled in synchronization with a single TTL1 signal.

[0261] In one embodiment, plot 714 is generated from the metric data of the metrics measured by any of RF sensors a1, a2~a(n - 1), and a(n + 1)~a(n + m) instead of RF sensor an.

[0262] FIG. 8 is a diagram of one embodiment of a system 800 for illustrating the use of a plurality of digital pulse signals, such as TTL signals, for sampling metric data of metrics received from RF sensors a1 to a(n+m). For example, the processor 124 of the analysis controller 106 generates a plurality of digital pulse signals to sample the analog metric data received from the RF sensors a1 to a(n+m). By way of illustration, the first of the digital pulse signals is used to sample the analog metric data received from the RF sensor a1 at each state of the metric data. In this illustration, the second of the digital pulse signals is used to sample the analog metric data received from the RF sensor a2 at each sub-state of the metric data. Also, in this illustration, the third of the digital pulse signals is used to sample the analog metric data received from the RF sensor a3 at each slice of the metric data.

[0263] The system 800 includes plasma sources PSa1 to PSa(n+m), RF sensors a1 to a(n+m), a DPS 102, an analysis controller 106, and a process controller 116. As an example, the system 800 has the same structure as the system 100 of FIG. 1A. As another example, the system 800 has the same structure as the system 150 of FIG. 1B.

[0264] The processor 124 of the analysis controller 106 generates TTL signals such as the TTL1 signal, the TTL2 signal, and the TTL3 signal. The processor 124 supplies the TTL signals to the ADC processor 210. The ADC processor 210 receives analog metric data from the RF sensors a1 to a3. The ADC processor 210 samples the analog metric data of the metric received from the RF sensor a1 synchronously with the TTL1 signal and outputs digital metric data. Also, the ADC processor 210 samples the metric data of the metric received from the RF sensor a2 synchronously with the TTL2 signal and outputs digital metric data, and the ADC processor 210 samples the metric data of the metric received from the RF sensor a3 synchronously with the TTL3 signal and outputs digital metric data.

[0265] Also, the processor 124 generates a clock signal and transmits the clock signal to the ADC processor 210. The analog metric data received from the RF sensors a1 to an is sampled synchronously with the clock signal. For example, each of the TTL1, TTL2, and TTL3 signals is synchronized with the clock signal. By way of illustration, the first pre-created number of cycles of the TTL1 signal occurs during each cycle of the clock signal, the second pre-created number of cycles of the TTL1 signal occurs during each cycle of the clock signal, and the third pre-created number of cycles of the TTL3 signal occurs during each cycle of the clock signal.

[0266] Also, the clock signal is generated by the processor 124 of the analysis controller 106 and supplied to all components of the plasma system 800. Examples of the components of the plasma system 800 include the plasma sources PSa1 to PSa(n + m), and the DPS 102. When a match system is used in the plasma system 800, the components of the plasma system 800 include the match system.

[0267] In one embodiment, the processor 124 of the analysis controller 106 generates each of the TTL1, TTL2, and TTL3 signals according to recipe information received from the user via the mouse 516 and the keyboard 514 (FIG. 5B). The processor of the analysis controller 106 transmits the TTL1, TTL2, and TTL3 signals to the ADC processor 210.

[0268] In one embodiment, the processor 132 of the process controller 116 (FIG. 1A) generates each of the TTL1, TTL2, and TTL3 signals according to recipe information received from the user via the mouse 516 and the keyboard 514 (FIG. 5B). The processor 132 transmits the TTL1, TTL2, and TTL3 signals to the processor 124 of the analysis controller 106, and the processor 124 of the analysis controller 106 transmits the TTL1, TTL2, and TTL3 signals to the ADC processor 210.

[0269] FIG. 9A is a graph 900 for illustrating a plot 902 of a clock signal. The graph 900 plots the logic levels of the plot 902 on the y-axis and time t on the x-axis. The clock signal illustrated by the plot 902 periodically transitions between a logic level 1 and a logic level 0. For example, cycle 1 of the plot 902 occurs between time t0 and time t4, and cycle 2 of the plot 902 occurs between time t4 and time t8. By way of illustration, during cycle 1, the plot 902 transitions from a logic level 0 to a logic level 1 at time t0 and remains at the logic level 1 from time t0 to time t2. In this illustration, during cycle 1 of the clock signal, the plot 902 transitions from a logic level 1 to a logic level 0 at time t2 and remains at the logic level 0 from time t2 to time t4. Continuing the illustration, during cycle 2 of the clock signal, the plot 902 transitions from a logic level 0 to a logic level 1 at time t4 and remains at the logic level 1 from time t4 to time t6. Also, during cycle 2 of the clock signal, the plot 902 transitions from a logic level 1 to a logic level 0 at time t6 and remains at the logic level 0 from time t6 to time t8. During cycle 3 of the clock signal, the plot 902 transitions from a logic level 0 to a logic level 1 at time t8.

[0270] In one embodiment, the transition from a logic level 0 to a logic level 1 during the current cycle of the clock signal is a portion of the preceding cycle of the clock cycle. For example, the transition of the plot 902 from a logic level 0 to a logic level 1 at time t0 is a portion of cycle 0 that precedes cycle 1 of the clock signal. Cycle 0 is of the clock signal. As another example, the transition of the plot 902 from a logic level 0 to a logic level 1 at time t4 is a portion of cycle 1 that precedes cycle 2 of the clock signal.

[0271] FIG. 9B is one embodiment of a graph 700 for illustrating a plot 702 of the TTL1 signal of FIG. 8.

[0272] FIG. 9C is an embodiment of a graph 704 for illustrating a plot 706 of metric data output from an RF sensor a1 (FIG. 8).

[0273] FIG. 9D is an embodiment of a graph 904 for illustrating a plot 906. The plot 906 is an example of a TTL2 signal (FIG. 8). The graph 904 includes the logic level of the plot 906 on the y-axis and time t on the x-axis. The plot 906 periodically transitions between a logic level 1 and a logic level 0. For example, the plot 906 transitions from the logic level 0 to the logic level 1 at time t0 and remains at the logic level 1 from time t0 to time t1. The plot 906 transitions from the logic level 1 to the logic level 0 at time t1 and remains at the logic level 0 from time t1 to time t1.5. The plot 906 transitions from the logic level 0 to the logic level 1 at time t1.5 and remains at the logic level 1 from time t1.5 to time t2.5. The plot 906 transitions from the logic level 1 to the logic level 0 at time t2.5 and remains at the logic level 0 from time t2.5 to time t4. Also, the plot 906 transitions from the logic level 0 to the logic level 1 at time t4 and remains at the logic level 1 from time t4 to time t5. Further, the plot 906 transitions from the logic level 1 to the logic level 0 at time t5 and remains at the logic level 0 from time t5 to time t5.5. The plot 906 transitions from the logic level 0 to the logic level 1 at time t5.5 and remains at the logic level 1 from time t5.5 to time t7. The plot 906 transitions from the logic level 1 to the logic level 0 at time t7 and remains at the logic level 0 from time t7 to time t8. The plot 906 transitions from the logic level 0 to the logic level 1 at time t8. It should be noted that the frequency of the transitions between the logic levels 1 and 0 of the plot 906 is greater than the frequency of the transitions between the logic levels 1 and 0 of the plot 702 (FIG. 9B).

[0274] FIG. 9E is an embodiment of a graph 908 for illustrating a plot 910 of metric data such as analog metric data of a metric output from an RF sensor a2 (FIG. 8). The graph 908 includes the metric level of the metric of the plot 910 on the y-axis and includes time t on the x-axis. The plot 910 periodically transitions between a metric level M4, a metric level M3.7, a metric level M2, and a metric level M2.3. For example, the plot 901 transitions from the metric level M2.3 to the metric level M4 at time t0 and stays at the metric level M4 from time t0 to time t1. Further, the plot 901 transitions from the metric level M4 to the metric level M3.7 at time t1 and stays at the metric level M3.7 from time t1 to time t1.5. The plot 901 transitions from the metric level M3.7 to the metric level M2 at time t1.5 and stays at the metric level M2 from time t1.5 to time t3. Also, the plot 901 transitions from the metric level M2 to the metric level M2.3 at time t3 and stays at the metric level M2.3 from time t3 to time t4. The plot 901 repeats the transitions between the metric levels M4, M3.7, M2, and M2.3 during cycle 2 of the clock signal.

[0275] The metric level M4 defines a sub-state S1a of the metric measured by the RF sensor a2, the metric level M3.7 defines a sub-state S1b of the metric measured by the RF sensor a2, the metric level M2 defines a sub-state S2a of the metric measured by the RF sensor a2, and the metric level M2.3 defines a sub-state S2b of the metric measured by the RF sensor a2. The metric level M 3.7 is smaller than the metric level M4 but larger than the metric level M3. Also, the metric level M2.3 is larger than the metric level M2 but smaller than the metric level M3.

[0276] Note that the sub - states S1a and S1b of plot 910 belong to the state S1 of plot 910. Similarly, the sub - states S2a and S2b of plot 910 belong to the state S2 of plot 910.

[0277] The metric data of plot 910 is sampled by the ADC processor 210 (FIG. 9D ) in synchronization with plot 906. For example, plot 910 is sampled periodically at the rising edge and falling edge of plot 910. By way of illustration, the analog metric data illustrated in plot 910 is converted from analog form to digital form at time t0 during cycle 1 of the clock signal, sampling the sub - state S1a of plot 910. In this illustration, the analog metric data illustrated in plot 910 is converted from analog form to digital form at time t1 during cycle 1 of the clock signal, sampling the sub - state S1b of plot 910. Continuing the illustration, the analog metric data illustrated in plot 910 is converted from analog form to digital form at time t1.5 during cycle 1 of the clock signal, sampling the sub - state S2a of plot 910. The analog metric data illustrated in plot 910 is converted from analog form to digital form at time t3 during cycle 1 of the clock signal, sampling the sub - state S2b of plot 910. Similarly, the analog data illustrated in plot 910 is sampled during cycle 2 of the clock signal to sample the sub - states S1a, S1b, S2a, and S2b of plot 910.

[0278] In one embodiment, plot 910 is generated from analog metric data output from any one of RF sensors a1, a3, a4~a(n + m) instead of RF sensor a2.

[0279] In one embodiment, plot 906 is used to sample plot 706 of the analog metric data output from RF sensor a1 instead of, or in addition to, sampling plot 910 of the analog metric data output from RF sensor a2.

[0280] In one embodiment, both plots 702 and 906 are used to sample plot 706 of the analog metric data output from RF sensor a2.

[0281] FIG. 9F is an embodiment of a graph 912 for illustrating a plot 914. The plot 914 is an example of a TTL3 signal (FIG. 8). The graph 912 includes the logic levels of the plot 914 on the y-axis and time t on the x-axis. The plot 914 periodically transitions between logic level 1 and logic level 0 during each cycle of the clock signal. For example, the plot 914 transitions from logic level 0 to logic level 1 at time t0, remains at logic level 1 from time t0 to time t0.25, where time t0.25 is between time t0 and t0.5. The plot 914 transitions from logic level 1 to logic level 0 at time t0.25 and remains at logic level 0 from time t0.25 to time t0.5. The plot 914 transitions from logic level 0 to logic level 1 at time t0.5 and remains at logic level 1 from time t0.5 to time t0.75. The plot 914 further transitions from logic level 1 to logic level 0 at time t0.75 and remains at logic level 0 from time t0.75 to time t1. The plot 914 transitions from logic level 0 to logic level 1 at time t1, remains at logic level 1 from time t1 to time t1.25, where time t1.25 is between time t1 and time t1.5. The plot 914 further transitions from logic level 1 to logic level 0 at time t1.25 and remains at logic level 0 from time t1.25 to time t1.5. The plot 914 transitions from logic level 0 to logic level 1 at time t1.5 and remains at logic level 1 from time t1.5 to time t1.75, where time t1.75 is between time t1.5 and t2. The plot 914 further transitions from logic level 1 to logic level 0 at time t1.75 and remains at logic level 0 from time t1.75 to time t2.

[0282] In this example, plot 914 transitions from a logic level of 0 to a logic level of 1 at time t2, remains at the logic level of 1 from time t2 to time t2.25, where time t2.25 is between time t2 and time t2.5. Time t2.25 is at 1 / 4 of the time interval between time t2 and t3. Plot 914 transitions from the logic level of 1 to the logic level of 0 at time t2.25 and remains at the logic level of 0 from time t2.25 to time t2.5. Plot 914 transitions from the logic level of 0 to the logic level of 1 at time t2.5 and remains at the logic level of 1 from time t2.5 to time t2.75. Plot 914 further transitions from the logic level of 1 to the logic level of 0 at time t2.75 and remains at the logic level of 0 from time t2.75 to time t3. Plot 914 transitions from the logic level of 0 to the logic level of 1 at time t3 and remains at the logic level of 1 from time t3 to time t3.25, where time t3.25 is between time t3 and t3.5. Plot 914 further transitions from the logic level of 1 to the logic level of 0 at time t3.25 and remains at the logic level of 0 from time t3.25 to time t3.5. Plot 914 transitions from the logic level of 0 to the logic level of 1 at time t3.5 and remains at the logic level of 1 from time t3.5 to time t3.75, where time t3.75 is between time t3.5 and t4. Plot 914 further transitions from the logic level of 1 to the logic level of 0 at time t3.75 and remains at the logic level of 0 from time t3.75 to time t4. Thus, plot 914 transitions between the logic levels of 1 and 0 during cycle 2 of the clock signal. It should be noted that the frequency of the transitions between the logic levels of 1 and 0 of plot 914 is greater than the frequency of the transitions between the logic levels of 1 and 0 of plot 906 (FIG. 9D).

[0283] FIG. 9G is an embodiment of a graph 916 for illustrating a plot 918 of metric data, such as analog metric data, of a metric output from an RF sensor an (FIG. 8). The graph 916 includes the metric level of the metric data of the plot 918 on the y-axis and time t on the x-axis. The plot 918 periodically transitions among metric levels M7, M6.9, M6.8, M6.7, M5, M4.9, M4.8, M4.7, M4.6, M4.5, M1, M0.9, M2, M2.1, M2.2, and M2.3. Each metric level M7, M6.9, M6.8, M6.7, M5, M4.9, M4.8, M4.7, M4.6, M4.5, M1, M0.9, M2, M2.1, M2.2, and M2.3 defines a slice of the plot 918. Each slice of the plot 918 occurs over a time interval of t0.5 units.

[0284] Note that the metric level M0.9 is less than the metric level M1 and greater than the metric level M0.5. The metric level 2.1 is greater than the metric level M2 and less than the metric level M2.2. The metric level 2.3 is greater than the metric level M2.2 and less than the metric level M3. Also, the metric level M4.9 is less than the metric level M4.8 and greater than the metric level M4.7. The metric level M4.6 is less than the metric level M4.7 and greater than the metric level M4.5. The metric level M6.9 is less than the metric level M7 and greater than the metric level M6.8. The metric level M6.7 is less than the metric level M6.8 and greater than the metric level M6.

[0285] Metric level M7 defines the first slice of sub-state S1a of the metric measured by RF sensor an, and metric level M6.9 defines the second slice of sub-state S1a. Metric level M6.8 defines the first slice of sub-state S1b, and metric level M6.7 defines the second slice of sub-state S1b. Sub-states S1a and S1b of plot 918 are part of state S1 of plot 918.

[0286] Similarly, metric level M5 defines the first slice of sub-state S2a of the metric measured by RF sensor an, metric level M4.9 defines the second slice of sub-state S2a, and metric level M4.8 defines the third slice of sub-state S2a. Metric level M4.7 defines the first slice of sub-state S2b, metric level M4.6 defines the second slice of sub-state S2b, and metric level M4.5 defines the third slice of sub-state S2b. Sub-states S2a and S2b of plot 918 are part of state S2 of plot 918.

[0287] Also, metric level M1 defines the first slice of state S3 of the metric measured by RF sensor an. Metric level M0.9 defines the second slice of state S3.

[0288] Similarly, metric level M2 defines the first slice of sub-state S4a of the metric measured by RF sensor an, and metric level M2.1 defines the second slice of sub-state S4a. Metric level M2.2 defines the first slice of sub-state S4b, and metric level M2.3 defines the second slice of sub-state S4b. Sub-states S4a and S4b of plot 918 are part of state S4 of plot 918.

[0289] During cycle 1 of the clock signal, plot 918 transitions from metric level M2.3 to metric level M7 at time t0 and remains at metric level M7 from time t0 to time t0.25. Further, during cycle 1 of the clock signal, plot 918 transitions from metric level M7 to metric level M6.9 at time t0.25 and remains at metric level M6.9 from time t0.25 to time t0.5. Also, during cycle 1 of the clock signal, plot 918 transitions from metric level M6.9 to metric level M6.8 at time t0.5 and remains at metric level M6.8 from time t0.5 to time t0.75. Further, during cycle 1 of the clock signal, plot 918 transitions from metric level M6.8 to metric level M6.7 at time t0.75 and remains at metric level M6.7 from time t0.75 to time t1.

[0290] Further, during cycle 1 of the clock signal, plot 918 transitions from metric level M6.7 to metric level M5 at time t1 and remains at metric level M5 from time t1 to time t1.25. Further, during cycle 1 of the clock signal, plot 918 transitions from metric level M5 to metric level M4.9 at time t1.25 and remains at metric level M4.9 from time t1.25 to time t1.5. During cycle 1 of the clock signal, plot 918 transitions from metric level M4.9 to metric level M4.8 at time t1.5 and remains at metric level M4.8 from time t1.5 to time t1.75. Also, during cycle 1 of the clock signal, plot 918 transitions from metric level M4.8 to metric level M4.7 at time t1.75 and remains at metric level M4.7 from time t1.75 to time t2.

[0291] During cycle 1 of the clock signal, plot 918 transitions from metric level M4.7 to metric level M4.6 at time t2 and remains at metric level M4.6 from time t2 to time t2.25. Also during cycle 1 of the clock signal, plot 918 transitions from metric level M4.6 to metric level M4.5 at time t2.25 and remains at metric level M4.5 from time t2.25 to time t2.5.

[0292] Furthermore, during cycle 1 of the clock signal, plot 918 transitions from metric level M4.5 to metric level M1 at time t2.5 and remains at metric level M1 from time t2.5 to time t2.75. During cycle 1 of the clock signal, plot 918 transitions from metric level M1 to metric level M0.9 at time t2.75 and remains at metric level M0.9 from time t2.75 to time t3.

[0293] During cycle 1 of the clock signal, plot 918 transitions from metric level M0.9 to metric level M2 at time t3 and remains at metric level M2 from time t3 to time t3.25. Furthermore, during cycle 1 of the clock signal, plot 918 transitions from metric level M2 to metric level M2.1 at time t3.25 and remains at metric level M2.1 from time t3.25 to time t3.5.

[0294] Also, during cycle 1 of the clock signal, plot 918 transitions from metric level M2.1 to metric level M2.2 at time t3.5 and remains at metric level M2.2 from time t3.5 to time t3.75. Further, during cycle 1 of the clock signal, plot 918 transitions from metric level M2.2 to metric level M2.3 at time t3.75 and remains at metric level M2.3 from time t3.75 to time t4. During cycle 2 of the clock signal, plot 918 transitions from metric level M2.3 to metric level M7 at time t4. Metric levels M7, M6.9, M6.8, M6.7, M5, M4.9, M4.8, M4.7, M4.6, M4.5, M1, M0.9, M2, M2.1, M2.2, and M2.3 are repeated during cycle 2 of the clock signal.

[0295] The metric data of plot 918 is sampled by the ADC processor 210 (FIG 9F ) in synchronization with plot 914. For example, plot 918 is sampled periodically at each rising edge and each falling edge of plot 914. Illustratively, the analog metric data represented by plot 918 is converted from analog form to digital form at time t0 during cycle 1 of the clock signal to sample metric level M7, at time t0.25 during cycle 1 of the clock signal to sample metric level M6.9, at time t0.5 during cycle 1 of the clock signal to sample metric level M6.8, and at time t0.75 during cycle 1 of the clock signal to sample metric level M6.7.

[0296] Also, in this example, the analog metric data represented by plot 918 is converted from analog format to digital format at time t1 during cycle 1 of the clock signal to sample metric level M5, at time t1.25 during cycle 1 of the clock signal to sample metric level M4.9, at time t1.5 during cycle 1 of the clock signal to sample metric level M4.8, at time t1.75 during cycle 1 of the clock signal to sample metric level M4.7, at time t2 during cycle 1 of the clock signal to sample metric level M4.6, and at time t2.25 during cycle 1 of the clock signal to sample metric level M4.5.

[0297] Furthermore, in this example 、Pro the analog metric data represented by lot 918 is converted from analog format to digital format at time t2.5 during cycle 1 of the clock signal to sample metric level M1 and at time t2.75 during cycle 1 of the clock signal to sample metric level M0.9. In this example, the analog metric data of plot 918 is converted from analog format to digital format at time t3 during cycle 1 of the clock signal to sample metric level M2, at time t3.25 during cycle 1 of the clock signal to sample metric level M2.1, at time t3.5 during cycle 1 of the clock signal to sample metric level M2.2, and at time t3.75 during cycle 1 of the clock signal to sample metric level M2.3.

[0298] Note that plots 702, 906, and 914 provide the rate at which the analog metric data is sampled. For example, plot 914 has a rate greater than that of plot 906, and plot 906 has a rate greater than that of plot 702. By way of illustration, if the metric data of plot 706 is sampled in synchronization with the rising and falling edges of plot 914, it is sampled at a first frequency. In this illustration, if the metric data of plot 706 is sampled in synchronization with the rising and falling edges of plot 906, it is sampled at a second frequency. Also, in this illustration, if the metric data of plot 706 is sampled in synchronization with the rising and falling edges of plot 702, it is sampled at a third frequency. The first frequency is greater than the second frequency, and the second frequency is greater than the third frequency.

[0299] In one embodiment, plot 918 is generated from analog metric data measured by any one of RF sensors a1, a2~a(n - 1), and a(n + 1)~a(n + m) instead of RF sensor an.

[0300] In one embodiment, plot 918 transitions from metric level M2.3 to metric level M7 at time t0 during cycle 0 of the clock signal instead of during cycle 1 of the clock signal. Also, in this embodiment, plot 918 transitions from metric level M2.3 to metric level M7 at time t4 during cycle 1 of the clock signal instead of during cycle 2 of the clock signal.

[0301] In one embodiment, plot 706 (Figure 9C) is sampled in synchronization with plot 914 in the same manner as plot 918 is sampled in synchronization with plot 914. For example, plot 706 is sampled at each rising edge and each falling edge of plot 914.

[0302] In one embodiment, plot 910 (FIG. 9E) is sampled in synchronization with plot 914 in the same manner as plot 918 is sampled in synchronization with plot 914. For example, plot 910 is sampled at each rising edge and each falling edge of plot 914.

[0303] FIG. 10A is a diagram of one embodiment of a system 1000 for illustrating the capture and transfer of metric data. System 1000 includes a DPS 1006, which includes an ADC 1008 and a transceiver 122 (FIG. 1A) of the DPS 102. ADC 1008 is an example of ADC 104 (FIG. 1A), and DPS 1006 is an example of DPS 102. For example, the memory device 212 (FIG. 2A) of ADC 104 is a circular buffer 1010. ADC 1008 includes an ADC processor 210 and a circular buffer 101 0 and. The ADC processor 210 is connected to the circular buffer 101, and the circular buffer 101 0 is connected to the data transceiver 122 of the DPS 1006.

[0304] Examples of the circular buffer 1010 include a first-in first-out (FIFO) buffer, a ring buffer, a circular queue, and a circular buffer. Illustratively, the digital metric data first written to the circular buffer 1010 is also the first to be read or the first to be deleted. When the circular buffer 1010 is full, the digital metric data first written to this circular buffer 1010 is overwritten with digital metric data. System 100 further includes an analysis controller 106 and a process controller 116. Also, a graph 500 is illustrated in FIG. 10A.

[0305] The ADC processor 210 samples the analog metric data 1002 received from the RF sensor 201 and outputs digital metric data 1004, and transmits the digital metric data 1004 to the circular buffer 1010. Examples of the analog metric data 1002 include the analog metric data 202 (FIG. 2A) and the analog metric data 222 (FIGS. 2A and 2B). Examples of the digital metric data 1004 include the digital metric data 204 and the digital metric data 224 (FIGS. 2A and 2B).

[0306] The operation of system 1000 will be described with reference to the states and sub-states of graph 500. For example, the ADC processor 210 of ADC 1008 captures digital metric data 1004 in a circular buffer 1010 during a time window for a certain state, and the digital metric data 1004 is transferred from the circular buffer 1010 to the processor 124 of analysis controller 106 during the next time window. An example of capturing digital metric data 1004 includes converting analog metric data 1002 into digital metric data 1004 and storing the digital metric data 1004 in the circular buffer 1010. Another example of capturing digital metric data 1004 includes storing the digital metric data 1004 in the circular buffer 1010. An example of transferring digital metric data 1004 is reading the digital metric data 1004 from the circular buffer 1010 by transceiver 122 and transmitting the digital metric data 1004 to the transceiver 128 (Figure 2A) of analysis controller 106. By way of illustration, transceiver 122 applies a transfer protocol to the digital metric data 1004 to generate one or more data transfer units and transmits the data transfer units to transceiver 128. In this illustration, transceiver 128 applies a transfer protocol to the received data transfer units to extract the digital metric data 1004 and transmits the digital metric data 1004 to the processor 124 of analysis controller 106. During the next time window for the state in which the digital metric data 1004 is transferred from the circular buffer 1010, the storage of the next state of the digital metric data 1004 received from the ADC processor 210 into the circular buffer 1010 is not performed. As an example, the next time window is the time window of the next state. By way of illustration, if the digital metric data 1004 is captured during state S1 of the digital metric data 1004, the capture of the digital metric data 1004 in state S2 is not performed during state S2. States S1 and S2 occur during the same clock cycle of the clock signal.As another example, the operations described in the previous example are applied to sub - states or slices.

[0307] The capture and transfer of digital metric data 1004 from the circular buffer 1010 are performed in a sequential manner. For example, the digital metric data 1004 is not captured and transferred from the circular buffer 1010 simultaneously. Illustratively, during a first time interval, a first portion of the plot 502 having state S1 is captured (e.g., stored, etc.) in the circular buffer 1010 by the ADC processor 210. During a second time interval, the first portion is transferred from the circular buffer 1010 to the transceiver 122 of the DPS 1006 for transmission to the analysis controller 106, and the capture of a second portion of the plot 502 having state S2 is not performed. The second time interval is consecutive to the first time interval. There is no other time interval between two consecutive time intervals. In this illustration, during a third time interval, a third portion of the plot 502 having state S3 is captured in the circular buffer 1010 by the ADC processor 210. In this illustration, the third time interval is consecutive to the second time interval. During a fourth time interval, the third portion is transferred from the circular buffer 1010 to the transceiver 122 of the DPS 1006 for transmission to the analysis controller 106, and the capture of a fourth portion of the plot 502 having state S4 is not performed. In this illustration, the fourth time interval is consecutive to the third time interval.

[0308] As another example, during a first time interval, a first portion of plot 502 having sub-state S2a is captured (e.g., stored, etc.) in circular buffer 1010 by ADC processor 210. During a second time interval, the first portion is transferred from circular buffer 1010 to transceiver 122 of DPS 1006 for transmission to analysis controller 106, and no capture of a second portion of plot 502 having sub-state S2b is performed. In this example, the second time interval is consecutive to the first time interval. In this example, during a third time interval, a third portion of plot 502 having sub-state S2a is captured in circular buffer 1010 by ADC processor 210. In this example, the third time interval is consecutive to the second time interval.

[0309] As another example, during a first time interval, a first slice of plot 502 is captured (e.g., stored, etc.) in circular buffer 1010 by ADC processor 210. During a second time interval, the first slice is transferred from circular buffer 1010 to transceiver 122 of DPS 1006 for transmission to analysis controller 106, and no capture of a second slice of plot 502 is performed. In this example, the second time interval is consecutive to the first time interval. In this example, during a third time interval, a third slice of plot 502 is captured in circular buffer 1010 by ADC processor 210. The third time interval is consecutive to the second time interval. During a fourth time interval, the third slice is transferred from circular buffer 1010 to transceiver 122 of DPS 1006 for transmission to analysis controller 106, and no capture of a fourth slice of plot 502 is performed. The fourth time interval is consecutive to the third time interval.

[0310] As yet another example, a predetermined number of consecutive states of digital metric data 1004, or a predetermined number of consecutive sub-states of digital metric data, or a capture of a predetermined number of consecutive slices of digital metric data is performed. Following the capture, the digital metric data 1004 is transferred from the circular buffer 1010 to the transceiver 122. As a further example, during a first time interval, a first portion of the plot 502 having states S1 and S2 is captured (e.g., stored, etc.) in the circular buffer 1010 by the ADC processor 210. During a second time interval, the first portion is transferred from the circular buffer 1010 to the transceiver 122 of the DPS 1006 for transmission to the analysis controller 106, and a second portion of the plot 502 having states S3 and S4 is not captured. The second time interval is consecutive to the first time interval. There is no other time interval between two consecutive time intervals.

[0311] As yet another further example, during a first time interval, a first portion of the plot 502 having first and second sub-states is captured (e.g., stored, etc.) in the circular buffer 1010 by the ADC processor 210. During a second time interval, the first portion is transferred from the circular buffer 1010 to the transceiver 122 of the DPS 1006 for transmission to the analysis controller 106, and a second portion of the plot 502 having states S3 and S4 is not captured. The second portion of the plot 502 has third and fourth sub-states. The second time interval is consecutive to the first time interval. There is no other time interval between two consecutive time intervals.

[0312] As yet another further example, during a first time interval, a first portion of plot 502 having a first slice and a second slice is captured (e.g., stored, etc.) in circular buffer 1010 by ADC processor 210. During a second time interval, the first portion is transferred from circular buffer 1010 to transceiver 122 of DPS 1006 for transmission to analysis controller 106, and no capture of a second portion of plot 502 having states S3 and S4 is performed. The second portion of plot 502 has third and fourth slices. The second time interval is consecutive with the first time interval. There are no other time intervals between two consecutive time intervals.

[0313] FIG. 10B is a diagram of one embodiment of monitor 512 for illustrating receipt of instructions from a user for capture and transfer of digital metric data 1004 (FIG. 10A). The GPU of monitor 512 displays a field 1030 for receiving an indication as to whether capture and transfer of digital metric data 1004 is to be performed, with reference to a plurality of states of digital metric data 1004. For example, the user uses mouse 516 or keyboard 514 (FIG. 5B) to provide an instruction to a computer processor located within monitor 512. The GPU of monitor 512 also displays a field 1032 for receiving an indication as to whether capture and transfer of digital metric data 1004 is to be performed, with reference to a plurality of sub-states of digital metric data 1004. For example, the user uses mouse 516 or keyboard 514 (FIG. 5B) to provide an instruction to a computer processor located within monitor 512. Also, the GPU of monitor 512 displays a field 1032 for receiving an indication as to whether capture and transfer of digital metric data 1004 is to be performed, with reference to a plurality of slices of digital metric data 1004. For example, the user uses mouse 516 or keyboard 514 (FIG. 5B) to provide an instruction to a computer processor located within monitor 512.

[0314] The GPU of monitor 512 further displays a field 1036 for receiving the state or sub-state or slice of digital metric data 1004 and the order in which the capture and transfer are to be performed. For example, field 1036 includes a first order 1038 and a second order 1040 in which the state or sub-state or slice of digital metric data 1004 is to be captured and transferred. For example, when an indication of the selection of the first order 1038 is received from the mouse 516 or the keyboard 514 or a combination thereof, a portion of the digital metric data 1004 is captured in the circular buffer 1010 during a first time interval and transferred to the transceiver 122 (FIG. 10A) during a second time interval. In this example, a second portion of the digital metric data 1004 cannot be captured during the second time interval. The second time interval is consecutive with the first time interval. By way of illustration, the first time interval is a time window of the first state of the digital metric data 1004, and the second time interval is a time window of the second state of the digital metric data 1004. As another illustration, the first time interval is a time window of the first sub-state of the digital metric data 1004, and the second time interval is a time window of the second sub-state of the digital metric data 1004. As yet another illustration, the first time interval is a time window of the first slice of the digital metric data 1004, and the second time interval is a time window of the second slice of the digital metric data 1004.

[0315] As another example, when an instruction to select a second order 1040 is received from the mouse 516 or the keyboard 514 or a combination thereof, a first portion of the digital metric data 1004 is captured in the circular buffer 1010 between a first time interval and a second time interval and transferred to the transceiver 122 (FIG. 10A) between a third time interval and a fourth time interval. In this example, a second portion of the digital metric data 1004 cannot be captured between the third and fourth time intervals. The second time interval is continuous with the first time interval. Also, the third time interval is continuous with the second time interval, and the fourth time interval is continuous with the third time interval. By way of illustration, the first time interval is a time window of a first state of the digital metric data 1004, the second time interval is a time window of a second state of the digital metric data 1004, the third time interval is a time window of a third state of the digital metric data 1004, and the fourth time interval is a time window of a fourth state of the digital metric data 1004. As another illustration, the first time interval is a time window of a first sub-state of the digital metric data 1004, the second time interval is a time window of a second sub-state of the digital metric data 1004, the third time interval is a time window of a third sub-state of the digital metric data 1004, and the fourth time interval is a time window of a fourth sub-state of the digital metric data 1004. As yet another illustration, the first time interval is a time window of a first slice of the digital metric data 1004, the second time interval is a time window of a second slice of the digital metric data 1004, the third time interval is a time window of a third slice of the digital metric data 1004, and the fourth time interval is a time window of a fourth slice of the digital metric data 1004.

[0316] FIG. 11A is a diagram of one embodiment of system 1100 for illustrating in-chamber matching, such as within a chamber. System 1100 includes an RF sensor 201, a DPS 102, an analysis controller 106, a process controller 116, and a plasma source 226.

[0317] The operation of system 1100 will be described with respect to graph 500 and graph 1102. Graph 500 shows metric data of a metric for a plasma system including plasma source 226 when the plasma system is in a first condition, such as condition 1. Examples of plasma systems including plasma source 226 include plasma system 100 (FIG. 1A) and plasma system 150 (FIG. 1B).

[0318] The metric data from which plot 502 is generated is measured by RF sensor 201 during a first period when the plasma system has condition 1. Graph 1102 shows metric data of a metric for a plasma system including plasma source 226 when the plasma system is in a second condition, such as condition 2. Graph 1102 includes a plot 1104 of metric data versus time t. The analog metric data on which plot 1104 is based is measured by RF sensor 201 during a second period when the same plasma system has condition 2. The second period occurs after and is equal to the first period. For example, the second period extends from time t8 to time t16. The period between time t8 and t16 spans cycles 3 and 4 of the clock signal. Thus, condition 2 occurs after the occurrence of condition 1. Cycle 4 is consecutive to cycle 3.

[0319] Plot 1104 is the same as Plot 502, except that each metric value of Plot 1104 is M1 lower than the corresponding metric value of Plot 502. For example, at the first time when Plot 502 has a metric value of M8, Plot 1104 has a metric value of M7. As another example, at the second time when Plot 502 has a metric value of M1, Plot 1104 has a metric value of M0. As an example, the metric value M0 is a positive metric value, not zero. In this example, metric values smaller than M0, such as the metric value -M1, are positive metric values. As another example, Plot 1104 has the same state, sub-state, and slice as Plot 502. Illustratively, when Plot 502 has state S2 with a metric value of M8, Plot 1104 has state S2 with a metric value of M7. As another illustration, when the metric value of state S1 of the metric data of Plot 502 is M8, the metric value of state S1 of the metric data of Plot 1104 is M7. As another illustration, when Plot 502 has sub-state S2a with a metric value of M8, Plot 1104 has sub-state S2a with a metric value of M7. As yet another illustration, when Plot 502 has the first slice of sub-state S2a and the first slice of Plot 502 has a metric value of M8, Plot 1104 has sub-state S2a with a metric value of M7, and the first slice of sub-state S2a of Plot 1104 has a metric value of M7.

[0320] Processor 132 compares the metric data of plot 1104 with the metric data of plot 502. For example, processor 132 compares the state of the metric data of plot 1104 with the same state of the metric data of plot 502. As another example, processor 132 compares a sub-state of the state of the metric data of plot 1104 with the same sub-state of the same state of the metric data of plot 502. As yet another example, processor 132 compares a slice of a sub-state of the state of the metric data of plot 1104 with the same slice of the same sub-state of the same state of the metric data of plot 502.

[0321] Based on the comparison, processor 132 determines where there is a mismatch between the metric data of plot 1104 and the metric data of plot 502. For example, processor 132 determines whether the metric data of plot 1104 is at least a pre-set amount smaller or larger than the metric data of plot 502. For example, processor 132 determines whether the state of the metric data of plot 1104 is at least a pre-set amount larger or smaller than the same state of the metric data of plot 502. As another example, processor 132 determines whether a sub-state of the state of the metric data of plot 1104 is at least a pre-set amount larger or smaller than the same sub-state of the same state of the metric data of plot 502. As yet another example, processor 132 determines whether a slice of a sub-state of the state of the metric data of plot 1104 is at least a pre-set amount larger or smaller than the same slice of the same sub-state of the same state of the metric data of plot 502.

[0322] When it is determined that there is a discrepancy between the metric data 1104 and 502, the processor 132 generates instructions for controlling a variable, such as increasing or decreasing it, when the plasma system is in condition 2. The process controller 116 sends the instructions to the analysis controller 106. Upon receiving the instructions, the processor 124 of the analysis controller 106 controls the plasma source 226 of the plasma system in condition 2 based on the instructions until the discrepancy between the metric data of plot 1104 and the metric data of plot 502 is reduced or eliminated. For example, the processor 124 controls the plasma source 226 of the plasma system in condition 2 based on the instructions until the metric data of plot 1104 regarding state S1 changes from M7 to M8.

[0323] In one embodiment, chamber matching is applied to sub - states or slices. For example, plot 1104 Instead of controlling the plasma source 226 until the metric value of state S1 of plot reaches within a preset range from the metric value M8 of plot 502, the variable of the plasma source 226 is controlled until the first metric value of sub - state S2a of state S2 of plot 1104 reaches within a predetermined range from the second metric value of the same sub - state S2a of plot 502. In this example, when the plasma system including the plasma source 226 is in condition 2, the first metric value is sampled by the ADC processor 210 (FIG. 2A), and when the plasma system including the plasma source 226 is in condition 1, the second metric value is sampled by the ADC processor 210. As another example, plot 1104Instead of controlling the plasma source 226 until the metric value of the state S1 is within a preset range from the metric value M8 of plot 502, the plasma source 226 is controlled until the first metric value of the first slice of the state S2 of plot 1104 is within a pre-stored range from the second metric value of the first slice of the state S2 of plot 502. In this example, when the plasma system is in condition 2, the first metric value is sampled by the ADC processor 210, and when the plasma system is in condition 1, the second metric value is sampled by the ADC processor 210.

[0324] In one embodiment, the in-chamber matching described with reference to FIG. 11A is performed by the processor 124 of the analysis controller 106 instead of the processor 132.

[0325] FIG. 11B is a diagram of one embodiment of a system 1150 for illustrating inter-chamber matching, such as between chambers. The system 1150 includes an RF sensor 201, a DPS 102, an analysis controller 106, an RF sensor 1152, a DPS 1156, an analysis controller 1158, a plasma source 1154, and a process controller 116. The operation of the system 1150 will be described with respect to graphs 500 and 1102. Examples of the plasma source 1154 include an RF generator and a matchless plasma source.

[0326] The DPS 1156 includes an ADC 1164 and a data transceiver 1166. As an example, the ADC 1164 is similar in structure and function to the ADC 104, and the data transceiver 1166 is similar in structure and function to the data transceiver 128.

[0327] The analysis controller 1158 includes a transceiver 1168, a processor 1170, and a communication controller 1172. As an example, the transceiver 1168 is similar in structure and function to the transceiver 122, the processor 1170 is similar in structure and function to the processor 124, and the communication controller 1172 is similar in structure and function to the communication controller 130.

[0328] The RF sensor 201 measures analog metric data 222 of an RF signal, such as a supplied or reflected RF signal, transferred through a component of the first plasma system, and transmits the analog metric data 222 to the DPS 102. The ADC processor 210 of the ADC 104 samples the analog metric data 222 to output digital metric data 224, and provides the digital metric data 224 to the transceiver 122. For example, the analog metric data 222 is sampled with respect to a state that is a position of the metric data of the plot 502, and the digital metric data 224 is output. As another example, the analog metric data 222 is sampled with respect to a sub-state that is a position of the metric data of the plot 502, and the digital metric data 224 is output. As yet another example, the analog metric data 222 is sampled with respect to a slice that is a position of the metric data of the plot 502, and the digital metric data 224 is output. The transceiver 122 applies a transfer protocol to the digital metric data 224 to generate a data transfer unit, and transmits the data transfer unit to the transceiver 128.

[0329] Transceiver 128 applies a transfer protocol to the data transfer unit received from transceiver 122, extracts digital metric data 224 from the data transfer unit, and provides the digital metric data 224 to processor 124 of analysis controller 106. Processor 124 transmits the digital metric data 224 to communication controller 130. Communication controller 130 applies a network communication protocol to the digital metric data 224 to generate one or more data packets, and transmits the data packets to communication controller 136 (FIG. 2B) of process controller 116. When receiving one or more data packets, communication controller 136 applies a network communication protocol to extract the digital metric data 224, and provides the digital metric data 224 to processor 132 of process controller 116. Processor 132 generates a portion of plot 502 by combining sample points such as metric data or metric values or sample data or sample values of the digital metric data 224. An example of a portion of plot 502 is a state of plot 502, or a sub-state of plot 502, or a slice of plot 502.

[0330] Similarly, RF sensor 1152, plasma source 1154, DPS 1156, and analysis controller 1158 are components of a plasma system different from the plasma system including RF sensor 201, plasma source 226, DPS 102, and analysis controller 106. For example, RF sensor 1152, plasma source 1154, DPS 1156, and analysis controller 1158 are components of a second plasma system, and RF sensor 201, plasma source 226, DPS 102, and analysis controller 106 are components of a first plasma system. An example of the second plasma system is similar to plasma system 100 or 150 (FIGS. 1A and 1B). RF sensor 1152 is connected to components such as an RF cable of the second plasma system, or an output of plasma source 1154, or an input of a match system, or an output of a match system, or an RF transmission line.

[0331] Also, RF sensor 1152 is connected to ADC 1164, and ADC 1164 is connected to transceiver 1166. Transceiver 1166 is connected to transceiver 1168, and transceiver 1168 is connected to processor 1170. Processor 1170 is connected to communication controller 1172, and communication controller 1172 is connected to the communication controller 136 (FIG. 1B) of process controller 116. Processor 1170 is also connected to plasma source 1154.

[0332] RF sensor 1152 measures analog metric data 1160 of an RF signal, such as transferred, for example, supplied or reflected, via a component of the second plasma system, and transmits the analog metric data 1160 to DPS 1156. The ADC processor of ADC 1164 samples the analog metric data 1160 and outputs digital metric data 1162, and the digital metric data 116 2It is provided to the transceiver 1166. For example, the analog metric data 1160 is sampled with respect to a state that is a certain position of the metric data of the plot 1104, and digital metric data 1162 is output. By way of illustration, the analog metric data 1160 is sampled at the same position such as A1 where the analog metric data 222 is sampled, and with respect to the same time window in which the analog metric data 222 is sampled. As another example, the analog metric data 1160 is sampled with respect to a sub - state that is a certain position of the metric data of the plot 1104, and digital metric data 1162 is output. By way of illustration, the analog metric data 1160 is sampled at the same position such as A1 where the analog metric data 222 is sampled, and with respect to the same time window in which the analog metric data 222 is sampled. In this illustration, the time window extends across sub - states of the states of the analog metric data 222 and 1160. As yet another example, the analog metric data 1160 is sampled at a position covering a slice of the metric data of the plot 1104, and further digital metric data 1162 is output. By way of illustration, the analog metric data 1160 is sampled at the same position such as A1 where the analog metric data 222 is sampled, and with respect to the same time window in which the analog metric data 222 is sampled. In this illustration, the time window extends across a slice of the sub - states of the states of the analog metric data 222 and 1160. The transceiver 1166 applies a transfer protocol to the digital metric data 1162 to generate a data transfer unit, and transmits the data transfer unit to the transceiver 1168.

[0333] Transceiver 1168 applies a transfer protocol to the data transfer unit received from transceiver 1166, extracts digital metric data 1162 from the data transfer unit, and provides the digital metric data 1162 to the processor 1170 of analysis controller 1172. The processor 1170 of analysis controller 1158 transmits the digital metric data 1162 to communication controller 1172. Communication controller 1172 applies a network communication protocol to the digital metric data 1162 to generate one or more data packets, and transmits the data packets to the communication controller 136 (Figure 2B) of process controller 116. When receiving one or more data packets, communication controller 136 applies a network communication protocol to extract the digital metric data 1162, and provides the digital metric data 1162 to the processor 132 of process controller 116. Processor 132 generates a portion of plot 1104 by combining sample points of the digital metric data 1162, such as metric data or metric values or sample data or sample values. An example of a portion of plot 1104 is the state of plot 1104, or a sub-state of plot 1104, or a slice of plot 1104.

[0334] The processor 132 of the process controller 116 receives the digital metric data 224 and 1162. The processor 132 compares the digital metric data 1162 that starts at a certain position and covers a certain time window with the digital metric data 224 that starts at the same position and covers the same time window to determine whether there is a mismatch between the digital metric data 1162 and the digital metric data 224. For example, the processor 132 determines whether the digital metric data 1162 is within a pre-fixed range from the digital metric data 224. By way of illustration, the processor 132 determines whether the digital metric data 1162 collected regarding the state of the metric data 502 is within a pre-fixed range from the same state of the digital metric data 224. As another illustration, the processor 132 determines whether the digital metric data 1162 collected regarding a sub-state of the state of the metric data 502 is within a pre-fixed range from the same sub-state of the same state of the digital metric data 224. As yet another illustration, the processor 132 determines whether the digital metric data 1162 collected regarding a slice of a sub-state of the state of the metric data 502 is within a pre-fixed range from the same slice of the same sub-state of the same state of the digital metric data 224.

[0335] In response to determining that digital metric data 1162 regarding a location and time window is not within a pre-fixed range from digital metric data 224 regarding the same location and the same time window, processor 132 generates instructions for controlling plasma source 1154 until digital metric data 1162 is within the pre-fixed range from digital metric data 224. The instructions include one or more values of variables. Process controller 116 sends the instructions to analysis controller 1158, and analysis controller 1158 controls plasma source 1154 to achieve one or more values of the variables. The variables of plasma source 1154 are controlled until digital metric data 1162 regarding the location and time window is within the pre-fixed range from digital metric data 224 regarding the same location and the same time window. For example, until the metric value M7 of state S1 of plot 1104 is within the pre-fixed range from the metric value M8 of plot 502, e.g., is matched, etc., processor 132 controls plasma source 1154 via analysis controller 1158 to increase or decrease the amount of power output from plasma source 1154. When digital metric data 1162 is within the pre-fixed range from digital metric data 224, the discrepancy between digital metric data 1162 and digital metric data 224 is reduced or eliminated.

[0336] Note that the same clock signal used to convert analog metric data 222 from analog form to digital form is used to convert analog metric data 1160 from analog form to digital form. For example, processor 132 of process controller 116 generates a clock signal and supplies it to ADCs 104 and 1164. ADC 104 samples digital metric data 224 during each clock cycle of the clock signal and samples digital metric data 1162 during the same clock cycle of the same clock signal.

[0337] FIG. 12A is one embodiment of a graph 1200 for illustrating different sampling rates by an ADC processor 210 (FIG. 2A) for edges (e.g., transitions, etc.) of two-state metric data of a metric as compared to a steady state of the metric data. The graph 1200 includes a plot 1202 of analog metric data sampled by the ADC processor 210 versus time t. The plot 1202 is an example of the analog metric data 202 (FIG. 2A). The metric of the graph 1200 is plotted on the y-axis and the time t is plotted on the x-axis.

[0338] During cycle 1 of the clock signal, the plot 1202 includes a rising edge of the metric data between t0 and t0.5, a first instance of a steady state of the metric data between t0.5 and t1.5, and a falling edge between t1.5 and t2.25. The rising edge may also be referred to herein as a rising transition and defines a transition state. Similarly, the falling edge may also be referred to herein as a falling transition and defines a transition state. Further, during cycle 1 of the clock signal, the plot 1202 includes a second instance of a steady state of the metric data between t2.25 and t4. During cycle 2 of the clock signal, the rising edge, the first instance of the steady state, the falling edge, and the second instance of the steady state occur in a similar manner as during cycle 1 of the clock signal, e.g., in the same manner, etc. Between each cycle of the clock signal, the rising and falling edges of the metric data of the plot 1202, and the two instances of the steady state are repeated.

[0339] During each cycle of the clock signal, the ADC processor 210 samples the rising edge of the metric data of plot 1202 with higher accuracy, e.g., a higher sampling rate or a higher frequency, compared to the lower accuracy in sampling the first instance or the second instance of the steady state. For example, during the time interval between time t0 and t0.5, the metric data such as the analog metric data 202 represented by plot 1202 is sampled at a first sampling rate and outputs digital metric data 224. The first sampling rate is greater than the second sampling rate for sampling the metric data of plot 1202 during the time interval between time t0.5 and t1.5. Illustratively, the ADC processor 210 determines whether the rate of increase in the value of the metric data of plot 1202 between the first time and the second time exceeds a preset rate. The second time is within a preset limit time from the first time and occurs after the first time. If it is determined that the rate of increase exceeds the preset rate, the ADC processor 210 decides to sample the metric data such as the analog metric data 202 represented by plot 1202 between the first time and the second time with higher accuracy, e.g., the first sampling rate. On the other hand, if it is determined that the rate of increase does not exceed the preset rate, the ADC processor 210 decides to sample the first instance or the second instance of the steady state of plot 1202 with lower accuracy, e.g., the second sampling rate. As another illustration, the ADC processor 210 is from time t0 to time t 0Determine whether the metric data of plot 1202 at 0.5 is within a predetermined range, such as metric level M8 or a range from a first preset metric level to a second preset metric level. The first preset metric level is a preset percentage, such as 1 or 2 percent, that is less than metric level M8, and the second preset metric level is a preset percentage that is greater than metric level M8. If it is determined that the metric data of plot 1202 between time t0 and t0.5 is not within the predetermined range or is outside the predetermined range, the ADC processor 210 decides to sample the metric data of plot 1202 from time t0 to t0.5 at a first sampling rate. Time t0 is an example of a position. In this illustration, the ADC processor 210 determines whether the metric data of plot 1202 from time t0.5 to time t1.5 is within the predetermined range. Further, if it is determined that the metric data of plot 1202 between time t0.5 and t1.5 is within the predetermined range, the ADC processor 210 decides to sample the metric data of plot 1202 from time t0.5 to time t1.5 at a second sampling rate. Time t0.5 is an example of a position.

[0340] As another example, during each cycle of the clock signal, a processor such as processor 124 or processor 132 determines whether to sample metric data, such as analog metric data 202 represented by plot 1202, at a first sampling rate or at a second sampling rate, controls ADC processor 210 to sample the metric data at the first sampling rate or the second sampling rate, and outputs digital metric data 204. By way of illustration, the processor determines whether the rate of increase of the value of metric data, such as digital metric data 204, represented by plot 1202 between a first time and a second time exceeds a preset rate. If it is determined that the rate of increase exceeds the preset rate, the processor generates an instruction to sample metric data, such as analog metric data 222, represented by plot 1202 between the first time and the second time at a higher accuracy, e.g., the first sampling rate, and sends the instruction to ADC 210. On the other hand, if it is determined that the rate of increase does not exceed the preset rate, the processor generates an instruction to sample metric data, such as analog metric data 222, of a steady state first or second instance of plot 1202 at a lower accuracy, e.g., the second sampling rate, and sends the instruction to ADC 210. In this illustration, when the processor is processor 132, processor 132 sends an instruction to ADC processor 210 via analysis controller 106. As another illustration, the processor determines whether the metric data of plot 1202 from time t0 to time t1.5 is within a predetermined range. If it is determined that the metric data of plot 1202 between time t0.5 and t1.5 is within the predetermined range, the processor determines to sample the metric data of plot 1202 from time t0.5 to time t1.5 at the second sampling rate, and sends an instruction to ADC processor 210 to sample the metric data at the second sampling rate.Also, when it is determined that the metric data of plot 1202 between time t0 and t0.5 is outside a predetermined range, the processor decides to sample the metric data of plot 1202 from time t0 to time t0.5 at a first sampling rate, and sends an instruction to ADC processor 210 to sample the metric data at the first sampling rate.

[0341] Furthermore, during each cycle of the clock signal, the ADC processor 210 samples the falling edge of the metric data of plot 1202 with higher accuracy compared to that of the first instance or the second instance in the steady state. For example, during the time interval between times t1.5 and t2.25, the metric data such as the analog metric data 202 represented by plot 1202 is sampled at the first sampling rate and outputs digital metric data 204. Illustratively, the ADC processor 210 determines whether the rate of decrease in the value of the metric data such as the digital metric data 204 between the first time and the second time exceeds a preset rate. The second time is within a preset limit time from the first time and occurs after the first time. If it is determined that the rate of decrease exceeds the preset rate, the ADC processor 210 decides to sample the metric data of plot 1202 between the first time and the second time with higher accuracy, for example, at the first sampling rate. On the other hand, if it is determined that the rate of decrease does not exceed the preset rate, the ADC processor 210 decides to sample the first instance or the second instance in the steady state of plot 1202 with lower accuracy, for example, at the second sampling rate. As another illustration, the ADC processor 210 determines whether the metric data of plot 1202 from time t1.5 to time t2.25 is within a predetermined range. If it is determined that the metric data of plot 1202 between times t1.5 and t2.25 is not within the predetermined range, the ADC processor 210 decides to sample the metric data of plot 1202 from time t1.5 to t2.25 at the first sampling rate. As yet another illustration, the ADC processor 210 determines whether the metric data of plot 1202 from time t1.5 to time t2.25 is within a predetermined range, for example, within the range of M1 or from the first predetermined metric level to the second predetermined metric level.The first default metric level is a default percentage, such as 1 or 2 percent, that is less than the metric level M2, and the second default metric level is a default percentage that is greater than the metric level M2. When it is determined that the metric data of the plot 1202 between times t1.5 and t2.25 is not within the default range, the ADC processor 210 decides to sample the metric data of the plot 1202 from time t1.5 to time t2.25 at the first sampling rate.

[0342] As another example, during each cycle of the clock signal, a processor such as processor 124 or processor 132 controls the ADC processor 210 to sample the metric data of the rising edge of plot 1202 at a first sampling rate and output digital metric data 224. By way of illustration, the processor determines whether the rate of decrease in the value of the metric data of plot 1202 between a first time and a second time exceeds a preset rate. The second time is within a preset limit time from the first time and occurs after the first time. If it is determined that the rate of decrease exceeds the preset rate, the processor generates an instruction to sample the metric data, such as analog metric data 202, represented by plot 1202 between the first time and the second time at a higher accuracy, for example, the first sampling rate, and sends the instruction to ADC 210. On the other hand, if it is determined that the rate of decrease does not exceed the preset rate, the processor generates an instruction to sample the metric data, such as analog metric data 222, of the first or second instance of the steady state of plot 1202 at a lower accuracy, for example, the second sampling rate, and sends the instruction to ADC 210. In this illustration, when the processor is processor 132, processor 132 sends an instruction to ADC processor 210 via analysis controller 106. As another illustration, the processor determines whether the metric data of plot 1202 from time t1.5 to time t2.25 is within a predetermined range. If it is determined that the metric data of plot 1202 between time t1.5 and t2.25 is not within the predetermined range, the processor controls the ADC processor 210 to sample the metric data of plot 1202 from time t1.5 to time t2.25 at the first sampling rate.

[0343] Note that the metric data of plot 1202 exemplifies a two-state signal. For example, the first instance of the steady state during each cycle of the clock signal has state S1. Illustratively, during state S1, the metric level of plot 1202 is within a predetermined range from metric level M8, for example, within a preset standard deviation. As another example, the second instance of the steady state during each cycle of the clock signal has state S2. Illustratively, during state S2, the metric level of plot 1202 is within a predetermined range from metric level M1, for example, within a preset standard deviation. As another example, each transition between two consecutive steady states such as state S1 and state S2 represented by plot 1202 does not have a single metric level. Rather, in this example, the metric value of the transition is outside the standard deviation of the two consecutive steady states. There is no steady state between two consecutive steady states. Illustratively, the metric value of the rising transition between states S1 and S2 of plot 1202 is outside the first preset standard deviation from metric level M8 of state S1 and outside the second preset standard deviation from metric level M1 of state S2.

[0344] FIG. 12B is an embodiment of a graph 1250 for illustrating different sampling rates applied by an ADC processor 210 (FIG. 2A) for sampling edges such as rising or falling transitions of three-state metric data of a metric as compared to a sampling rate for sampling steady states of the metric data. Graph 1250 includes a plot 1252 of metric data sampled by ADC processor 210 versus time t. Plot 1252 is an example of analog metric data 202 (FIG. 2A). The metric of graph 1250 is plotted on the y-axis and time t is plotted on the x-axis.

[0345] During cycle 1 of the clock signal, plot 1252 includes a first instance of the steady state of the metric data between times t0 and t1, a first instance of the rising edge of the metric data between times t1 and t1.5, a second instance of the steady state of the metric data between times t1.5 and time t2.75, a second instance of the rising edge of the metric data between times t2.75 and time 3.25, and a third instance of the steady state between times t3.25 and time t3.75. Time t2.75 is at three quarters of the time interval between times t2 and t3, time 3.25 is at one quarter of the time interval between times t3 and t4, and time 3.75 is at three quarters of the time interval between times t3 and t4. Further, during cycle 1 of the clock signal, plot 1252 includes a falling edge of the metric data between times t3.75 and t4. During cycle 2 of the clock signal, the first instance of the steady state, the first instance of the rising edge, the second instance of the steady state, the second instance of the rising edge, the third instance of the steady state, and the falling edge occur in a similar manner as during cycle 1 of the clock signal, e.g., in the same manner, etc.

[0346] During each cycle of the clock signal, the ADC processor 210 samples the metric data of plot 1252 at a higher accuracy, e.g., a higher sampling rate or a higher frequency, during the instance of the rising edge or the falling edge, compared to the accuracy in sampling the instance of the steady state, in the same manner as the ADC 210 samples the metric data of plot 1202 (FIG. 12A). For example, the metric data such as the analog metric data 202 represented by plot 1252 during the time interval between time t1 and t1.5 is determined to be sampled by the ADC processor 210 at a first sampling rate, and is sampled to output digital metric data 204. The first sampling rate is greater than the second sampling rate for sampling the metric data of plot 1252 during the time interval between time t0 and t1. The metric data of plot 1252 during the time interval between time t0 and t1 is determined to be sampled by the ADC processor 210 at the second sampling rate and is sampled. As another example, during each cycle of the clock signal, a processor such as processor 124 or processor 132 controls the ADC processor 210 to sample the metric data of plot 1252 between time t1 and t1.5 at the first sampling rate and output digital metric data 204. The first sampling rate is greater than the second sampling rate for sampling the metric data of plot 1252 during the time interval between time t0 and t1. As yet another example, the metric data of plot 1252 during the time interval between time t3.75 and t4 is determined to be sampled at the first sampling rate and is sampled to output digital metric data 204. The first sampling rate is greater than the second sampling rate for sampling the metric data of plot 1252 during the time interval between time t3.25 and t3.75.The metric data of plot 1252 during the time interval between times t3.25 and t3.75 is determined to be sampled by ADC processor 210 at a second sampling rate and is sampled. As yet another example, during each cycle of the clock signal, a processor such as processor 124 or processor 132 controls ADC processor 210 to sample metric data such as analog metric data 202 between times t3.75 and t4 of plot 1252 at a first sampling rate and output digital metric data 204. The first sampling rate is greater than the second sampling rate for sampling the metric data of plot 1252 during the time interval between times t3.25 and t3.75.

[0347] Note that the metric data of plot 1252 exemplifies a three-state signal. For example, the first instance of the steady state during each cycle of the clock signal has state S1. Illustratively, during state S1, the metric level of plot 1252 is within a predetermined range from metric level M2, for example, within a preset standard deviation. As another example, the second instance of the steady state during each cycle of the clock signal has state S2. Illustratively, during state S2, the metric level of plot 1252 is within a predetermined range from metric level M5, for example, within a preset standard deviation. As yet another example, the third instance of the steady state between each cycle of the clock signal has state S3. Illustratively, during state S3, the metric level of plot 1252 is within a predetermined range from metric level M11, for example, within a preset standard deviation. Metric level M11 is greater than metric level M8. As another example, each transition between two consecutive steady states, such as between state S1 and state S2 or between state S2 and state S3, represented by plot 1252, does not have a single metric level. Rather, in this example, the metric value of the transition is outside the standard deviation of the two consecutive steady states. There is no steady state between two consecutive steady states. Illustratively, the metric value of the rising transition between states S1 and S2 of plot 1252 is outside the first preset standard deviation from metric level M2 of state S1 and outside the second preset standard deviation from metric level M5 of state S2.

[0348] Note that some of the embodiments of this specification describe a processor.

[0349] In one embodiment, instead of the rising transition that occurs between states S2 and S3 of plot 1252, a falling transition occurs. In this embodiment, state S3 has a lower metric level compared to metric level M5 of state S2.

[0350] FIG. 13 is a diagram of one embodiment of monitor 512 for illustrating reception of sampling rates for each edge and each steady state during each cycle of a clock signal. Monitor 512 includes a display of graph 1200. Below graph 1200, three fields 1302, 1304, and 1306 are generated for display by the GPU of monitor 512.

[0351] The user uses keyboard 514 or mouse 516 (FIG. 5B) or a combination thereof to provide sampling rate values within each of fields 1302, 1304, and 1306 for each cycle of the clock signal. For example, the computer processor of monitor 512 receives a sampling rate for sampling the rising edge of plot 1202 during each cycle of the clock signal within field 1302. As another example, the computer processor receives a sampling rate for sampling the falling edge of plot 1202 during each cycle of the clock signal within field 1304. As yet another example, the computer processor receives a sampling rate for sampling instances such as a first instance and a second instance of the steady state of plot 1202 during each cycle of the clock signal within field 1306. In this example, the first instance of the steady state is between the rising edge of the cycle and the falling edge of plot 1202 during that cycle, and the second instance is between the falling edge and the next rising edge of plot 1202 during the immediately following cycle. In this example, a cycle precedes the immediately following cycle.

[0352] When monitor 512 is part of analysis controller 106 (FIG. 1A), the computer processor of monitor 512 transmits the sampling rates received within fields 1302, 1304, and 1306 to ADC processor 210 (FIG. 2A) via transceivers 122 and 128. ADC processor 210 samples analog metric data 222 (FIG. 2B) according to the sampling rates received within fields 1302, 1304, and 1306 and outputs digital metric data 224 (FIG. 2B).

[0353] In one embodiment, when monitor 512 is part of analysis controller 116 (FIG. 1B), the computer processor of monitor 512 transmits the sampling rates received within fields 1302, 1304, and 1306 to processor 124 of analysis controller 106 via communication controllers 136 and 130 (FIG. 2B). Processor 124 transmits the sampling rates received within fields 1302, 1304, and 1306 to ADC processor 210 (FIG. 2A). Upon receiving the sampling rates, ADC processor 210 samples analog metric data 222 according to the sampling rates and outputs digital metric data 224.

[0354] In one embodiment, instead of field 1306, two different fields are generated by the GPU of monitor 512 for display on monitor 512. The two fields include a first field and a second field. The user uses keyboard 514 or mouse 516 or a combination thereof to provide a first sampling rate within the first field and a second sampling rate within the second field. The first sampling rate is for sampling the first steady-state instance of plot 1202 (FIG. 12A) during each cycle of the clock signal. The second sampling rate is for sampling the second steady-state instance of plot 1202 during each cycle of the clock signal. The computer processor of monitor 512 receives the first and second sampling rates provided within the first and second fields.

[0355] In one embodiment, instead of field 1306, six different fields are generated by the GPU of monitor 512 for display. 6The fields include a first field, a second field, a third field, a fourth field, a fifth field, and a sixth field. The user uses the keyboard 514 or the mouse 516 or a combination thereof to provide a first sampling rate within the first field, a second sampling rate within the second field, a third sampling rate within the third field, a fourth sampling rate within the fourth field, a fifth sampling rate within the fifth field, and a sixth sampling rate within the sixth field. The first sampling rate is for sampling the first steady-state instance of the plot 1252 (FIG. 12B) during each cycle of the clock signal. The second sampling rate is for sampling the second steady-state instance of the plot 1252 during each cycle of the clock signal. The third sampling rate is for sampling the third steady-state instance of the plot 1252 during each cycle of the clock signal. The fourth sampling rate is for sampling the first rising edge of the plot 1252 during each cycle of the clock signal, and the fifth sampling rate is for sampling the second rising edge of the plot 1252 during each cycle of the clock signal. The sixth sampling rate is for sampling the falling edge of the plot 152 during each cycle of the clock signal. The computer processor receives the first through sixth sampling rates provided within the first through sixth fields.

[0356] FIG. 14A is a diagram of one embodiment of a payload 1400 of a data gram for illustrating a method by which digital metric data 204 (FIG. 2A) is transferred between an analysis controller 106 (FIG. 1A) and a process controller 116 (FIG. 1A). For example, the data gram is generated by a communication controller 130 of the analysis controller 106 by applying a network communication protocol and transmitted to a communication controller 136 of the process controller 116. By way of illustration, the communication controller 130 receives data inserted in fields 1410A, 1410B, and 1410E from a processor 124, applies a network communication protocol to generate a data gram, and transmits the data gram to the communication controller 136. In this example, the communication controller 136 applies a network communication protocol to the data gram to extract data from fields 1410A, 1410B, and 1410E and provides the data to a processor 132 of the process controller 116 for analysis. Further, in this example, the processor 132 determines data to be inserted in fields 1410C, 1410D, and 1410E based on the data received in fields 1410A, 1410B, and 1410E and provides the data to be inserted in fields 1410C, 1410D, and 1410E to the communication controller 136. In this example, the communication controller 136 receives data to be inserted in fields 1410C, 1410D, and 1410E from the processor 132, applies a network communication protocol to generate a data gram, and transmits the data gram to the communication controller 130. Continuing the example, the communication controller 130 receives data from the communication controller 136, applies a network communication protocol to extract data from fields 1410C, 1410D, and 1410E, and provides the data to the processor 124. The processor 124 controls a plasma source according to the data received in fields 1410C, 1410D, and 1410E. Examples of plasma sources include plasma sources 226 and 1154 (FIG. 11B).

[0357] Examples of data grams include packets such as UDP packets, TCP / IP packets, or UDP / IP packets. Payload 1400 includes a sample set (SS) 1402, followed by a plurality of sample sets 1404. For example, payload 1400 includes sample set 1, followed by a plurality of sample sets 2 to Ma, where Ma is a positive integer greater than 1. By way of illustration, Ma is in the range of 7 to 9. Further by way of illustration, Ma is 8.

[0358] Each of the sample sets 1 to Ma of payload 1400 stores digital metric data such as digital metric data 204 or 224 (FIGS. 2A and 2B) output by ADC processor 210 (FIG. 2A), and the digital metric data is sampled from an edge such as a rising edge or a falling edge of analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). For example, sample set 1402 includes digital metric data output by ADC processor 210 by sampling the rising edge of plot 1202 (FIG. 12A). Further, in this example, each of sample sets 1404 includes digital metric data of the metric output by ADC processor 210 by sampling the rising edge of plot 1202. The digital metric data corresponding to the edge is sampled during one or more cycles of the clock signal.

[0359] Payload 1400 further includes another sample set 1406, followed by a plurality of sample sets 1408. For example, payload 1400 includes sample set 1, followed by a plurality of sample sets 2 to Na, where Na is a positive integer greater than 1. By way of illustration, Na is in the range of 60 to 64. Further by way of illustration, Na is 62. Each sample set of payload 1400 has a fixed number of bytes P, where P is a positive integer.

[0360] Each of Sample Sets 1 through Na stores digital metric data output by the ADC processor 210 by sampling the steady state of analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). For example, Sample Set 1406 includes digital metric data of a metric output by the ADC processor 210 by sampling the first instance of the steady state of Plot 1202. Further, in this example, each of Sample Sets 1408 includes digital metric data of a metric output by the ADC processor 210 by sampling the first instance of the steady state of Plot 1202. As an example, it should be noted that if the first instance of the steady state of Plot 1202 is long compared to the rising edge of Plot 1202, Na is greater than Ma. The rising edge precedes the first instance of the steady state of Plot 1202. The digital metric data corresponding to the steady state is sampled during the same one or more cycles of the clock signal at which the digital metric data corresponding to the edge is sampled.

[0361] The sample set 1402 of the payload 1400 includes a plurality of fields, and the plurality of fields include a field 1410A for storing a digital metric value of forward power or delivered power sampled by the ADC processor 210, a field 1410B for storing a digital metric value of reverse power sampled by the ADC processor 210, a field 1410C for storing a frequency value of an RF signal supplied by the plasma source, a field 1410D for storing setpoint data, a field 1410E for storing the status of the RF signal, and a reverse field 1410F. As an example of the setpoint data, the amount of power or the amount of voltage supplied by the plasma source can be mentioned. Examples of the status of the RF signal include whether the plasma source operates in continuous wave (CW) mode or pulse mode, the number of states of the RF signal, whether fields 1410A and 1410B include digital power values at the edge or steady state of the metric data of the metric, whether field 1410A includes forward power or delivered power as metric data, or whether the frequency in field 1410C is manually adjusted by the user or automatically adjusted by the computer processor of the monitor 512 (FIG. 5B). In pulse mode, the RF signal has a plurality of states. In CW mode, the RF signal has a single state. Similarly, each of the sample sets 2 to Ma of the payload 1400 includes a plurality of fields such as fields 1410A to 1410F. Further, each of the sample sets 1 to Na of the payload 1400 includes a plurality of fields such as fields 1410A to 1410F.

[0362] In one embodiment, the payload 1400 is limited by a maximum byte size in the range of 1300 bytes to 1700 bytes. For example, the payload 1400 is limited by a byte size of 1500 bytes. In another example, the payload 1400 is limited by a byte size of 1600 bytes.

[0363] In one embodiment, each of the fields 1410A to 1410F has a size of bit number a1, where a1 is a positive integer. For example, field 1410A stores a digital value of forward power, and the digital value is represented by 16 bits. As another example, field 1410A stores a digital value of forward power measured in watts, and the digital value is represented by 8 bits or 32 bits. Illustratively, the digital value of forward power is restricted by a resolution of b1 watts, where b1 is a positive integer or a positive real number. Illustratively, b1 is 0.5 watts or 1 watt or 2 watts or 3 watts. As used herein, the resolution is the minimum unit, or increment or decrement. As another example, field 1410B stores a digital value of reverse power, and the digital value is represented by 16 bits. Illustratively, the digital value of reverse power is restricted by a resolution of b1 watts. Further illustratively, field 1410B stores a digital value of reverse power, and the digital value is represented by 8 bits or 32 bits. As another example, field 1410C stores a digital value of the frequency of the RF signal generated by the plasma source, and the digital value is represented by 16 bits. Illustratively, the digital value of the frequency is restricted by a resolution of b2 kilohertz (kHz), where b2 is a positive integer or a positive real number. Illustratively, b2 is 0.5 kHz or 1 kHz or 2 kHz. As yet another example, field 1410D stores a digital value of setpoint data, and the digital value is represented by 16 bits. As another example, field 1410D stores a digital value of forward power or supply power measured in watts, and the digital value is represented by 8 bits or 32 bits. Illustratively, the digital value of forward power is restricted by a resolution of b1 watts.

[0364] As another example, field 1410E stores a digital value of the status, and the digital value is represented in 16 bits or 32 bits. By way of illustration, field 1410E includes 1 bit indicating whether the plasma source operates in CW mode or pulse mode, 2 bits indicating the number of states of the RF signal generated by the plasma source, and a bit indicating whether the sample set having field 1410E has digital metric data regarding either the steady state of the metric or the edge of the metric. By way of illustration, the digital value of the metric data in the steady state of the metric is restricted to a resolution of b3 microseconds, and the digital value of the metric data at the edge of the metric is restricted to a resolution of b4 microseconds. Further by way of illustration, b3 ranges from 130 to 180, and b4 ranges from 15 to 25. Further by way of illustration, b3 is 160, and b4 is 20. As another illustration, b3 is 140. As yet another illustration, b3 is 150 and b4 is 25. Field 1410E further includes 1 bit indicating whether the digital value of either the forward power or the delivered power measured by an RF sensor such as RF sensor 201 or 1152 (FIG. 11B) is included in field 1410A. Field 1410E further includes 1 bit indicating whether the frequency in field 1410C of the plasma source is manually adjusted by the user or automatically adjusted by a computer processor. As another example, field 1410F includes any 32-bit data not included in fields 1410A - 1410E.

[0365] In one embodiment, each sample set described herein includes a timestamp field for defining a timestamp. For example, the timestamp field is located between fields 1410E and 1410F. The timestamp indicates the number of bits in each of fields 1410A, 1410B, 1410C, 1410D, and 1410E. For example, the timestamp is equal to 32 bits, or 16 bits, or 8 bits. By way of illustration, the timestamp provides a resolution at which metric data is sampled within field 1410A or within field 1410B. Further by way of illustration, the timestamp provides a resolution in the range of 0.8 ms to 1.2 ms, such as 1 ms.

[0366] In one embodiment, the reverse field 1410F is not included within each sample set.

[0367] FIG. 14B is an embodiment of the payload 1420 of a single packet transferred between the analysis controller 106 (FIG. 1A) and the process controller 116 (FIG. 2B). The payload 1420 includes a plurality of states such as state S1, state S2, and state S3, and metric data regarding the rising edge or falling edge associated with each of the states. The rising edge or falling edge is associated with the state when it precedes or is immediately after the state. The payload 1420 is used to illustrate that each of the numbers Nb, Nc, and Nd of the sample sets of the payload 1420 is smaller than the number Na of the sample sets of the payload 1400, where each of Nb, Nc, and Nd is a positive integer. For example, the number Nb, or Nc, or Nd of the sample sets of the payload 1420 is 1, and the number Na of the sample sets of the payload 1400 is 30. As another example, the number Nb, or Nc, or Nd of the sample sets of the payload 1420 is 2, and the number Na of the sample sets of the payload 1400 is 20. Further, the payload 1420 is used to illustrate that each of the numbers Mb, Mc, and Md of the sample sets of the payload 1420 is smaller than the number Ma of the sample sets of the payload 1400, where each of Mb, Mc, and Md is a positive integer.

[0368] As an example, it should be noted that the total size of the payload 1420, such as the total number of sample sets, etc., is equal to the total size of the payload 1400, such as the total number of sample sets, etc. As an example, the sum of the numbers Mb, Mc, and Md is equal to Ma, and the sum of the numbers Nb, Nc, and Nd is equal to Na. In addition, as an example, the resolution of each of the sample sets Nb, Nc, and Nd of the payload 1420 is different from the resolution of each of the sample sets Na of the payload 1400 (FIG. 14A), for example, smaller, etc. By way of illustration, the resolution of each of the sample sets Nb, Nc, and Nd of the payload 1420 is 140 microseconds, and the resolution of each of the sample sets Na of the payload 1400 is 160 microseconds.

[0369] Each of the sample sets 1 to Mb of the payload 1420 stores digital metric data output by the ADC processor 210 (FIG. 2A) by sampling an edge such as a rising edge or a falling edge of the analog metric data 202 (FIG. 2A) or 222 (FIG. 2B), and the edge is related to the steady state of the metric data. For example, the edge is adjacent to the steady state of the metric data, for example, immediately after or immediately before, and provides a transition to another steady state. For example, the sample set 1422 of the payload 1420 includes digital metric data of the metric output by the ADC processor 210 by sampling the first instance of the rising edge of the plot 1252 (FIG. 12B). In this example, the rising edge follows and is adjacent to the first instance of the steady state of the plot 1252. In this example, the first instance of the steady state of the plot 1252 is state S1. Illustratively, the first instance of the rising edge of the plot 1252 occurs during the time interval between time t1 and time t1.5. Further, in this illustration, each of the sample sets 1424 includes digital metric data of the metric output by the ADC processor 210 by sampling the first instance of the rising edge of the plot 1252.

[0370] Payload 1420 further includes another sample set 1426, followed by a plurality of sample sets 1428. For example, after sample set 1 of payload 1420, sample sets 2 to Nb follow, where Nb is smaller than Mb. Sample set 1426 follows sample set 1424. Each of sample sets 1426 and 1428 of payload 1420 stores digital metric data output by ADC processor 210 by sampling the steady state of analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). For example, sample set 1426 includes digital metric data output by ADC processor 210 by sampling the first instance of the steady state of plot 1252. In this example, the first instance of the steady state of plot 1252 occurs between times t0 and t1 and is referred to herein as state S1. Further, in this example, each of sample sets 1428 includes digital metric data of the metric output by ADC processor 210 by sampling the first instance of the steady state of plot 1252.

[0371] Following the plurality of sample sets 1428 are sample sets 1430 and 1432 of payload 1420. For example, following sample set 1 of payload 1420 are sample sets 2 to Mc. As another example, payload 1420 includes sample set 1430, and sample set 1430 includes digital metric data output by ADC processor 210 by sampling a second instance of the rising edge of plot 1252. In this example, the second instance of the rising edge follows and is adjacent to the second instance of the steady state of plot 1252. Further, in this example, the second instance of the rising edge of plot 1252 is in state S2. Illustratively, the second instance of the rising edge occurs during a time interval between time t2.75 and time t3.25. Further, in this example, each of sample sets 1432 includes digital metric data output by ADC processor 210 by sampling a second instance of the rising edge of plot 1252.

[0372] Payload 1420 further includes another sample set 1434 following sample set 1432, and a plurality of sample sets 1436 follow sample set 1434. For example, following sample set 1 of payload 1420, sample sets 2 to Nc follow, where Nc is smaller than Mc. In this example, each of sample sets 1434 and 1436 of payload 1420 stores digital metric data output by ADC processor 210 by sampling a steady state of analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). By way of illustration, sample set 1436 includes digital metric data output by ADC processor 210 by sampling a second instance of the steady state of plot 1252. In this illustration, the second instance of the steady state of plot 1252 occurs between times t1.5 and t2.75 and is referred to herein as state S2. Further, in this example, each of sample sets 1436 includes digital metric data output by ADC processor 210 by sampling a second instance of the steady state of plot 1252.

[0373] Payload 1420 also includes sample set 1438 that follows sample set 1436, and is followed by a plurality of sample sets 1440. For example, after sample set 1 of payload 1420, sample sets 2 to Md follow. As another example, sample set 1438 of payload 1420 includes digital metric data of a metric output by ADC processor 210 by sampling the falling edge of plot 1252. In this example, the falling edge follows and is adjacent to the third instance of the steady state of plot 1252. Further, in this example, the third instance of the steady state of plot 1252 is state S3. Illustratively, the falling edge occurs during the time interval between time t3.75 and time t4. Further, in this illustration, each of sample sets 1440 includes digital metric data of a metric output by ADC processor 210 by sampling the falling edge of plot 1252.

[0374] Payload 1420 further includes another sample set 1442 following sample set 1440, and a plurality of sample sets 1444 follow sample set 1442. For example, after sample set 1 of payload 1420, sample sets 2 to Nd follow, where Nd is smaller than Md. Each of sample sets 1442 and 1444 of payload 1420 stores digital metric data output by ADC processor 210 by sampling the steady state of analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). As an example, sample set 1442 includes digital metric data of the metric output by ADC processor 210 by sampling the third instance of the steady state of plot 1252. In this example, the third instance of the steady state of plot 1252 occurs between times t3.25 and t3.75 and is referred to herein as state S3. Further, in this example, each of sample sets 1444 includes digital metric data of the metric output by ADC processor 210 by sampling the third instance of the steady state of plot 1252.

[0375] Each sample set of payload 1420 has a default number of bytes P, where P is a positive integer. Further, each sample set of payload 1420 includes a plurality of fields such as fields 1410A to 1410F (FIG. 14A).

[0376] It should be further noted that the number of edges in which digital metric data is stored in payload 1420 is greater than the number of edges in which digital metric data is stored in payload 1400. For example, payload 1420 includes digital metric data sampled from three edges, and payload 1400 includes digital metric data sampled from one edge. A processor, such as processor 124 or processor 132, calculates a first number of edges of digital metric data to be stored in payload 1420. The first number of edges occurs during each cycle of the clock signal. Similarly, the processor calculates a second number of edges of digital metric data to be stored in payload 1400, and the second number of edges occurs during each cycle of the clock signal. The processor further compares the first number of edges with the second number of edges to determine whether the first number is greater than the second number. In response to determining that the first number of edges is greater than the second number of edges, the processor compares the number of sample sets assigned within payload 1400 to each digital metric data of the second number of edges, and determines to assign a smaller number of sample sets within payload 1420 to each digital metric data of the first number of edges. The processor provides an instruction indicating the number of sample sets assigned to each digital metric data of the first number of edges to a communication controller, such as communication controller 130 or 136 (FIG. 1A). Upon receiving the instruction, the communication controller generates a packet having payload 1420. Further, the processor provides another instruction indicating the number of sample sets assigned to each digital metric data of the second number of edges to the communication controller. Upon receiving the other instruction, the communication controller generates a packet having payload 1400.

[0377] Note also that the number of steady states of the digital metric data stored in payload 1420 is greater than the number of steady states of the digital metric data stored in payload 1400. For example, payload 1420 includes digital metric data sampled from three steady states, and payload 1400 includes digital metric data sampled from one steady state. A processor, such as processor 124 or processor 132, calculates a first number of steady states of the digital metric data to be stored in payload 1420. The first number of steady states occurs during each cycle of the clock signal. Similarly, the processor calculates a second number of steady states of the digital metric data to be stored in payload 1400, and the second number of steady states occurs during each cycle of the clock signal. The processor further compares the first number of steady states with the second number of steady states to determine whether the first number is greater than the second number. In response to determining that the first number of steady states is greater than the second number of steady states, the processor compares the number of sample sets assigned within payload 1400 to each digital metric data of the second number of steady states, and determines to assign a smaller number of sample sets within payload 1420 to each digital metric data of the first number of steady states. The processor provides an instruction indicating the number of sample sets assigned to each digital metric data of the first number of steady states to a communication controller, such as communication controller 130 or 136 (FIG. 1A). Upon receiving the instruction, the communication controller generates a packet having payload 1420. Further, the processor provides another instruction indicating the number of sample sets assigned to each digital metric data of the second number of steady states to the communication controller. Upon receiving the other instruction, the communication controller generates a packet having payload 1400.

[0378] In one embodiment, payload 1420 is limited by a maximum byte size.

[0379] In one embodiment, the terms packet and datagram are used interchangeably herein.

[0380] FIG. 14C-1 is a diagram of one embodiment of payloads 1470, 1472, 1474, and 1476 of a plurality of packets, such as packet 1, packet 2, packet 3, and packet 4, to illustrate that a large amount of steady-state digital metric data can be distributed among the packets. Packets 1-4 are transferred between the analysis controller 106 and the process controller 116 (FIG. 2B). The payload 1470 of packet 1 includes digital metric data of an edge, such as a rising edge or a falling edge, related to the state S1 of the metric. Each sample set 1-Me of the payload 1470 stores digital metric data output by the ADC processor 210 (FIG. 2B) from an edge, such as a rising edge or a falling edge, of the analog metric data 202 (FIG. 2A) or 222 (FIG. 2B), where the edge is related to the state S1 of the metric data, and Me is a positive integer. The edge is adjacent to the steady state of the metric data, for example, preceding or immediately following, providing a transition from one steady state to another steady state. For example, the sample set 1478A of the payload 1470 includes digital metric data output by the ADC processor 210 by sampling the rising edge of the plot 1202 (FIG. 12A). In this example, the rising edge precedes and is adjacent to the first instance of the steady state of the plot 1202. Further, in this example, the first instance of the steady state of the plot 1202 is the state S1. Illustratively, the rising edge occurs during the time interval between time t0 and time t0.5. Further, in this illustration, each of the plurality of sample sets 1478B includes digital metric data output by the ADC processor 210 by sampling the rising edge of the plot 1202.

[0381] The payload 1472 of packet 2 includes sample set 1478C that follows sample set 1478A, and is followed by a plurality of sample sets 1478D. For example, after sample set 1 of payload 1472, sample sets 2 to Ne follow, where Ne is greater than Me and is a positive integer. Each of sample set 1478C and sample set 1478D of payload 1472 stores digital metric data output by the ADC processor 210 by sampling the steady state of analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). For example, sample set 1478C includes digital metric data of the metric output by the ADC processor 210 by sampling the first instance of the steady state of plot 1202. The first instance of the steady state of plot 1202 occurs between times t0.5 and t1.5 and is referred to herein as state S1. Further, each of sample sets 1478D includes digital metric data output by the ADC processor by sampling the first instance of the steady state of plot 1202.

[0382] The payload 1474 of packet 3 includes a sample set 1478E that follows the sample set 1478D, and is followed by a plurality of sample sets 1478F. For example, after the sample set 1 of the payload 1474, sample sets 2 to Nf follow, where Nf is a positive integer. Each of the sample sets 1478E and 1478F of the payload 1474 stores digital metric data output by the ADC processor 210 from the steady state of the analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). For example, the sample set 1478E includes digital metric data of the metric output by the ADC processor 210 by sampling the first instance of the steady state S1 of the plot 1202. Further, in this example, each of the sample sets 1478F includes digital metric data output by the ADC processor 210 by sampling the first instance of the steady state of the plot 1202.

[0383] The payload 1476 of packet 4 includes a sample set 1478G that follows the sample set 1478F, and a plurality of sample sets 1478H follow the sample set 1478G. For example, sample sets 2 to Ng follow the sample set 1 of the payload 1476, where Ng is a positive integer. Each of the sample sets 1478G and 1478H of the payload 1476 stores digital metric data output by the ADC processor 210 from the steady state of the analog metric data 202 (FIG. 2A) or 222 (FIG. 2B). For example, the sample set 1478G includes digital metric data of the metric output by the ADC processor 210 by sampling the first instance of the steady state S1 of the plot 1202. Further, in this example, each of the sample sets 1478H includes digital metric data output by the ADC processor 210 by sampling the first instance of the steady state of the plot 1202. As illustrated, the payloads of packets 2 to 4 include digital metric data of the metric output by sampling the first instance of the steady state of the plot 1202.

[0384] Each sample set of any of the payloads 1470, 1472, 1474, and 1476 is limited to a number P of bytes.

[0385] Figure 14C-2 is a diagram of one embodiment of payload 1480 of packet 5, including digital metric data of edges related to steady state S2. Packet 5 is transferred between analysis controller 106 and process controller 116 (Figure 2B). Payload 1480 of packet 5 includes metric data related to edges such as rising edges or falling edges related to the state S2 of the metric. Each sample set 1 to Mf of payload 1480 stores digital metric data output by ADC processor 210 (Figure 2B) by sampling an edge such as a rising edge or a falling edge of analog metric data 202 (Figure 2A) or 222 (Figure 2B). The edge is related to the state S2 of the metric data, where Mf is a positive integer. The edge is adjacent to the steady state of the metric data, for example, preceding or following immediately, providing a transition from one steady state to another steady state. For example, sample set 1478I of payload 1480 includes digital metric data output by ADC processor 210 by sampling the falling edge of plot 1202 (Figure 12A). In this example, the falling edge precedes and is adjacent to the second instance of the steady state of plot 1202. Further, in this example, the second instance of the steady state of plot 1202 is state S2. Illustratively, the falling edge occurs during the time interval between time t1.5 and time t2.25. Further, in this illustration, each of the plurality of sample sets 1478J includes digital metric data output by ADC processor 210 by sampling the falling edge of plot 1202.

[0386] Each sample set of payload 1480 is limited to a number P of bytes.

[0387] Note also that the number of steady-state sample sets of digital metric data stored in Packets 2-4 is greater than the number of steady-state sample sets of digital metric data stored in Payload 1400 (Figure 14A). For example, Payloads 1472, 1474, and 1476 contain digital metric data sampled from one state, and Payload 1400 contains digital metric data sampled from one steady state. A processor, such as Processor 124 or Processor 132, calculates a first time window of the steady state of the digital metric data to be stored in Payloads 1472, 1474, and 1476. The steady state occurs during each cycle of the clock signal. Similarly, the processor calculates a second time window of the steady state of the digital metric data to be stored in Payload 1400, and the steady state occurs during each cycle of the clock signal. The processor further compares the first time window with the second time window to determine whether the first time window is larger than the second time window. In response to determining that the steady state of the first time window is larger than the second time window, the processor determines to store a greater amount of digital metric data in Payloads 1472, 1474, and 1476 as compared to the amount of digital metric data stored in Payload 1400. Further, in response to determining that the first time window is larger than the second time window, the processor determines to assign a first number of packets to the digital metric data collected during the first time window as compared to a second number of packets assigned to the digital metric data collected during the second time window. The first number of packets is larger than the second number of packets. The processor provides an instruction indicating the first number of packets to be assigned to the digital metric data collected during the first time window to a communication controller, such as Communication Controller 130 or 136 (Figure 1A). Upon receiving the instruction, the communication controller generates packets having Payloads 1472, 1474, and 1476.Furthermore, the processor provides another instruction to the communication controller indicating a second number of packets assigned to the digital metric data collected during the second time window. Upon receiving the other instruction, the communication controller generates a packet having a payload 1400.

[0388] FIG. 15 is a diagram of an embodiment of system 1500 for illustrating details of MPS1514. MPS1514 is an example of any one of a1 to a(n + M) of MPS (FIG. 1B). System 1500 includes MPS1514, connection 1510, and plasma chamber 152. MPS1514 includes input section 1502, output section 1504, and reactance circuit 1506. An example of input section 1502 includes a signal generator and a part of a gate driver. An example of the signal generator is a rectangular wave oscillator that generates a rectangular wave signal such as a digital waveform or a pulse train. The rectangular wave generates pulses between a first logic level such as high or 1 and a second logic level such as low or 0. Examples of output section 1504 include the remaining part of the gate driver and a half-bridge transistor circuit. Furthermore, an example of reactance circuit 1506 is a variable capacitor. Another example of reactance circuit 1506 is a fixed capacitor.

[0389] Input section 1502 is connected to output section 1504, and output section 1504 is further connected to reactance circuit 1506. Reactance circuit 1506 is connected to electrode 1508 disposed in plasma chamber 152 via connection 1510. Examples of electrode 1508 include the lower electrode of chuck 118 (FIG. 1B), RF coil 154A, RF coil 154B, and RF coil 154C (FIG. 1B).

[0390] The input section 1502 generates a plurality of rectangular wave signals and provides the rectangular wave signals to the output section 1504. The output section 1504 generates an amplified rectangular waveform from the plurality of rectangular wave signals received from the input section 1504. Further, the output section 1504 shapes the envelope such as the peak-to-peak amplitude of the amplified rectangular waveform. For example, a shaping control signal 1508 is supplied from the input section 1502 to the output section 1504 to generate the envelope. The shaping control signal 1508 has a plurality of voltage values for shaping the amplified rectangular waveform.

[0391] The shaped amplified rectangular waveform is transmitted from the output section 1504 to the reactance circuit 1506. The reactance circuit 1506 removes the higher harmonics of the amplified rectangular waveform and generates an RF signal 1512 which is a shaped sine waveform having a fundamental frequency, for example, by filtering. Examples of the RF signal 1512 include the RF signals 140a1, 140a2, 140an, 140a(n + 1), and 140a(n + m). The shaped sine waveform has a shaped envelope.

[0392] The RF signal 1512 is transmitted from the reactance circuit 1506 to the electrode 1508 via the connection 1510 for processing the substrate S. Further, one or more process materials such as a fluorine-containing gas, an oxygen-containing gas, a nitrogen-containing gas, and a liquid for depositing a metal and a dielectric are supplied to the plasma chamber 152. When receiving the shaped sine waveform and the one or more process materials, the plasma is ignited in the plasma chamber 152 for processing the substrate S. An example of the MPS 1514 is provided in U.S. Patent No. 10,264,663, the entire disclosure of which is incorporated herein by reference.

[0393] In some embodiments, the input section 1502 includes a controller board having a signal generator and further includes a gate driver, and the output section includes a half-bridge transistor circuit. The controller board includes a controller connected to the signal generator to control the signal generator to generate a rectangular wave signal at a predetermined frequency.

[0394] The embodiments described herein may be implemented in various computer system configurations including a handheld hardware unit, a microprocessor system, a microprocessor-based or programmable home appliance, a minicomputer, a mainframe computer, and the like. The present embodiments can also be implemented in a distributed computing environment where tasks are performed by remote processing hardware units linked via a network.

[0395] In some embodiments, the controller is part of a system, and the system can be part of the examples described above. Such a system includes a semiconductor processing apparatus that includes one or more processing tools, one or more chambers, one or more processing platforms, and / or specific processing components (such as a wafer pedestal, a gas flow system, etc.). These systems are integrated with electronics for controlling their operation before, during, and after the processing of a semiconductor wafer or substrate. The electronics may also be referred to as a "controller" and may control various components or sub-components of one or more systems. The controller is programmed to control any of the processes disclosed herein, including delivery of process gases, temperature setting (e.g., heating and / or cooling), pressure setting, vacuum setting, power setting, RF generator setting, RF matching circuit setting, frequency setting, flow rate setting, liquid delivery setting, position and motion setting, loading and unloading of wafers to and from the tool, and loading and unloading of wafers to and from other transfer tools and / or load locks connected or interlocked with the system.

[0396] Broadly speaking, in various embodiments, the controller is defined as an electronic device having various integrated circuits, logic, memory, and / or software that receives instructions, issues instructions, controls operations, enables cleaning operations, enables endpoint measurements, etc. The integrated circuits include chips in the form of firmware that stores program instructions, chips defined as DSPs, ASICs, PLDs, and / or one or more microprocessors or microcontrollers that execute program instructions (e.g., software). The program instructions are instructions communicated to the controller in the form of various individual settings (or program files) that define operating variables for performing a specific process on, for, or with respect to a semiconductor wafer. The operating variables are, in some embodiments, part of a recipe defined by a process engineer to achieve one or more processing steps during the manufacture of one or more layers, materials, metals, oxides, silicon, silicon dioxide, surfaces, circuits, and / or dies of a wafer.

[0397] In some embodiments, the controller is part of a computer that is integrated into, connected to, or otherwise network-connected to the system, or is connected to such a computer. For example, the controller is part of the "cloud," i.e., all or part of a fab host computer system, which enables remote access to wafer processing. The computer enables remote access to the system to monitor the current progress of manufacturing operations, investigate the history of past manufacturing operations, investigate trends or performance metrics from multiple manufacturing operations, change variables of the current process, set processing steps to track the current process, or initiate a new process.

[0398] In some embodiments, a remote computer (e.g., a server) provides process recipes to the system via a network, which includes a local network or the Internet. The remote computer includes a user interface that enables input or programming of variables and / or settings, which are then communicated from the remote computer to the system. In some examples, the controller receives instructions in the form of data that specify each variable of the processing steps to be performed during one or more operations. It should be understood that the variables are specific to the type of process being performed and the type of tool that the controller is configured to interface with or control. Thus, as described above, the controller is distributed, such as by including one or more individual controllers that are networked together and operate towards a common purpose such as the processes and controls described herein. An example of a distributed controller for such a purpose is one or more integrated circuits on a chamber that are installed remotely (such as at the platform level or as part of a remote computer) and communicate with one or more integrated circuits that cooperate to control the process in the chamber.

[0399] In various embodiments, examples of systems include, but are not limited to, plasma etching chambers or modules, film deposition chambers or modules, spin rinse chambers or modules, metal plating chambers or modules, cleaning chambers or modules, bevel edge etching chambers or modules, physical vapor deposition (PVD) chambers or modules, chemical vapor deposition (CVD) chambers or modules, atomic layer deposition (ALD) chambers or modules, atomic layer etching (ALE) chambers or modules, ion implantation chambers or modules, track chambers or modules, and any other semiconductor processing system related to or used in the fabrication and / or manufacture of semiconductor wafers.

[0400] In some embodiments, it should be further noted that the operations described above are applicable to various types of plasma chambers, such as plasma chambers including inductively coupled plasma (ICP) reactors, capacitively coupled plasma chambers, transformer coupled plasma chambers, capacitively coupled plasma reactors, conductor tools, dielectric tools, plasma chambers including electron cyclotron resonance (ECR) reactors, and the like.

[0401] As described above, depending on one or more process steps performed by a tool, the controller communicates with one or more of other tool circuits or modules, other tool components, cluster tools, other tool interfaces, adjacent tools, neighboring tools, tools disposed throughout the factory, main computers, other controllers, or tools used for material transport to load and unload a wafer container to and from a tool location and / or load port within a semiconductor manufacturing factory.

[0402] With the above embodiments in mind, it should be understood that some of the present embodiments employ various computer-implemented operations including data stored in a computer system. These operations physically manipulate physical quantities. Any of the operations described herein that form part of the present embodiments are useful mechanical operations.

[0403] Also, some of the present embodiments relate to hardware units or devices for performing these operations. The device is specially made for a dedicated computer. When defined as a dedicated computer, the computer is operable for a special purpose while performing other processes, executing programs, or routines that do not belong to the special purpose.

[0404] In some embodiments, the operations may be processed by a computer selectively activated or configured by one or more computer programs stored in a computer memory, cached, or obtained via a computer network. When data is obtained via a computer network, the data may be processed by other computers on the computer network, such as in a cloud of computing resources.

[0405] One or more embodiments may also be implemented as computer-readable code on a non-transitory computer-readable medium. A non-transitory computer-readable medium is any data storage hardware unit that stores data, such as a memory device, etc., and the data can be read later by a computer system. Examples of non-transitory computer-readable media include hard drives, network attached storage (NAS), ROM, RAM, compact disc ROMs (CD-ROMs), CD recordable (CD-Rs), CD rewritable (CD-RWs), magnetic tape, and other optical and non-optical data storage hardware units. In some embodiments, the non-transitory computer-readable medium includes a computer-readable tangible medium distributed on a network-coupled computer system such that the computer-readable code is stored and executed in a distributed manner.

[0406] Although the method operations have been described in a particular order, it should be understood that in various embodiments, other housekeeping operations are performed between the operations, the method operations are adjusted to occur at slightly different times, are distributed in a system that allows the method operations to occur at various intervals, or are performed in a different order than that described above.

[0407] It should further be noted that in one embodiment, without departing from the scope described in the various embodiments described in this disclosure, one or more features from any of the above-described embodiments may be combined with one or more features of any other embodiment.

[0408] The foregoing embodiments have been described in some detail for the purpose of clarity of understanding. However, it will be apparent that certain changes and modifications can be made within the scope of the appended claims. Accordingly, the embodiments are to be regarded as illustrative rather than restrictive, and the embodiments are not limited to the details given herein, but rather may be modified within the scope of the appended claims and the scope of their equivalents. The present disclosure includes the following application examples. [Application Example 1] A method for controlling a plasma tool, receiving, by a processor, a first set of metric data from the plasma tool; analyzing the first set of metric data to determine a first position and a first time window for capturing a second set of metric data; providing, by the processor, the first position and the first time window to a data processing system of the plasma tool; receiving the second set of metric data captured at the first position and with respect to the first time window; analyzing the second set of metric data to generate variable data; and controlling the plasma tool according to the variable data A method including. [Application Example 2] The method according to Application Example 1, wherein the first time window includes a first time and a second time, and the first position is at the first time. [Application Example 3] The method according to Application Example 2, wherein a third set of metric data outside the first time window is not captured. [Application Example 4] The method according to Application Example 1, wherein the plasma tool includes an RF generator or a matchless plasma source. [Application Example 5] The method according to Application Example 1, wherein analyzing the first set of metric data includes determining whether a portion of the first set of metric data is within a predetermined range; and determining the first position and the first time window where the portion of the first set of metric data is within the predetermined range A method including. [Application Example 6] The method according to Application Example 5, wherein the predetermined range corresponds to a steady state of the portion of the first set of metric data. [Application Example 7] The method according to Application Example 1, wherein analyzing the first set of the metric data comprises determining whether a portion of the first set of the metric data is outside a predetermined range, determining the first position and the first time window where the portion of the first set of the metric data is outside the predetermined range and a method comprising the steps of. [Application Example 8] The method according to Application Example 7, wherein the predetermined range corresponds to a transition state of the portion of the first set of the metric data, and during the transition state, the portion of the first set of the metric data transitions from a first steady state of the first set of the metric data to a second steady state of the first set of the metric data. [Application Example 9] The method according to Application Example 1, wherein the time window defines a state, or a sub-state, or a slice of an RF signal generated by a plasma source of the plasma tool. [Application Example 10] The method according to Application Example 1, wherein analyzing the second set of the metric data to generate the variable data comprises determining a first statistical value from the second set of the metric data, determining the variable data based on the first statistical value and a method comprising the steps of. [Application Example 11] The method according to Application Example 10, receiving a third set of the metric data captured with respect to a second time window at a second position, determining a second statistical value from the third set of the metric data, further comprising wherein analyzing the second set of the metric data to generate the variable data comprises determining whether there is a consensus between the first statistical value and the second statistical value, determining the variable data in response to determining that there is a consensus between the first statistical value and the second statistical value and a method comprising the steps of and a method. [Application Example 12] The method according to Application Example 1, wherein analyzing the second set of the metric data to generate the variable data comprises determining whether the number of samples of the second set of the metric data exceeds a predetermined threshold, determining a statistical value from the second set of the metric data in response to determining that the number of samples of the second set of the metric data exceeds the predetermined threshold Determining the variable data based on the statistical value A method comprising. [Application Example 13] The method according to Application Example 1, further comprising providing, by the processor, a first number of cycles during which the second set of metric data should be collected. [Application Example 14] The method according to Application Example 13, wherein the first number of cycles is 1, analyzing the first set of metric data to determine a second position and a second time window for capturing a third set of metric data; providing, by the processor, the second position and the second time window to the data processing system of the plasma tool; providing, by the processor, a second number of cycles during which the third set of metric data should be collected comprising wherein the second number of cycles follows the first number of cycles, A method. [Application Example 15] The method according to Application Example 1, generating a digital pulse signal; providing, to the data processing system, the digital pulse signal indicating a rate at which a portion of the first set of metric data is sampled further comprising wherein the portion corresponds to a state, or a sub-state, or a slice of the first set of metric data, and the portion forms the second set of metric data, A method. [Application Example 16] The method according to Application Example 1, receiving a digital pulse signal from a plasma source of the plasma tool; providing, to the data processing system, the digital pulse signal indicating a rate at which the second set of metric data is sampled further comprising. [Application Example 17] The method according to Application Example 1, wherein a portion of the first set of metric data is not captured by the data processing system during a period in which the second set of metric data is received by the processor from the data processing system. [Application Example 18] The method according to Application Example 1, further comprising receiving a third set of metric data captured with respect to the first time window at the first position. The third set of metric data is captured during a cycle different from the cycle during which the second set of metric data is captured, and analyzing the second set of metric data to generate the variable data includes comparing the second set and the third set of metric data to identify a discrepancy between the second set and the third set, and generating the variable data to reduce the discrepancy. Method. [Application Example 19] The method according to Application Example 1, further comprising receiving, at the first location and with respect to the first time window, a third set of metric data captured from a second data processing system of a second plasma tool. Analyzing the second set of metric data to generate the variable data includes comparing the second set and the third set of metric data to identify a discrepancy between the second set and the third set, and generating the variable data to reduce the discrepancy. Method. [Application Example 20] The method according to Application Example 1, receiving a third set of metric data from the data processing system, determining whether the third set of metric data includes a greater number of transition states compared to the number of transition states of the second set of metric data, and whether the third set of metric data includes a greater number of steady states compared to the number of steady states of the second set of metric data, in response to determining that the third set of metric data includes the greater number of steady states, comparing the number of sample sets assigned within the second payload of the second packet to each of the steady states of the second set of metric data, and assigning a smaller number of sample sets within the first payload of the first packet to each of the steady states of the third set of metric data. In response to determining that the third set of metric data includes a greater number of transition states, compare the number of sample sets assigned within the second payload of the second packet to each of the transition states of the second set of metric data, and assign a smaller number of sample sets within the first payload of the first packet to each of the transition states of the third set of metric data A method, further comprising [Application Example 21] The method according to Application Example 1, wherein receiving a third set of metric data from the data processing system determining whether the third set of metric data includes a greater amount of data corresponding to the steady state of the second set of metric data as compared to the amount of data corresponding to the steady state in response to determining that the third set of metric data includes the greater amount of data, assign a greater number of packets to the steady state of the third set of metric data as compared to the number of packets assigned within the steady state of the second set of metric data A method, further comprising [Application Example 22] A controller for controlling a plasma tool, comprising receiving a first set of metric data from the plasma tool analyzing the first set of metric data to determine a first position and a first time window used to capture a second set of metric data providing the first position and the first time window to a data processing system of the plasma tool receiving the second set of metric data captured at the first position and with respect to the first time window analyzing the second set of metric data to generate variable data, and controlling the plasma tool according to the variable data a processor configured to a memory device connected to the processor A controller, comprising [Application Example 23] The controller according to Application Example 22, wherein, to analyze the first set of metric data, the processor determines whether a portion of the first set of metric data is within a predetermined range, and Determine the first position and the first time window in which the portion of the first set of metric data is within the predetermined range configured to be wherein the predetermined range corresponds to a steady state of the portion of the first set of metric data Controller [Application Example 24] A controller according to Application Example 22, wherein, in order to analyze the first set of metric data, the processor determines whether a portion of the first set of metric data is outside a predetermined range, and determines the first position and the first time window in which the portion of the first set of metric data is outside the predetermined range configured to be wherein the predetermined range corresponds to a transition state of the portion of the first set of metric data, and during the transition state, the portion of the first set of metric data transitions from a first steady state of the first set of metric data to a second steady state of the first set of metric data Controller [Application Example 25] A plasma source configured to generate a radio frequency (RF) signal, a data processing device, and a controller connected to the data processing device and the plasma source including, wherein the controller receives a first set of metric data related to the RF signal from an RF sensor, analyzes the first set of metric data to determine a first position and a first time window used to capture a second set of metric data, provides the first position and the first time window to the data processing system, receives the second set of metric data captured at the first position and with respect to the first time window, analyzes the second set of metric data to generate variable data, and controls the plasma source according to the variable data configured to be Plasma system [Application Example 26] A plasma system according to Application Example 25, wherein, in order to analyze the first set of metric data, the controller determines whether a portion of the first set of metric data is within a predetermined range, and determines the first position and the first time window in which the portion of the first set of metric data is within the predetermined range configured to be wherein the predetermined range corresponds to a steady state of the portion of the first set of metric data Plasma system [Application Example 27] The plasma system according to Application Example 25, wherein, in order to analyze the first set of metric data, the controller determines whether a portion of the first set of metric data is outside a predetermined range, and determines a first position and a first time window in which the portion of the first set of metric data is outside the predetermined range is configured to wherein the predetermined range corresponds to a transition state of the portion of the first set of metric data, and during the transition state, the portion of the first set of metric data transitions from a first steady state of the first set of metric data to a second steady state of the first set of metric data Plasma system

Claims

1. A method for controlling a plasma tool, comprising: receiving, by a processor, a first set of metric data from the plasma tool; analyzing the first set of metric data to determine a first position and a first time window for capturing a second set of metric data; providing, by the processor, the first position and the first time window to a data processing system of the plasma tool; receiving the second set of metric data captured at the first position and with respect to the first time window; analyzing the second set of metric data to generate variable data; and controlling the plasma tool according to the variable data. A method as described above.

2. The method according to claim 1, wherein the first time window includes a first time and a second time, and the first position is at the first time.

3. The method according to claim 2, wherein a third set of metric data outside the first time window is not captured.

4. The method according to claim 1, wherein the plasma tool includes an RF generator or a matchless plasma source.

5. The method according to claim 1, wherein analyzing the first set of metric data includes: determining whether a portion of the first set of metric data is within a predetermined range; and determining the first position and the first time window when the portion of the first set of metric data is within the predetermined range. A method as described above.

6. The method according to claim 5, wherein the predetermined range corresponds to a steady state of the portion of the first set of metric data.

7. The method according to claim 1, wherein analyzing the first set of metric data includes: determining whether a portion of the first set of metric data is outside a predetermined range; and determining the first position and the first time window when the portion of the first set of metric data is outside the predetermined range. A method as described above.

8. The method according to claim 7, wherein the predetermined range corresponds to a transition state of the portion of the first set of metric data, and during the transition state, the portion of the first set of metric data transitions from a first steady state of the first set of metric data to a second steady state of the first set of metric data.

9. The method according to claim 1, wherein the time window defines a state, or a sub-state, or a slice of an RF signal generated by a plasma source of the plasma tool.

10. The method according to claim 1, wherein generating the variable data by analyzing the second set of metric data comprises: determining a first statistical value from the second set of metric data; and determining the variable data based on the first statistical value.

11. The method according to claim 10, further comprising: receiving a third set of metric data captured for a second time window at a second location; determining a second statistical value from the third set of metric data; wherein generating the variable data by analyzing the second set of metric data comprises: determining whether there is a consensus between the first statistical value and the second statistical value; and determining the variable data in response to determining that there is a consensus between the first statistical value and the second statistical value.

12. The method according to claim 1, wherein generating the variable data by analyzing the second set of metric data comprises: determining whether the number of samples of the second set of metric data exceeds a predetermined threshold; determining a statistical value from the second set of metric data in response to determining that the number of samples of the second set of metric data exceeds the predetermined threshold; and determining the variable data based on the statistical value.

13. The method according to claim 1, further comprising providing, by the processor, a first number of cycles during which the second set of metric data is to be collected.

14. The method according to claim 13, wherein the first number of cycles is 1. Analyzing the first set of metric data to determine a second location and a second time window for capturing a third set of metric data; Providing, by the processor, the second location and the second time window to the data processing system of the plasma tool; Providing, by the processor, a second number of cycles during which the third set of metric data should be collected comprising; wherein the second number of cycles follows the first number of cycles; A method.

15. The method according to claim 1, further comprising: Generating a digital pulse signal; Providing the digital pulse signal indicating a rate at which a portion of the first set of metric data is sampled to the data processing system; further comprising; wherein the portion corresponds to a state, or a sub-state, or a slice of the first set of metric data, and the portion forms the second set of metric data; A method.

16. The method according to claim 1, further comprising: Receiving a digital pulse signal from a plasma source of the plasma tool; Providing the digital pulse signal indicating a rate at which the second set of metric data is sampled to the data processing system; A method.

17. The method according to claim 1, wherein a portion of the first set of metric data is not captured by the data processing system during a period in which the second set of metric data is received by the processor from the data processing system.

18. The method according to claim 1, further comprising: Receiving a third set of metric data captured with respect to the first time window at the first location; wherein the third set of metric data is captured during cycles different from the cycles during which the second set of metric data is captured, and analyzing the second set of metric data to generate the variable data comprises comparing the second set of metric data and the third set of metric data to identify a discrepancy between the second set and the third set, and generating the variable data to reduce the discrepancy; A method.

19. The method according to claim 1, Further comprising receiving, at the first position and with respect to the first time window, a third set of metric data captured from a second data processing system of a second plasma tool, Analyzing the second set of the metric data to generate the variable data includes comparing the second set and the third set of the metric data to identify a discrepancy between the second set and the third set, and generating the variable data to reduce the discrepancy. Method.

20. The method according to claim 1, Receiving a third set of metric data from the data processing system, Determining whether the third set of metric data includes a greater number of transition states compared to the number of transition states of the second set of metric data, and whether it includes a greater number of steady states compared to the number of steady states of the second set of metric data, In response to determining that the third set of metric data includes the greater number of steady states, comparing the number of sample sets assigned in the second payload of the second packet to each of the steady states of the second set of metric data, and assigning a smaller number of sample sets in the first payload of the first packet to each of the steady states of the third set of metric data, In response to determining that the third set of metric data includes the greater number of transition states, comparing the number of sample sets assigned in the second payload of the second packet to each of the transition states of the second set of metric data, and assigning a smaller number of sample sets in the first payload of the first packet to each of the transition states of the third set of metric data Further comprising a method.

21. The method according to claim 1, Receiving a third set of metric data from the data processing system, Determining whether the third set of metric data includes a greater amount of data corresponding to steady states compared to the amount of data corresponding to the steady states of the second set of metric data, In response to determining that the third set of metric data contains more data than that, assign a larger number of packets to the steady state of the second set of metric data compared to the number of packets assigned to the steady state of the second set of metric data The method further comprising.

22. A controller for controlling a plasma tool, Receiving a first set of metric data from the plasma tool, Analyze the first set of metric data to determine a first position and a first time window used to capture a second set of metric data, Provide the first position and the first time window to a data processing system of the plasma tool, Receiving the second set of metric data captured at the first position and with respect to the first time window, Analyze the second set of metric data to generate variable data, and Controlling the plasma tool according to the variable data A processor configured as follows, A memory device connected to the processor A controller comprising.

23. The controller according to claim 22, wherein, in order to analyze the first set of metric data, the processor Determine whether a portion of the first set of metric data is within a predetermined range, and Determine the first position and the first time window in which the portion of the first set of metric data is within the predetermined range Configured as follows, The predetermined range corresponds to a steady state of the portion of the first set of metric data, Controller.

24. The controller according to claim 22, wherein, in order to analyze the first set of metric data, the processor Determine whether a portion of the first set of metric data is outside a predetermined range, and Determine the first position and the first time window in which the portion of the first set of metric data is outside the predetermined range Configured as follows, The predetermined range corresponds to a transition state of the portion of the first set of metric data, and during the transition state, the portion of the first set of metric data transitions from a first steady state of the first set of metric data to a second steady state of the first set of metric data. Controller. Claim 25 A plasma source configured to generate a radio frequency (RF) signal, A data processing device, A controller connected to the data processing device and the plasma source Including, the controller Receives a first set of metric data related to the RF signal from an RF sensor, Analyzes the first set of metric data to determine a first position and a first time window used to capture a second set of metric data, Provides the first position and the first time window to the data processing device, Receives the second set of metric data captured at the first position and with respect to the first time window, Analyzes the second set of metric data to generate variable data, and Controls the plasma source according to the variable data Is configured to Plasma system. Claim 26 The plasma system according to claim 25, wherein, in order to analyze the first set of metric data, the controller Determines whether a portion of the first set of metric data is within a predetermined range, and Determines the first position and the first time window in which the portion of the first set of metric data is within the predetermined range Is configured to The predetermined range corresponds to a steady state of the portion of the first set of metric data. Plasma system. Claim 27 The plasma system according to claim 25, wherein, in order to analyze the first set of metric data, the controller Determines whether a portion of the first set of metric data is outside a predetermined range, and Determines the first position and the first time window in which the portion of the first set of metric data is outside the predetermined range Is configured to The predetermined range corresponds to a transition state of the portion of the first set of metric data, and during the transition state, the portion of the first set of metric data transitions from a first steady state of the first set of metric data to a second steady state of the first set of metric data. Plasma system.

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