Method of estimating the state of a chamber and device therefor

Abstract

The present disclosure discloses a method of estimating a chamber state through a chamber monitoring element. In particular, the method includes obtaining Y reference state data corresponding to Y coordinates in an N-dimensional coordinate system with each of N elements as an axis; generating Y first state similarity data by calculating a similarity between current state data and each of the Y reference data; determining a plurality of second state similarity data of an entire coordinate by performing at least one of interpolation or extrapolation in the N-dimensional coordinate system based on the Y first state similarity data; and estimating a current state of each of the N elements according to a coordinate including a second state similarity data as an estimated state similarity data corresponding to a second state similarity having a maximum value among a plurality of second state similarities included in the plurality of second state similarity data.

Description

Technical Field

[0001] This disclosure generally relates to a method for estimating the internal state of a chamber and an apparatus therefor. More specifically, this disclosure relates to a method for estimating the current values ​​of a plurality of elements that define the internal state of a chamber and an apparatus therefor.

[0002] Furthermore, this disclosure relates to a method and apparatus for improving the estimation accuracy of the current values ​​of multiple elements. Background Technology

[0003] In semiconductor or display manufacturing and inspection processes, it is crucial to ensure that the equipment used in the process is within verified operating ranges and that process conditions are correctly set. However, while the status of an ongoing process can be partially checked by detecting specific physical quantities of plasma, it is extremely difficult to directly inspect the current internal state of a chamber within an ongoing process, such as the temperature or position of a wafer chuck.

[0004] Ultimately, there is no alternative but to perform a test run to check the process results, which leads to additional costs and time. Furthermore, even if the process results are incorrect, it is difficult to pinpoint the cause of the problem.

[0005] Therefore, it is important to estimate the internal state of the chamber, predict that the process results may be incorrect, and accurately identify the causes that may lead to the problem. Summary of the Invention

[0006] This disclosure aims to provide a method that can improve the estimation accuracy of multiple elements that define the internal state of a chamber.

[0007] The technical problems to be solved by this disclosure are not limited to those described above, and those skilled in the art will clearly understand other technical problems not mentioned based on this disclosure.

[0008] According to embodiments of this disclosure, a method for estimating a chamber state using a chamber monitoring element may include: obtaining Y reference state data corresponding to Y coordinates in an N-dimensional coordinate system with each of N elements as an axis, where Y is a natural number equal to or greater than 2 and is a portion of the entire coordinate system that can be represented in the N-dimensional coordinate system, and wherein the N elements are selected from M elements defining the chamber state, where M is a natural number equal to or greater than 1, N is a natural number equal to or greater than 1, and M is equal to or greater than N; transmitting radio waves of a specific frequency range into the interior of the chamber and receiving radio waves reflected from the interior of the chamber; generating current state data representing the chamber state based on the received radio waves; and calculating the relationship between the current state data and each of the Y reference data. The similarity is used to determine Y first state similarities; Y first state similarity data are generated by mapping the Y first state similarities to the Y coordinates; multiple second state similarity data for the entire coordinate are determined by performing at least one of interpolation or extrapolation in an N-dimensional coordinate system based on the Y first state similarity data, wherein each of the multiple second state similarity data includes multiple second state similarities for each of the entire coordinate; the second state similarity data corresponding to the second state similarity data that has the maximum value among the multiple second state similarities included in the multiple second state similarity data is determined as estimated state similarity data; and the current state of each of the N elements is estimated based on the coordinates included in the estimated state similarity data.

[0009] A cavity monitoring element for estimating the state of a cavity according to this disclosure may include: an antenna configured to transmit radio waves within a specific frequency range into the interior of the cavity and receive radio waves reflected from the interior of the cavity; a bracket configured to fix the antenna to the exterior or interior of the cavity; a signal processor configured to apply an electrical signal to the antenna and obtain an electrical signal from the antenna; and a controller configured to control the signal processor and generate state data of the cavity based on the obtained electrical signal, wherein the controller is configured to: obtain Y reference state data corresponding to Y coordinates in an N-dimensional coordinate system with each of N elements as axes, where Y is a natural number equal to or greater than 2 and is a portion of the entire coordinate system that can be represented in the N-dimensional coordinate system, and wherein the N elements are selected from M elements defining the state of the cavity, where M is a natural number equal to or greater than 1, N is a natural number equal to or greater than 1, and M is equal to or greater than N; control the signal processor to transmit radio waves within a specific frequency range into the interior of the cavity and receive radio waves reflected from the interior of the cavity. The system receives radio waves reflected from the chamber and obtains electrical signals based on the received radio waves; generates current state data representing the state of the chamber based on the received radio waves; determines Y first state similarities by calculating the similarity between the current state data and each of Y reference data; generates Y first state similarity data by mapping the Y first state similarities to the Y coordinates; determines multiple second state similarity data for the entire coordinate system by performing at least one of interpolation or extrapolation in an N-dimensional coordinate system based on the Y first state similarity data, wherein each of the multiple second state similarity data includes multiple second state similarities for each of the entire coordinate system; determines the second state similarity data corresponding to the second state similarity data that has the maximum value among the multiple second state similarities included in the multiple second state similarity data as estimated state similarity data; and estimates the current state of each of the N elements based on the coordinates included in the estimated state similarity data.

[0010] According to this disclosure, the accuracy of estimating the internal state of a cavity can be improved by estimating the internal state of the cavity.

[0011] According to this disclosure, the internal state of a chamber can be accurately estimated even using a relatively small amount of reference state data.

[0012] The technical problems to be solved by this disclosure are not limited to those described above, and those skilled in the art will clearly understand other technical problems not mentioned based on this disclosure. Attached Figure Description

[0013] Figure 1 This is a block diagram of the monitoring element according to an embodiment.

[0014] Figure 2 and Figure 3 This is a schematic diagram of a monitoring element installed in a chamber according to an embodiment.

[0015] Figure 4 It is a graph of the S11 parameters as an instance of state data.

[0016] Figure 5 This is a flowchart illustrating a method for generating reference state data according to an embodiment of the present disclosure.

[0017] Figure 6 It is a method for calculating the similarity between reference state data and state data, and a method for estimating the internal state of a cavity based on the similarity.

[0018] Figure 7 Intended to show Figure 6 The problem lies in the method for estimating the internal state of the chamber described in [the document].

[0019] Figures 8 to 19 A method for improving the estimation accuracy of the internal state of a cavity is shown according to an embodiment of the present disclosure.

[0020] Figure 20 and Figure 21 Methods for performing interpolation and extrapolation according to embodiments of the present disclosure are shown.

[0021] Figure 22 and Figure 23 This is a diagram illustrating how the estimation accuracy increases as the dimension of the coordinate system increases, according to an embodiment of the present disclosure.

[0022] Figure 24 This is a block diagram of a monitoring system according to an embodiment.

[0023] Figure 25 This is a schematic diagram of a monitoring system installed in a process equipment according to an embodiment. Detailed Implementation

[0024] The embodiments described in this disclosure are intended to clearly illustrate the ideas of this disclosure to those skilled in the art to which this disclosure pertains. Therefore, this disclosure is not limited to the embodiments described in this disclosure, and the scope of this disclosure should be interpreted to include various modifications or variations within the spirit of this disclosure.

[0025] As used in this disclosure, commonly used terms are employed in consideration of the functionality of this disclosure. However, the terms may vary depending on the intent of those skilled in the art, precedent, or the emergence of new technologies. In contrast, the meaning of a term is explained when a specific term is defined as having an optional meaning. Therefore, the terms used in this disclosure should be interpreted based on their actual meaning throughout the disclosure and its details, and not merely on their names.

[0026] The accompanying drawings are provided for ease of illustration of this disclosure, and the shapes shown in the drawings may be exaggerated to aid in understanding this disclosure; therefore, this disclosure is not limited to the drawings.

[0027] In this disclosure, if a detailed description of a known configuration or function related to this disclosure would obscure the subject matter of this disclosure, it will not be repeated. Furthermore, throughout this disclosure, unless otherwise stated, the terms "first," "second," etc., are used only to distinguish one element from another.

[0028] According to this disclosure, a monitoring element can be provided. The monitoring element transmits radio waves into a cavity of process equipment, such as semiconductor process equipment and display process equipment, and receives radio waves reflected from the internal space of the cavity, thereby monitoring the geometry of the internal space of the cavity. More specifically, the cavity includes multiple components, such as a lower electrode on which a substrate (e.g., a wafer) is placed, an upper electrode facing the lower electrode, pins for supporting the substrate, and baffles. The geometry of the cavity can be defined by a combination of the geometries (e.g., positions or shapes) of the corresponding components.

[0029] In this paper, even if the same radio waves are emitted into the cavity, the received radio waves can vary depending on the geometry of the cavity. For example, if the geometry of a part of the component changes (e.g., the position or shape of the part of the component changes), the received radio waves after the change may differ from those received before the change, even if the same radio waves are emitted into the cavity. That is, how radio waves are reflected by the internal space of the cavity can vary depending on the geometry of the cavity. In other words, the received reflected waves can reflect the geometry of the cavity.

[0030] Alternatively, for example, the load inside the chamber can be varied as plasma is generated inside, or the environment inside the chamber can be varied for each process cycle. In this paper, monitoring elements can monitor electrical / physical characteristics based on the varying load or environment inside the chamber.

[0031] For example, the environment inside a wafer chuck can change as the temperature, height, and position of the chuck change during the process within the chamber. In this case, even if the same radio waves are emitted into the chamber, the received radio waves after the change may differ from those received before the change. That is, the way radio waves are reflected inside the chamber can vary depending on the physical / electrical state of the chamber. In other words, the received reflected waves can reflect the physical / electrical state of the chamber.

[0032] Therefore, monitoring elements can monitor chambers where processes are not in progress (as well as chambers where processes are in progress). For example, monitoring elements can monitor the geometry of the internal space of a chamber to monitor chambers where processes are not in progress, such as determining the assembly status of process equipment during manufacturing, or determining the outcome of preventive maintenance (PM) of process equipment. As another example, monitoring elements monitor the geometry of the internal space of a chamber to monitor chambers where processes are in progress, such as performing a process while checking that each process step is proceeding normally, or predicting the timing of preventive maintenance.

[0033] As described above, the components and methods disclosed herein for monitoring chamber status monitor whether the equipment is correctly assembled before the start of a process, or whether the equipment is in normal condition between and during processes. That is, the objects to be monitored by the components and methods disclosed herein may include the geometry of the components inside the chamber, the wear level of each component, the relative positional relationship between the components, and unnecessary deposits of byproducts generated during the process of the target substrate passing through the chamber on the inner wall of the chamber and the surfaces of the components inside the chamber.

[0034] On the other hand, the object to be monitored by the components and methods disclosed herein may not include the material and energy state supplied to the chamber to be monitored (e.g., active material, etching gas, inert gas flowing into the chamber to perform the necessary process, radio frequency (RF) power or its plasma, etc.).

[0035] According to embodiments of this disclosure, a method for estimating a chamber state using a chamber monitoring element may include: obtaining Y reference state data corresponding to Y coordinates in an N-dimensional coordinate system with each of N elements as an axis, where Y is a natural number equal to or greater than 2 and is a portion of the entire coordinate system that can be represented in the N-dimensional coordinate system, and wherein the N elements are selected from M elements defining the chamber state, where M is a natural number equal to or greater than 1, N is a natural number equal to or greater than 1, and M is equal to or greater than N; transmitting radio waves of a specific frequency range into the interior of the chamber and receiving radio waves reflected from the interior of the chamber; generating current state data representing the chamber state based on the received radio waves; and calculating the relationship between the current state data and each of the Y reference data. The similarity is used to determine Y first state similarities; Y first state similarity data are generated by mapping the Y first state similarities to the Y coordinates; multiple second state similarity data for the entire coordinate are determined by performing at least one of interpolation or extrapolation in an N-dimensional coordinate system based on the Y first state similarity data, wherein each of the multiple second state similarity data includes multiple second state similarities for each of the entire coordinate; the second state similarity data corresponding to the second state similarity data that has the maximum value among the multiple second state similarities included in the multiple second state similarity data is determined as estimated state similarity data; and the current state of each of the N elements is estimated based on the coordinates included in the estimated state similarity data.

[0036] In this document, obtaining Y reference state data may include: obtaining the Y reference state data by performing a first operation on each of the Y coordinates, wherein the first operation includes: manually adjusting the N elements to correspond to one of the Y coordinates; transmitting radio waves of a specific frequency range into the interior of the chamber and receiving radio waves reflected from the interior of the chamber; and generating reference state data representing the state of the chamber based on the received radio waves.

[0037] Furthermore, the remaining elements among the M elements, excluding the N elements, may not be manually adjusted.

[0038] Furthermore, the plurality of second state similarities can be determined as the similarity between the current state data and the state of the chamber when N elements have values ​​corresponding to one of the entire coordinates.

[0039] Furthermore, determining multiple second-state similarity data may include performing at least one of interpolation or extrapolation using a function of dimension Z or greater than Z, where Z is a natural number equal to or greater than 0.

[0040] Furthermore, the Y coordinates can be selected such that the interval between adjacent coordinates in the N-dimensional coordinate system is constant.

[0041] Furthermore, the Y coordinates can be randomly selected in an N-dimensional coordinate system.

[0042] Furthermore, the Y coordinates can be selected in an N-dimensional coordinate system according to a pre-configured pattern.

[0043] Furthermore, N can be a natural number equal to or greater than 2, and the N elements are selected such that the value of one of the N elements changes by a first ratio, and at least one of the remaining N elements can change by a second ratio.

[0044] A cavity monitoring element for estimating the state of a cavity according to this disclosure may include: an antenna configured to transmit radio waves within a specific frequency range into the interior of the cavity and receive radio waves reflected from the interior of the cavity; a bracket configured to fix the antenna to the exterior or interior of the cavity; a signal processor configured to apply an electrical signal to the antenna and obtain an electrical signal from the antenna; and a controller configured to control the signal processor and generate state data of the cavity based on the obtained electrical signal, wherein the controller is configured to: obtain Y reference state data corresponding to Y coordinates in an N-dimensional coordinate system with each of N elements as axes, where Y is a natural number equal to or greater than 2 and is a portion of the entire coordinate system that can be represented in the N-dimensional coordinate system, and wherein the N elements are selected from M elements defining the state of the cavity, where M is a natural number equal to or greater than 1, N is a natural number equal to or greater than 1, and M is equal to or greater than N; control the signal processor to transmit radio waves within a specific frequency range into the interior of the cavity and receive radio waves reflected from the interior of the cavity. The system receives radio waves reflected from the chamber and obtains electrical signals based on the received radio waves; generates current state data representing the state of the chamber based on the received radio waves; determines Y first state similarities by calculating the similarity between the current state data and each of Y reference data; generates Y first state similarity data by mapping the Y first state similarities to the Y coordinates; determines multiple second state similarity data for the entire coordinate system by performing at least one of interpolation or extrapolation in an N-dimensional coordinate system based on the Y first state similarity data, wherein each of the multiple second state similarity data includes multiple second state similarities for each of the entire coordinate system; determines the second state similarity data corresponding to the second state similarity data that has the maximum value among the multiple second state similarities included in the multiple second state similarity data as estimated state similarity data; and estimates the current state of each of the N elements based on the coordinates included in the estimated state similarity data.

[0045] In this document, the controller may be configured to obtain Y reference state data by performing a first operation on each of the Y coordinates, wherein the first operation may include: manually adjusting the N elements to correspond to one of the Y coordinates; transmitting radio waves of a specific frequency range into the interior of the chamber and receiving radio waves reflected from the interior of the chamber; and generating reference state data representing the state of the chamber based on the received radio waves.

[0046] Furthermore, the remaining elements among the M elements, excluding the N elements, may not be manually adjusted.

[0047] Furthermore, the plurality of second state similarities can be determined as the similarity between the current state data and the state of the chamber when N elements have values ​​corresponding to one of the entire coordinates.

[0048] Furthermore, the controller can be configured to perform at least one of interpolation or extrapolation using a function of dimension Z or greater than Z, where Z can be a natural number equal to or greater than 0.

[0049] Furthermore, the Y coordinates can be selected such that the interval between adjacent coordinates in the N-dimensional coordinate system can be constant.

[0050] Furthermore, the Y coordinates can be randomly selected in an N-dimensional coordinate system.

[0051] Furthermore, the Y coordinates can be selected in an N-dimensional coordinate system according to a pre-configured pattern.

[0052] Furthermore, N can be a natural number equal to or greater than 2, and the N elements can be selected such that the value of one of the N elements changes by a first ratio, and at least one of the remaining N elements can change by a second ratio.

[0053] [Definitions of terms used in this disclosure]

[0054] Meanwhile, the terminology used in describing the embodiments of this disclosure can be defined as follows.

[0055] (1) Status data

[0056] It can be a set of parameters reflecting the geometric, electrical, and / or physical state of the cavity. For example, parameters that can be used as state data may be i) S-parameters, ii) H-parameters, iii) Y-parameters, iv) Z-parameters, v) combinations of at least two parameters selected from S-parameters, H-parameters, Y-parameters, and Z-parameters, vi) parameters derived from S-parameters, H-parameters, Y-parameters, and Z-parameters, or vii) parameters derived from combinations of at least two parameters selected from S-parameters, H-parameters, Y-parameters, and Z-parameters. The monitoring element measures the frequency characteristics of the cavity, derives the parameter set, and can use the parameter set to determine the state of the cavity.

[0057] (2) Elements

[0058] As used in this disclosure, "element" can refer to an element that defines the geometric, electrical, and / or physical state of a cavity. In other words, an element can refer to an element capable of altering the state inside a cavity. For example, elements that can alter and define the electrical and / or physical state inside a cavity may include wafer chuck height, wafer chuck temperature, cavity wall temperature, edge ring height, gate valve position, flow rate and pressure of gas supplied to the cavity, radio frequency (RF) power and RF frequency supplied to the cavity, wafer chuck direct current (DC) bias, slot valve position, wafer loading, and byproduct deposition thickness on the cavity wall, etc.

[0059] In addition, for example, elements that can change the geometry of the cavity and define the geometry of the cavity may include the position and shape of multiple components, such as a lower electrode on which a substrate (e.g., a wafer) is placed, an upper electrode facing the lower electrode, a pin for supporting the substrate, and a baffle, as described above.

[0060] (3) Coordinate system

[0061] As described below, the monitoring element and / or monitoring system can select N elements from at least some of M elements that define the internal state of the chamber. In this case, the monitoring element or monitoring system can form a virtual coordinate system with each of the N axes as an axis. That is, in this disclosure, a coordinate system refers to a virtual coordinate system with N axes, where each of the N selected elements serves as an axis. Therefore, the coordinate system can be N-dimensional. For example, if only one of the M elements is selected, the coordinate system has only one axis and is a one-dimensional coordinate system. As another example, if two of the M elements are selected, the coordinate system can have two axes and is a two-dimensional coordinate system.

[0062] However, since these coordinate systems are virtual coordinate systems, they may not be visually representable. That is, in this disclosure, coordinate systems are defined for the purpose of illustrating the ideas of this disclosure. For example, monitoring elements and / or monitoring systems can map each axis of a coordinate system to coordinates of each coordinate system and store them in tabular form. Furthermore, as another example, monitoring elements and / or monitoring systems can be stored in list form by mapping elements indicating each axis of a coordinate system to coordinates of each coordinate system.

[0063] In other words, in this disclosure, a coordinate system is not a coordinate system in which the N axes, each of the N elements, must be orthogonal, but any form in which the values ​​of the N elements are mapped to each other can be called a coordinate system.

[0064] (4) Coordinates

[0065] Coordinates can refer to a set of values ​​for each of the N selected elements. For example, when N1, N2, N3, N4, and N5 are chosen to form a five-dimensional coordinate system, the coordinates can be represented as V1, V2, V3, V4, and V5. In this case, V1 can be a value on the N1 axis, V2 can be a value on the N2 axis, V3 can be a value on the N3 axis, V4 can be a value on the N4 axis, and V5 can be a value on the N5 axis.

[0066] In other words, just as a coordinate system is not necessarily visually representable, coordinates should not be interpreted as limited to specific points that can be indicated in N-dimensional space. That is, coordinates should be interpreted as a set of values ​​corresponding to each axis in the coordinate system.

[0067] (5) State similarity data

[0068] In this disclosure, state similarity data includes coordinates and state similarity. State similarity is the similarity calculated between reference state data and current state data. Furthermore, the coordinates are the coordinates of the reference state data used to calculate the similarity, and are a set of values ​​of elements adjusted when the reference state data was generated. In other words, state similarity data includes information about the similarity between the internal state of the chamber and the current internal state of the chamber at the corresponding coordinates.

[0069] [Monitoring element according to embodiments of this disclosure]

[0070] Figure 1 This is a block diagram illustrating a monitoring element according to an embodiment. (Refer to...) Figure 1 The monitoring element 100 may include an antenna 110, a signal processing unit 120, a communication unit 130, a control unit 140, and a storage unit 150.

[0071] Monitoring element 100 can transmit and receive radio waves via antenna 110. Antenna 110 can receive electrical signals to transmit radio waves. Antenna 110 can receive radio waves and convert them into electrical signals. Monitoring element 100 may include one antenna 110. Alternatively, monitoring element 100 may include two or more antennas 110. In this case, one or some of the two or more antennas 110 can be used to transmit radio waves, while the others can be used to receive radio waves. Alternatively, each of the two or more antennas 110 can be used to transmit and receive radio waves at different locations.

[0072] The monitoring element 100 can apply an electrical signal to the antenna 110 and receive an electrical signal from the antenna 110 via the signal processing unit 120. The signal processing unit 120 can apply an electrical signal within a specific frequency range to the antenna 110. The signal processing unit 120 can receive an electrical signal within a specific frequency range from the antenna 110. More specific details about this operation will be provided later.

[0073] The monitoring element 100 can generate status data via the signal processing unit 120. More details about this operation will be explained later.

[0074] The monitoring element 100 can communicate with the outside world through the communication unit 130. For example, the communication unit 130 can transmit status data and monitoring information to the outside world.

[0075] The communication unit 130 can implement wired or wireless communication. The communication unit 130 may be, for example, a wired / wireless local area network (LAN) module, a wide area network (WAN) module, an Ethernet module, a Bluetooth module, a Zigbee module, a universal serial bus (USB) module, an Institute of Electrical and Electronics Engineers (IEEE) 1394 module, a wireless fidelity (Wi-Fi) module, an Ether-CAT module, a component network module, or a combination thereof, but is not limited to these.

[0076] The monitoring element 100 can generate monitoring information via the control unit 140. The control unit 140 can generate monitoring information based on status data. More details about this operation will be explained later.

[0077] Control unit 140 may be implemented as a computer or similar element, depending on hardware, software, or a combination thereof. At the hardware level, control unit 140 may be one or more processors. Alternatively, control unit 140 may be configured as multiple processors that are physically spaced apart from each other and cooperate through communication. Control unit 140 may be, for example, a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a state machine, a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), a radio frequency integrated circuit (RFIC), or a combination thereof, but is not limited thereto. At the software level, control unit 140 may be provided in the form of a program that drives control unit 140 as hardware.

[0078] Furthermore, the operation of all embodiments described in this disclosure can be controlled and executed by the control unit 140. For example, the operation of at least one of embodiments 1 to 5 described in this disclosure can be executed under the control of the control unit 140. In other words, the control unit 140 can control the overall operation of the monitoring element 100.

[0079] The monitoring element 100 can store various types of data and programs in the storage unit 150. For example, the storage unit 150 can store status data generated by the signal processing unit 120. As another example, the storage unit 150 can store monitoring information generated by the control unit 140.

[0080] Storage cell 150 may be, for example, non-volatile semiconductor memory, hard disk, flash memory, solid-state drive (SSD), random-access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), other types of tangible non-volatile recording media, or combinations thereof, but is not limited thereto.

[0081] The monitoring element 100 may further include a fixing part 160. The fixing part 160 can fix the antenna 110 at a location near the chamber. For example, the fixing part 160 can fix the antenna 110 such that the antenna 110 is spaced apart from the chamber by a predetermined distance. The predetermined distance may be, for example, 1 mm, 3 mm, 5 mm, 7 mm, or 1 cm, but is not limited thereto. As another example, the fixing part 160 can fix the antenna 110 such that the antenna 110 is in contact with the chamber. The fixing part 160 may be, for example, a bracket, but is not limited thereto.

[0082] The monitoring element 100 may further include an output section 170. For example, the output section 170 may be a display. The monitoring element 100 can display monitoring information via the display. As another example, the output section 170 may be a speaker. The monitoring element 100 can output an alarm via the speaker.

[0083] The monitoring element 100 may further include an electromagnetic wave shield 180. The electromagnetic wave shield 180 prevents the antenna 110 from being affected by external electromagnetic waves, or reduces said influence. For example, the electromagnetic wave shield 180 may be disposed outside the chamber to surround the antenna 110. The electromagnetic wave shield 180 may be provided with various materials capable of shielding electromagnetic waves.

[0084] An integrated monitoring element 100 can be provided. For example, the monitoring element 100 can be provided in a form in which the antenna 110, signal processing unit 120, communication unit 130, control unit 140, storage unit 150 and fixing part 160 are integrated.

[0085] Alternatively, the monitoring element 100 can be configured as a separate component. For example, the monitoring element 100 can be configured such that the antenna 110 is separate from other components.

[0086] Not Figure 1 All components shown are necessary components of the monitoring element and can be omitted. Figure 1 The monitoring element may include at least one or more components. Furthermore, the monitoring element may further include... Figure 1 Components not shown in the diagram.

[0087] Monitoring elements can be achieved using network analyzers such as vector network analyzers (VNAs).

[0088] For example, signal processing units, communication units, control units, and storage units can be implemented using a network analyzer.

[0089] As another example, a network analyzer can be used to achieve the signal processing unit. In this case, in addition to the network analyzer, the monitoring element may also include additional elements for achieving the communication unit, control unit, and storage unit.

[0090] The monitoring element can be installed in the chamber.

[0091] Figure 2 and Figure 3 This is a schematic diagram showing a monitoring element installed in a chamber according to an embodiment.

[0092] Reference Figure 2 The antenna can be located outside the cavity 10. For example, the antenna can be located outside the viewport 11 formed in the cavity 10.

[0093] The antenna can be mounted outside the cavity 10 via a fixing part. For example, the antenna can be mounted outside the cavity 10 via a fixing part such that the antenna and the cavity 10 are spaced apart by a predetermined distance. As another example, the antenna can be mounted outside the cavity 10 via a fixing part such that the antenna and the cavity 10 are in contact with each other.

[0094] Although not shown in the figure, the antenna can also be located inside the cavity. For example, the antenna can be located inside the viewport formed in the cavity. The antenna can be mounted inside the cavity via a mounting component. However, when the antenna is located inside the cavity, the cavity may become contaminated or the antenna may be damaged during the manufacturing process, which is disadvantageous compared to positioning the antenna outside the cavity.

[0095] Reference Figure 3 In the case of an integrated monitoring element 100, the monitoring element 100 can be used by being mounted into the chamber 10. For example, this can mean that all components of the monitoring element 100 are manufactured as inseparable, such that the monitoring element 100 is attached as a whole to the outside of the chamber.

[0096] In the case of a detachable monitoring element, the monitoring element may be used in a form in which only one or some components of the monitoring element are mounted to a chamber while other components are connected to said components mounted to the chamber via wires. For example, the monitoring element may be used in a form in which an antenna is mounted to the chamber and other components are connected to said antenna via wires. The connecting wires may be, for example, coaxial cables. For example, in the case of a detachable monitoring element, it may mean that only some components (e.g., the antenna) are attached to the outside of the chamber, while the remaining components are detachable from said partial components and can be wired or wirelessly connected to said partial components. That is, in the case of a detachable monitoring element, it may mean that at least a portion of the components of the monitoring element are designed to be detachable, and the components are designed to be assemblable depending on the purpose of use.

[0097] In this context, "assembly-friendly" can mean that some components and the remaining components are assembled to be directly connected without the need for connecting wires such as coaxial cables. Furthermore, as mentioned above, some components and the remaining components can be wired or wirelessly connected via connecting wires. For example, if some components and the remaining components are wirelessly connected, each of the some components and the remaining components may further include a wireless communication unit for wireless communication.

[0098] Referenced Figure 2 and Figure 3 The description explains that the antenna is positioned corresponding to a viewport, but in addition to the viewport, the antenna can also be positioned corresponding to an area of ​​the cavity that is penetrated by radio waves, such as ceramic. For example, in addition to the existing viewport, an additional port for mounting the antenna is formed in the cavity, and the antenna can be positioned corresponding to said additional port.

[0099] In addition, it has been referred to Figure 2 and Figure 3 The monitoring element is described as including one antenna, but as mentioned above, the monitoring element may include two or more antennas. In this case, one or some of the two or more antennas may be installed in one area of ​​the chamber, while the others may be installed in another area of ​​the chamber.

[0100] [Methods for generating status data by monitoring components]

[0101] The monitoring element can generate status data.

[0102] The status data can be correlated with radio waves incident from the antenna into the cavity (hereinafter referred to as "incident waves") and radio waves reflected from the interior space of the cavity and received by the antenna (hereinafter referred to as "reflected waves"). The status data can also be correlated with the voltage applied to the antenna and the voltage output from the antenna.

[0103] Status data can correspond to a specific frequency range. Status data can be generated for a specific frequency range.

[0104] The incident and reflected waves can be used to define the state data. For example, the ratio between the incident and reflected waves (e.g., the ratio of the reflected wave to the incident wave) can be used to define the state data. The state data can be, for example, S-parameters, H-parameters, Y-parameters, Z-parameters, or parameters calculated therefrom, but is not limited to these.

[0105] In some embodiments, the status data may be S-parameters.

[0106] In some other embodiments, the state data may be an H parameter.

[0107] In some other embodiments, the state data may be the Y parameter.

[0108] In some other embodiments, the state data may be a Z parameter.

[0109] In some other embodiments, the state data may be parameters derived from at least one of a group consisting of S-parameters, H-parameters, Y-parameters, and Z-parameters.

[0110] In addition, in some other embodiments, the state data may be a combination of at least two parameters selected from a group consisting of S-parameters, H-parameters, Y-parameters, and Z-parameters.

[0111] In addition, in some other embodiments, the state data may be parameters derived from a combination of at least two parameters from a group consisting of freely selected S-parameters, H-parameters, Y-parameters, and Z-parameters.

[0112] That is, the state data can be i) S parameter, ii) H parameter, iii) Y parameter, iv) Z parameter, v) a combination of at least two parameters selected from the group consisting of S parameter, H parameter, Y parameter and Z parameter, vi) a parameter derived from S parameter, H parameter, Y parameter and Z parameter, or vii) a parameter derived from a combination of at least two parameters selected from the group consisting of S parameter, H parameter, Y parameter and Z parameter.

[0113] For example, state data can be represented as the following n×2 matrix.

[0114] (First frequency) (Magnitude of reflected wave / Magnitude of incident wave)

[0115] (Second frequency) (Magnitude of reflected wave / Magnitude of incident wave) ...

[0117] (nth frequency) (magnitude of reflected wave / magnitude of incident wave)

[0118] As another example, state data can be represented as the following n×3 matrix.

[0119] (First frequency) (Magnitude of incident wave) (Magnitude of reflected wave)

[0120] (Second frequency) (Magnitude of incident wave) (Magnitude of reflected wave) ...

[0122] (nth frequency) (magnitude of incident wave) (magnitude of reflected wave)

[0123] Here, n is the number of frequencies of the measurement state data, the first frequency is the lower limit of the frequency of the measurement state data, the nth frequency is the upper limit of the frequency of the measurement state data, and the first to nth frequencies are the frequency range of the measurement state data.

[0124] Simultaneously, when monitoring element 100 measures status data, the status data can be measured by transmitting radio waves corresponding to each of the first to nth frequencies at least once. For example, parameters are measured while transmitting the first frequency wave m times, parameters are measured while transmitting the second frequency wave m times, and so on, until the parameters are measured while transmitting the nth frequency wave m times. In this document, during the m transmissions, the intensity of the radio waves at the first to nth frequencies transmitted each time may be different or the same.

[0125] As another example, parameters are measured while transmitting at frequencies from the first to the nth frequency once, and then again while transmitting at frequencies from the first to the nth frequency once more, and so on, until parameters are measured while transmitting at frequencies from the first to the nth frequency m times. In this paper, for each transmission, the intensity of the radio waves at each transmitted frequency may be different or the same.

[0126] Here, n can be determined based on the resolution of the frequency to be measured (i.e., the interval between frequencies). For example, when measuring state data between 3 GHz and 8.5 GHz, when n is 55, the frequency response can be measured in units of 0.1 GHz. As another example, when n is 11, the frequency response can be measured in units of 0.5 GHz.

[0127] State data may include parameter values ​​for a specific frequency range. In the example above, (size of reflected wave / size of incident wave), (size of incident wave), and (size of reflected wave) may be parameter values. The number of parameter values ​​included in the state data may be, for example, at least 500, 1000, 1500, or 2000, but is not limited to these. Regarding state data, multiple state data entries belonging to a specific frequency range may include multiple peaks belonging to that specific frequency range. The number of peaks included in the state data may be, for example, at least 5, 10, 20, 50, or 100, but is not limited to these.

[0128] Status data can correspond to a specific point in time. Status data can be generated at a specific point in time. For example, the specific point in time could be a point in time when the process is not in progress, such as the point in time when the assembly of the process equipment is completed during equipment manufacturing, or the point in time when preventative maintenance of the process equipment is completed. As another example, the specific point in time could be a point in time when the process is in progress, such as the point in time at a specific process step.

[0129] Figure 4 This is a graph showing the S11 parameters as an instance of state data. Figure 4 The S11 parameters are shown in decibels (dB) over the frequency range of 3 GHz to 8.5 GHz. Figure 4In the study, dozens of peaks were found, but the number of peaks can vary depending on the criteria used to count them. For example, in... Figure 4 In this context, peak values ​​are used to distinguish the characteristics or patterns of state data, and the standard can vary depending on the purpose. For example, a peak value can be defined as the radio strength in decibels (dB) that is greater than or equal to a certain level in each frequency range, and can refer to the frequency at which the radio strength in the previous frequency range increases or decreases by a specific amount or exceeds said specific amount compared to the radio strength in the current frequency range. Furthermore, a peak value can refer to the frequency at which the degree of change in the radio strength in the previous frequency range compared to the radio strength in the current frequency range (i.e., the slope of the graph) increases or decreases by a specific amount or exceeds said specific amount.

[0130] Status data can reflect the geometric state of a chamber. For example, when the geometry of a component (e.g., the position or shape of a component within a chamber) changes, the changed status data may differ from the original status data. As another example, status data in cases where some components are damaged may differ from status data in cases where they are not damaged. As yet another example, status data in cases where foreign objects are present may differ from status data in cases where no foreign objects are present within the chamber.

[0131] State data can also reflect the electrical state of a chamber. For example, since conductivity, dielectric constant, and other properties vary depending on the material properties of the chamber or component, state data can reflect the electrical state of the chamber. As another example, when a polymer film or the like is formed on the inner wall of a chamber as the process proceeds, the dielectric constant of the wall changes, and therefore the state data can reflect the electrical state of the chamber.

[0132] That is, when the process cycle is repeated, the state data can change according to the process state within the chamber. For example, even if the state data measured in the first process state and the state data measured in the second process state of the process cycle do not change in terms of the position or shape of the components included in the chamber, the electrical state within the chamber can change with the change of process state.

[0133] According to an embodiment, the monitoring element can transmit radio waves of every frequency within a specific frequency range into the cavity and receive radio waves reflected from the cavity to generate status data. For example, the monitoring element can transmit radio waves of a first frequency into the cavity and receive radio waves reflected from the cavity to generate a first parameter value, and transmit radio waves of a second frequency into the cavity and receive radio waves reflected from the cavity to generate a second parameter value. By performing this procedure across the entire frequency range, the monitoring element can generate status data corresponding to a specific frequency range.

[0134] [Example 1: Method for generating reference state data]

[0135] To monitor a chamber, a chamber in a process state (e.g., an idle state) may exist as a reference for chamber monitoring, and the chamber in the current process state can be monitored by comparing the reference chamber in the process state with the chamber in the current process state. In this way, the process state of the chamber serving as the reference for chamber monitoring can be referred to as the reference state.

[0136] For example, the reference state could be the golden chamber state. As another example, the reference state could be the process state of a chamber of interest to the user. The chamber of interest could be, for example, a chamber in a well-assembled state, a chamber that has undergone preventative maintenance, a chamber with good process results, a chamber in a poor condition, a chamber requiring preventative maintenance, or a chamber in an accidental state. As another example, the process state of a chamber of interest to the user could refer to a state in which at least one of the elements defining the internal state of the chamber is manipulated by the user. For example, the process state of a chamber of interest to the user could be the internal state of a chamber arbitrarily created by the user through manipulation of the wafer chuck temperature and height.

[0137] The monitoring element can generate state data of the chamber as a reference state (hereinafter referred to as "reference state data").

[0138] Figure 5 This is a flowchart of a method for generating reference state data according to an embodiment.

[0139] Reference Figure 5 In S501, the monitoring element 100 can select a specific element from among the M elements that can define the interior of the chamber. Furthermore, in S503, a chamber with an artificially adjusted internal state can be prepared by artificially adjusting the internal state of the chamber, so that the specific element has a specific coordinate.

[0140] However, it may not be necessary to select only one specific element from the M elements. For example, the monitoring element 100 may select N elements as at least some of the M elements (i.e., N is greater than or equal to 1), and the internal state of the chamber may be manually adjusted to have specific coordinates of the N elements. However, to aid in understanding the explanation, the case of N=1 will be described first, and embodiments of the case of N>1 will be described in detail later.

[0141] Furthermore, if a specific selected element is manually changed, the remaining M-1 elements can also be changed. That is, the M elements defining the internal state of the chamber may not be able to change completely independently. For example, when the temperature of the wafer chuck is manually adjusted, the height of the wafer chuck can also be changed. However, since the height of the wafer chuck naturally changes with the temperature of the wafer chuck, the relationship between these factors can be ignored. In other words, the remaining elements are assumed to have fixed values ​​or states, and only the specific selected element can be manually adjusted. This is because changes in the remaining elements that occur when a specific selected element is manually changed are reflected in the reference state data and do not hinder the generation of the reference state data.

[0142] In S505, the monitoring element 100 can transmit radio waves of a specific frequency range into the cavity under reference conditions and receive radio waves reflected from the cavity.

[0143] A specific frequency range can be determined by considering the characteristics of the object being monitored in the apparatus and method for monitoring the process status of a chamber disclosed in this disclosure.

[0144] For example, as described above, the monitoring object of the apparatus and method disclosed in this disclosure for monitoring the process status of a chamber is whether the equipment (chamber) was correctly assembled before the process described above, or whether there are any abnormalities on the inner wall of the equipment or the surfaces of various components disposed inside the equipment due to the implemented process between processes and after the process is completed. That is, the objects to be monitored by the apparatus and method disclosed in this disclosure may include the geometry of each component inside the chamber, the wear level of each component, the relative positional relationship between each component, and unnecessary deposition of by-products generated by the process of the target substrate passing through the chamber on the inner wall of the chamber and on the surface of each component inside the chamber. Therefore, the specific frequency range used in the apparatus and method disclosed in this disclosure can be determined as a frequency band that is beneficial for monitoring the geometry of each component inside the chamber, the relative position between each component, the wear level of each component, or the unnecessary deposition of by-products generated by the process on the inner wall of the chamber and on the surface of each component inside the chamber.

[0145] As another example, the specific frequency range can be defined as a frequency band in which the state of the supplied material and energy can be measured by its influence on the state of the supplied material and energy. For instance, when monitoring the electrical / physical properties inside a chamber by measuring frequency characteristics, the state of the material and energy supplied to the chamber must be measured, and a frequency range in which the characteristics change according to the electrical / physical properties must be selected. That is, the specific frequency range can be defined as a frequency band in which the state of the supplied material and energy is affected.

[0146] According to some embodiments, a specific frequency range can be defined as a frequency band having a wavelength of 1 mm to 1000 mm. That is, a specific frequency range can be 300 MHz to 300 GHz.

[0147] According to some other embodiments, a specific frequency range can be defined as a frequency band having a wavelength of 10 mm to 500 mm. That is, a specific frequency range can be 600 MHz to 30 GHz.

[0148] According to some other embodiments, the specific frequency range may be from 1 GHz to 20 GHz.

[0149] A specific frequency range may depend on the size of the internal space of the chamber and / or the size of the components included in the chamber.

[0150] The lower limit of a specific frequency range can depend on the size of the internal space of the chamber. For example, the larger the internal space of the chamber, the smaller the lower limit can be.

[0151] The upper limit of a specific frequency range can depend on the size of the components included in the chamber. For example, the smaller the component, the higher the upper limit can be.

[0152] In S507, the monitoring element 100 can use the received radio waves to generate reference state data for the chamber. For example, the monitoring element 100 can generate reference state data by performing S505 to S507 once. As another example, the monitoring element 100 can keep the coordinates of a selected specific element constant, perform S505 to S507 a pre-configured number of times to obtain a preset number of state data, and then use representative values ​​(e.g., mean, deviation, standard deviation, mode, median, etc.) of the pre-configured number of state data to generate reference state data. Simultaneously, when the state data is a set of measurement parameters (e.g., S11 parameters) for each frequency, the monitoring element 100 can calculate representative values ​​(e.g., mean, deviation, standard deviation, mode, and median) for each measurement parameter, and use the calculated set of measurement parameters to configure the reference state data.

[0153] In other words, when the coordinates of the specific element selected to generate the reference state data are constant, a reference state data can be obtained by performing S505 to S507 once or more. Therefore, generating a reference state data by performing S505 to S507 once should be understood as follows: when the coordinates of the selected specific element are constant, the monitoring element 100 transmits radio waves of a specific frequency range into the chamber once or more, receives radio waves reflected from inside the chamber once or more, and uses the received radio waves once or more to generate reference state data.

[0154] Furthermore, reference state data refers to data generated by mapping state data or representative values ​​of state data obtained through performing one or more of the above-described S505 to S507 steps to the coordinates of a selected specific element. That is, the monitoring element 100 can generate reference state data by mapping state data or representative values ​​of said state data obtained through performing one or more of the above-described S505 to S507 steps to the coordinates of a selected specific element.

[0155] In S509, the monitoring element 100 can determine whether Y reference state data have been obtained. In this case, Y can be a pre-configured number of data. If Y reference state data have not been obtained, the coordinates of the selected specific element can be manually adjusted in S511. Afterwards, the monitoring element 100 can execute S505 to S507. That is, when the monitoring element 100 obtains the Y reference state data by executing S505 to S507 until the Y reference state data are obtained, the monitoring element 100 can store the Y reference state data in S513.

[0156] In this scenario, the manually adjusted coordinates may differ from the original coordinates. For example, the coordinates selected in S511 may be coordinates that have not been selected since S501 was implemented. In other words, the coordinates corresponding to the Y reference state data must be different coordinates, and there must be no overlapping coordinates.

[0157] [Example 2: A method for calculating the similarity between reference state data and current state data]

[0158] Monitoring element 100 can calculate the similarity between reference state data and state data measured by monitoring element 100. The higher the similarity, the more similar the current internal state of the chamber can be understood or determined to be with the reference state. Alternatively, when the similarity exceeds a similarity threshold, the current internal state of the chamber can be understood or determined to be the reference state. In other words, the current internal state of the chamber can be determined by referencing similarity.

[0159] Furthermore, monitoring element 100 can generate monitoring information based on the calculated similarity. The monitoring information may include a scatter plot of state data relative to reference state data. Users can visually examine the relationship between the reference state data and the state data through the scatter plot. For example, the scatter plot can represent the similarity between state data measured according to a predetermined cycle or a measurement trigger signal indicated by monitoring element 100 and the reference state data as points on a grid. In other words, the scatter plot can represent the similarity between the state data and the reference state data as points on a graphical plane based on a predetermined period interval or measurement trigger signal indicated by monitoring element 100.

[0160] Monitoring information may include a history of when the chamber was identified as being in a reference state in the past. This history may include, but is not limited to, the dates, times, and frequency of reference states.

[0161] The monitoring information may include a description of the reference state. This description may be, for example, a description of what process state the reference state refers to, but is not limited to this, and may include various content related to the reference state.

[0162] Figure 6 The process of generating monitoring information according to an embodiment of this disclosure is illustrated. Furthermore, in this disclosure, the monitoring information may include information obtained by estimating the current internal state of a chamber. Therefore, in this disclosure, estimating the current internal state of a chamber may mean that the monitoring element 100 generates monitoring information.

[0163] Reference Figure 6 , refer to Figure 6 In S601, the monitoring element 100 can be loaded onto... Figure 5 The Y reference state data are obtained by generating and storing Y reference state data.

[0164] Furthermore, in S603, the monitoring element 100 can transmit radio waves within a specific frequency range into the cavity and receive radio waves reflected from the cavity. Furthermore, in S605, the monitoring element 100 can use the received radio waves to generate current state data of the cavity. For example, the monitoring element 100 can generate current state data by performing S603 to S605 one or more times as described above. In this case, when the monitoring element 100 repeatedly performs S603 to S605 a predetermined number of times as described above, the current state data can be generated using representative values ​​of a predetermined number of state data obtained through the repeated performance. Meanwhile, the reference state data is data that includes state data (or representative values ​​of state data) mapped to each other and coordinates, but the current state data is data that includes state data (or representative values ​​of state data) but does not have coordinates mapped to the state data. This is because the purpose of this disclosure is to use the reference state data to find the coordinates corresponding to the current state data.

[0165] The monitoring element 100 can calculate Y first state similarities by calculating the similarity between each of the Y reference state data and the current state data.

[0166] Similarity can be calculated, for example, using graph similarity algorithms such as mean, sum of squares (SOS) and cosine similarity, correlation integral techniques or convolution techniques, but is not limited to these.

[0167] The following text will illustrate some examples of calculating similarity.

[0168] As an example of calculating similarity, monitoring element 100 can use the difference between reference state data and current state data within a specific frequency range to calculate similarity. For example, referring to the following [Equation 1], monitoring element 100 can calculate similarity as the sum of squares of the differences between the parameter values ​​of the reference state data and the parameter values ​​of the current state data within a specific frequency range.

[0169] [Equation 1]

[0170] Here, S11 (reference state) is the parameter value of the reference state data, S11 (current state) is the parameter value of the current state data measured by the monitoring element 100, and W is the total number of data points.

[0171] As another example of calculating similarity, referring to [Equation 2], the monitoring element 100 can use the cosine similarity between reference state data and current state data within a specific frequency range to calculate similarity.

[0172] [Equation 2]

[0173] Here, S11 (reference state) represents the parameter values ​​of the reference state data in vector form, and S11 (current state) represents the parameter values ​​of the state data in vector form.

[0174] Meanwhile, when [Equation 2] is expressed in the form of similarity % it is as shown in [Equation 3] below. Furthermore, [Equation 3] also represents the vector form of [Equation 2] in scalar form. Additionally, [Equation 3] represents both the vector form and the scalar form of [Equation 2].

[0175] [Equation 3]

[0176] In S609, the monitoring element 100 can generate Y first state similarity data based on the Y first state similarities. For example, in S609, the monitoring element 100 can generate the Y first state similarity data by mapping coordinates corresponding to the Y first state similarities to the Y first state similarities.

[0177] In S611, the monitoring element 100 can estimate the current internal state of the chamber based on the first state similarity data. Furthermore, the monitoring element 100 can generate the aforementioned monitoring information based on the estimated current internal state of the chamber and provide the monitoring information to the user.

[0178] For example, monitoring element 100 can estimate the coordinates of reference state data corresponding to the first state similarity with the maximum value among the Y first state similarities as the current internal state of the chamber. Furthermore, monitoring element 100 can generate monitoring information based on the estimated current internal state of the chamber and provide the monitoring information to the user.

[0179] [Example 3: Method 1 for improving the estimation accuracy of the internal state of a cavity]

[0180] However, as described above, when the monitoring element 100 estimates the coordinates of the reference state data corresponding to the first state similarity with the maximum value among the Y first state similarities as the current internal state of the chamber, errors may occur in the estimation of the current internal state of the chamber.

[0181] Figure 7 This is a diagram illustrating the problem that arises when the coordinates of reference state data, which correspond to the first state with the highest similarity as described above, are estimated as the current internal state of the chamber.

[0182] Reference Figure 7 Assume that Y reference state data are obtained by selecting "wafer chuck temperature" from M elements. For example, it is shown that nine reference state data are generated by manually adjusting the "wafer chuck temperature" from 60 degrees to 100 degrees in 5-degree increments. Monitoring element 100 can calculate a first state similarity between the current state data and each of the nine reference state data. (Refer to...) Figure 7 The first-state similarity at 80 degrees Celsius has the highest value of 99.592. Therefore, monitoring element 100 can estimate that the temperature of the wafer chuck currently present inside the chamber is 80 degrees Celsius. However, when the actual temperature of the wafer chuck currently present inside the chamber is 77 degrees Celsius, there is a difference from the temperature estimated by monitoring element 100. That is, the above method can lead to estimation errors when estimating the internal state of the chamber.

[0183] Furthermore, the above method obtains reference state data by manually adjusting the coordinates of elements. Therefore, even if a large amount of reference state data is obtained through fine-tuning the coordinates, other coordinates will inevitably exist among the adjusted coordinates. That is, no matter how finely the coordinates are adjusted, coordinates that have not been measured by the reference state data will still inevitably exist among them.

[0184] Therefore, using the above method, errors are inevitable when estimating the current internal state of the chamber, and the current internal state of the chamber may not always be accurately estimated. Therefore, a method is needed to improve the accuracy of estimating the current internal state of the chamber.

[0185] Figure 8This is a diagram illustrating a method for improving the accuracy of estimating the current internal state of a chamber.

[0186] Reference Figure 8 The monitoring element 100 can generate Y first state similarity data through S801 to S809. Simultaneously, processes S801 to S807 are... Figure 6 The processes S601 to S609 shown are the same. Therefore, the description of S801 to S807 is redundant and will not be repeated here. The application will be... Figure 6 Explanation of S601 to S609 shown.

[0187] In S811, the monitoring element 100 can perform interpolation or extrapolation within the coordinate system based on the Y first state similarity data. In this case, if the function used for interpolation or extrapolation is a polynomial function of degree two or higher, the function can be more accurate. However, the function used for interpolation or extrapolation is not necessarily limited to polynomial functions of degree two or higher, and functions of degree zero or one can also be used. For example, when using a polynomial function, the accuracy can be high, but the computational load required to estimate the state similarity in the complete coordinate system can be too large, and depending on the performance of the control unit 140 of the monitoring element 100, the excessive computational load can lead to a long time for state similarity estimation.

[0188] For example, when the degree of the polynomial function is Z, Z can be an appropriate value that will not lead to overfitting when performing interpolation or extrapolation. When the degree of the polynomial function is appropriately high, accurate interpolation or extrapolation can be performed, allowing highly accurate measurement of state similarity for all coordinates in the coordinate system. However, when the degree of the polynomial function is too high, overfitting can occur, causing the trend of state similarity within the coordinate system to fail to reflect the actual internal state of the chamber based on all coordinates in the coordinate system.

[0189] Therefore, even if Z is chosen as a natural number greater than or equal to 2, rather than 0 or 1, it is still important to choose an appropriate number that does not cause overfitting.

[0190] In short, interpolation or extrapolation can be performed by applying a function of an appropriate number of iterations based on the target estimation accuracy of the internal state of the chamber and the performance of the control unit 140.

[0191] In this case, examples applicable to interpolation or extrapolation will be described in detail in the following [Example 5].

[0192] In S813, the monitoring element 100 can determine multiple second state similarity data for each of the complete coordinates in the coordinate system by performing interpolation and / or extrapolation. In this case, all second state similarity data can also be estimated for each of the complete coordinates in the coordinate system. That is, by performing interpolation and / or extrapolation, the values ​​of the first state similarity included in the Y first state similarity data that have already been generated can be changed. Alternatively, among all coordinates in the coordinate system, the Y first state similarity data can be maintained, and the state similarity of coordinates other than the Y coordinates can be estimated by interpolation and / or extrapolation.

[0193] Here, "all coordinates" can refer to any number of coordinates that can be represented within a coordinate system. That is, "all coordinates" can mean that all spatial positions included in the coordinate system are distinguished by coordinate values.

[0194] In S815, the monitoring element 100 may select the state similarity data with the greatest similarity among the plurality of second state similarity data as the estimated similarity data.

[0195] In S817, the monitoring element 100 can estimate the values ​​of the coordinates included in the estimated similarity data as the current internal state of the chamber.

[0196] Figure 9 An example is shown where the current internal state of the chamber is estimated in the same manner as described above. Furthermore, in order to obtain... Figure 9 The outline diagram shown obtained Y reference state data by manually adjusting the wafer chuck temperature Y times among M elements. That is, Figure 9 The coordinate system shown is a one-dimensional coordinate system with "wafer chuck temperature" as the axis, and the Y values ​​of "wafer chuck temperature" that are manually adjusted Y times are the coordinates of the reference state data.

[0197] also, Figure 9 The monitoring element 100 generates Y first state similarity data by calculating the similarity between each of the Y obtained reference state data and the current state data, and obtains multiple second state similarity data with complete coordinates by interpolation. Figure 9 The interpolation used visualizes the profile of the state similarity data of "wafer chuck temperature" by applying a polynomial function profile fitting method.

[0198] Reference Figure 9 As can be seen from (a) and (b), the "wafer chuck temperature" is estimated to be 70 degrees regardless of the actual "wafer chuck height". Furthermore, when the current "wafer chuck temperature" is 70 degrees, the current "wafer chuck temperature" can be estimated to be 70 degrees by interpolation, regardless of whether reference state data is generated when the "wafer chuck temperature" is 70 degrees.

[0199] Therefore, the embodiments of this disclosure can improve estimation accuracy.

[0200] Furthermore, according to embodiments of this disclosure, the current internal state of the chamber can be accurately estimated even using a small amount of reference state data. Previously, to improve estimation accuracy, more reference state data for various coordinates had to be obtained. However, obtaining more reference state data required more time and cost to manually adjust the coordinates. In addition, users had to expend considerable effort to obtain the reference state data. However, there are always coordinates that cannot be estimated using reference state data. Therefore, the efficiency may not be significant compared to the time and cost invested.

[0201] Furthermore, storing large amounts of reference state data requires corresponding storage space. Additionally, to estimate the internal state of the chamber, a large amount of reference state data must be loaded each time, which increases the processing load for comparing it with the current state data.

[0202] However, according to embodiments of this disclosure, even when using relatively less reference state data, the current internal state of the chamber can be estimated more accurately than when using more reference state data, thereby achieving the effect of requiring less storage space and less processing load.

[0203] [Example 4: Method 2 for improving the estimation accuracy of the internal state of a cavity]

[0204] In [Example 2], it is described that one of M elements is selected, and the selected element is manually adjusted Y times so that the monitoring element 100 generates Y reference state data. Furthermore, it can be seen that by generating the Y reference state data according to the method of [Example 2] and estimating the current internal state of the chamber according to [Example 3], the estimation accuracy is significantly improved compared to conventional techniques.

[0205] Nevertheless, in [Example 4], a method will be described that improves the estimation accuracy more than selecting only one of the M elements, so that the monitoring element 100 generates Y reference state data to estimate the current internal state of the chamber.

[0206] Figure 10 The aim is to explain the problems that may occur when only one of M elements is manually adjusted Y times.

[0207] Figure 10 This is a graph showing the similarity between reference state data and current state data measured at a coordinate point 0.5 mm high on the wafer chuck, measured multiple times. That is, Figure 10The similarity of states from multiple measurements is shown to estimate the height of the wafer chuck inside the chamber. Additionally, although these are not coordinates constituting a coordinate system, the temperature of the wafer chuck is 100 degrees Celsius when the corresponding reference state data is generated.

[0208] observe Figure 10 The graph in the figure shows the highest similarity when the current wafer chuck temperature is 100 degrees and the current wafer chuck height is 0.5 mm. This is a natural result, as the reference state data was generated when the wafer chuck temperature was 100 degrees and the wafer chuck height was 0.5 mm.

[0209] However, even when the reference state data is generated at a wafer chuck height of 0.5 mm, the similarity is not the highest when the current wafer chuck temperature is 90 degrees Celsius. Specifically, when calculating the similarity between the internal state of the chamber at a current wafer chuck temperature of 90 degrees Celsius and the reference state data, the similarity is slightly higher when the current wafer chuck height is 0.6 mm than when it is 0.5 mm. Therefore, even if the actual height of the current wafer chuck is 0.6 mm, it can still be estimated as 0.5 mm due to variations in wafer chuck temperature. This leads to a decrease in the estimation accuracy of the actually selected elements due to variations in other unselected elements.

[0210] In addition, such as Figure 10 As shown, the similarity is extremely high when the current wafer chuck height is 0.4 mm, 0.5 mm, and 0.6 mm. In this case, it may be unclear whether the monitoring element 100 should estimate the current wafer chuck height as 0.4 mm, 0.5 mm, or 0.6 mm.

[0211] Therefore, a method is needed to solve the above. Figure 10 This addresses the problems in the estimation process and further improves the accuracy of the estimation.

[0212] To address the aforementioned issues and improve estimation accuracy, N-dimensional reference state data can be acquired. In this case, N can be a natural number greater than or equal to 2. That is, by selecting two or more elements from M elements and generating Y reference state data, estimation accuracy can be further improved. For example, when the monitoring element 100 is not manually adjusted... Figure 10 When the height of the wafer chuck and the temperature of the wafer chuck are adjusted manually, reference state data can be generated, allowing for a more accurate estimation of the current internal state of the chamber.

[0213] Therefore, it is necessary to base on Figure 11 The method described herein generates reference state data, rather than the method based on [Example 1]. Figure 5 A method for generating reference state data (as described in [Example 1]).

[0214] Reference Figure 11 In S1101, the monitoring element 100 can select N elements from M elements that define the interior of the chamber.

[0215] For example, when selecting two elements to estimate the state of a wafer chuck, "wafer chuck height" and "wafer chuck temperature" can be chosen. As another example, when selecting two elements to estimate wafer alignment, "wafer loading" and "edge ring height" can be chosen. As yet another example, when selecting two factors to check whether the temperature inside the chamber has stabilized, "wafer chuck temperature" and "chamber wall temperature" can be chosen. However, the elements are not limited to these, and the number of selected elements can be greater than or equal to three, and various combinations of elements can be selected depending on the purpose of estimating the state inside the chamber.

[0216] In S1103, when N elements out of M elements are selected, the internal state of the chamber can be manually adjusted so that the N elements have specific coordinates based on the N-dimensional coordinate system, thereby preparing a chamber with a manually adjusted internal state.

[0217] Furthermore, when the N elements are artificially altered, the remaining MN elements can also be altered. However, as shown in [Example 1]... Figure 5 As mentioned earlier, the relationships between these elements can be ignored. In other words, even if the remaining MN elements are changed by artificially altering the N elements, the change to the remaining MN elements can be ignored.

[0218] In S1105, the monitoring element 100 can transmit radio waves of a specific frequency range into the cavity in a reference state and receive radio waves reflected from the cavity.

[0219] Furthermore, in S1107, the monitoring element 100 can use the received radio waves to generate reference state data for the chamber. In this case, the method for generating reference state data can be the same as... Figure 5 The method described herein. In other words, when the coordinates of the N elements selected to generate a reference state data are constant, a reference state data can be obtained by performing S1105 to S1107 one or more times. Therefore, performing S1105 to S1107 once to generate a reference state data should be understood as the monitoring element 100 transmitting radio waves of a specific frequency range into the cavity one or more times when the coordinates of the selected specific elements are constant, receiving radio waves reflected from inside the cavity one or more times, and using the received radio waves one or more times to generate reference state data.

[0220] Furthermore, reference state data refers to data generated by mapping state data or representative values ​​of the state data obtained through performing S1105 to S1107 one or more times to the coordinates of a selected specific element. That is, the monitoring element 100 can generate a reference by mapping state data or representative values ​​of the state data obtained through performing S1105 to S1107 one or more times to the coordinates of a selected specific element. Here, representative values ​​may include, but are not limited to, the average, deviation, standard deviation, mode, and median as described above.

[0221] In step S1109, monitoring element 100 can determine whether Y reference state data have been acquired. In this case, Y can be a pre-configured number. If the Y reference state data are not acquired, the coordinates of the selected specific element can be manually adjusted in step S1111. Afterward, monitoring element 100 can perform steps S1105 to S1107. That is, when monitoring element 100 performs steps S1105 to S1107 until the Y reference state data are acquired, monitoring element 100 can store the Y reference state data in step S1113.

[0222] In this scenario, the manually adjusted coordinates may differ from the original coordinates. For example, the coordinates selected in S1111 may be coordinates that have not been selected since S1101 was implemented. In other words, the coordinates corresponding to each of the Y reference state data must be distinct coordinates, and there must be no overlapping coordinates.

[0223] At the same time, when the coordinates of N elements are manually adjusted, there are various methods to select the coordinates that are manually adjusted.

[0224] Figure 12 This illustrates a method for selecting manually adjusted coordinates when N is 2, and an example of the corresponding configuration of Y reference state data. However, Figure 12 The aim is to utilize visual materials to facilitate understanding of the ideas in this disclosure, and through Figure 12 The method for configuring the Y reference state data described is not limited to the case of N=2.

[0225] In other words, even when N is 3 or greater than 3, the method can still be applied. Figure 12 The methods for configuring Y reference state data are described in (a) to (d).

[0226] Now, refer to Figure 12 This section describes the method for configuring the Y reference state data.

[0227] Figure 12(a) shows that the Y reference state data are configured such that all Y coordinates are equally spaced in an N-dimensional coordinate system. Figure 12 In (a), the spacing between adjacent coordinates within the coordinate system can be constant. For example, Figure 12 The spacing between adjacent axial coordinates of the first element in (a) can be constant, and the spacing between adjacent axial coordinates of the second element can be constant.

[0228] As in Figure 12 In (a), the method for configuring the Y reference state data is to obtain the Y reference state data by adjusting each of the selected N elements as many times as possible in an N-dimensional coordinate system. Since each of the N elements is adjusted as many times as possible, the estimation accuracy can be higher than that of other configuration methods.

[0229] In this scenario, estimation accuracy can be improved by making the spacing between elements closer together, but the number of reference state data can also be reduced by making the spacing between elements larger. Even with a reduced number of reference state data, the estimation accuracy can still be higher than that of conventional techniques that do not perform interpolation as described above.

[0230] Figure 12 (b) illustrates obtaining Y reference state data by repeatedly performing the following process on each of the N elements: in which reference state data is generated while adjusting the value of only one of the selected N elements at regular intervals and keeping the remaining elements unchanged. Figure 12 As shown in (b), for reference state data measured when only the first element is changed and the second element is not changed, the spacing between adjacent axial coordinates of the first element is constant. On the other hand, for reference state data measured when only the second element is changed and the first element is not changed, the spacing between adjacent axial coordinates of the second element is constant.

[0231] Figure 12 (b) is a method of configuring the Y reference state data by adjusting only one element among the N elements based on the value of greatest interest to the user. For example... Figure 12 The configuration in (b) can significantly reduce the time cost of configuring the Y reference state data.

[0232] Figure 12 (c) illustrates the generation of reference state data for randomly selected coordinates in an N-dimensional coordinate system. Y coordinates are randomly selected, and the internal state of the chamber is artificially adjusted to correspond to each of the selected Y coordinates, thereby generating reference state data.

[0233] Even if the Y reference state data are as follows Figure 12 In the general configuration of (c), if the Y reference state data are distributed on an N-dimensional coordinate system, the current internal state of the chamber can also be estimated by interpolation.

[0234] exist Figure 12 In (d), Y coordinates are selected based on a pre-configured pattern in an N-dimensional coordinate system, and the internal state of the chamber is manually adjusted to correspond to each of the selected Y coordinates, thereby generating reference state data. In this case, the pre-configured pattern can be stored in the storage unit 150 of the monitoring element 100 and / or the storage unit 220 of the monitoring system described below. In this case, the coordinates of the pre-configured pattern can also be stored. Alternatively, when information about the pre-configured pattern and reference coordinates is stored, the Y coordinates can be selected by scaling the pre-configured pattern based on the selected N elements, the size of the complete coordinate system, and the number of selected coordinates (i.e., Y).

[0235] Even in Figure 12 In case (d), when the Y reference state data are distributed on an N-dimensional coordinate system, even if the Y reference state data are configured, the current internal state of the chamber can be estimated by interpolation.

[0236] Furthermore, the methods for selecting Y coordinates and configuring Y reference state data are not limited to... Figure 12 Examples in the text. That is, Figure 12 This is merely an embodiment of how the Y reference state data can be configured, and the Y reference state data can be configured in any way.

[0237] also, Figure 12 The example shown is not limited to the case of N=2 as described above, and even when N>2, the same principle can be used to configure the Y reference state data in the N-dimensional coordinate system according to the increase in the number and direction of the axes.

[0238] The monitoring element 100 can use Y stored reference state data to estimate the current internal state of the chamber. In this case, the monitoring element 100 can, based on... Figure 8 The current internal state of the chamber is estimated using the processes S801 to S817 described herein. That is, as the number of elements to be selected increases, the method for configuring the Y reference state data may differ, but the method for using the Y reference state data to estimate the current internal state of the chamber may be the same.

[0239] That is, all coordinates in the coordinate system can be considered identical, except that they are coordinates of an N-dimensional coordinate system rather than a one-dimensional coordinate system. In other words, besides the fact that the number of values ​​included in the axes and coordinates of the coordinate system is N, Figure 8The procedures S801 to S817 are even applied in [Example 4], making it possible to estimate the current internal state of the chamber.

[0240] Figures 13 to 16 The use of the above is shown. Figure 12 The Y reference state data configured in (a) to (d) are used to measure the current internal state of the chamber.

[0241] Figures 13 to 16 The diagram illustrates configuring Y reference state data by selecting "wafer chuck height" and "wafer chuck temperature" as the height. However, it is not limited to this, and those skilled in the art will readily understand that the current internal state of the chamber can be measured according to the same principle even when other elements are selected, and the current internal state of the chamber can be measured according to the same principle even when more than 2 elements are selected.

[0242] also, Figures 13 to 16 The interpolation used is a polynomial function contour fitting method. Furthermore, this is a visualization of the contour plots of the state similarity data for "wafer chuck height" and "wafer chuck temperature".

[0243] Figure 13 Shown by according to Figure 12 (a) is used to configure the Y reference state data to estimate the current internal state of the chamber. Figure 14 Shown by according to Figure 12 (b) is used to configure Y reference state data to estimate the current internal state of the chamber. Figure 15 Shown by according to Figure 12 (c) is used to configure Y reference state data to estimate the current internal state of the chamber. Figure 16 Shown by according to Figure 12 The (d) is used to configure Y reference state data to estimate the current internal state of the chamber.

[0244] Reference Figures 13 to 16 The diagram illustrates first state similarity data for the coordinates of the Y reference state data generated through interpolation, and multiple second state similarity data for all coordinates within the coordinate system. That is, second state similarity data for coordinates other than the Y coordinates configured with the Y reference state data can also be determined, and the highest state similarity data among the multiple second state similarity data for all coordinates can be determined as the estimated state similarity data. Furthermore, the coordinates of the estimated state similarity data can be used to estimate the current internal state of the chamber.

[0245] Figure 17 This demonstrates another method for configuring Y reference state data, and Figure 18 An example of interpolation is shown accordingly.

[0246] Figure 17 This illustrates the acquisition of Y reference state data while performing multiple processes included in a process cycle.

[0247] Figure 17 (a) illustrates that when a process cycle includes five processes a to e, the monitoring element 100 acquires a reference state data from each of the five processes while the five processes are being performed. That is, the monitoring element 100 selects two elements from the M elements that define the internal state of the chamber, and measures the coordinates of the selected two elements in each process while the process cycle is in progress.

[0248] Figure 17 (b) shows that monitoring element 100 measures the coordinates of two elements selected periodically or aperiodically within a process. Meanwhile, Figure 17 (b) can be a diagram showing the monitoring element 100 measuring the coordinates of two elements multiple times within a single process, but it can also be a diagram showing the monitoring element 100 measuring the coordinates of two elements within the same plurality of processes performed during multiple process cycles. For example, when 10 process cycles are performed, the monitoring element 100 can measure the coordinates of two elements each time the first process is performed. In this case, the monitoring element 100 can measure the coordinates at least once in the first process of a single process cycle.

[0249] Figure 17 (c) is Figure 17 (a) and Figure 17 The combination of (b) can be used to create a graph of coordinates with two elements measured within multiple processes during multiple process cycles performed by the monitoring element 100. For example, after measuring coordinates with two elements simultaneously during multiple process cycles, the coordinates measured in each of the first to the Tth processes can be classified based on process data.

[0250] at the same time, Figure 17 Examples (a) through (c) are merely examples given for the purpose of illustration and are not limited thereto. For instance, the number of processes that may be included in a process cycle is not limited to five, but may include a variety of numbers of processes such that reference state data for each process can be obtained.

[0251] Figure 18 The use of the above is shown. Figure 17 The configured Y reference state data are used to measure the current internal state of the chamber.

[0252] Figure 18The diagram illustrates the selection of "wafer chuck height" and "wafer chuck temperature" as heights to configure the Y reference state data. However, this is not a limitation, and those skilled in the art will readily understand that the current internal state of the chamber can be measured according to the same principle even when other elements are selected, and the current internal state of the chamber can be measured according to the same principle even when more than 2 elements are selected.

[0253] also, Figure 18 The interpolation used is a polynomial function contour fitting method. Furthermore, this is a visualization of the contour plots of the state similarity data for "wafer chuck height" and "wafer chuck temperature".

[0254] Reference Figure 18 The diagram illustrates first state similarity data calculated by interpolation of the coordinates of the Y reference state data, and a plurality of second state similarity data for all coordinates within the coordinate system. That is, second state similarity data for coordinates other than the Y coordinates configuring the Y reference state data can also be determined, and the highest state similarity data among the plurality of second state similarity data for all coordinates can be determined as the estimated state similarity data. Furthermore, the coordinates of the estimated state similarity data can be estimated as the current internal state of the chamber.

[0255] At the same time, when according to Figures 17 to 18 When estimating the current internal state of a chamber, it can be determined whether an anomaly has occurred during the process. For example, if there is a predetermined amount or greater difference between the coordinates of the estimated current internal state of the chamber based on the current state data measured during the first process and the coordinates of the reference state data measured during the first process, the monitoring element 100 can identify that an anomaly has occurred in the first process and can notify the user of this.

[0256] At the same time, such as Figure 17 As shown, when obtaining reference state data for each of the multiple processes while performing multiple process cycles, obtaining the reference state data and estimating the current internal state of the chamber can be performed together.

[0257] For example, when the monitoring element 100 obtains the current state data in the first process of the Rth process cycle, the reference state data obtained up to the (R-1)th process cycle and the current state data can be used to estimate the current internal state of the chamber.

[0258] Meanwhile, in the first process of the aforementioned Rth process cycle, the current state data can be added to the database storing the reference state data as reference state data.

[0259] The monitoring element 100 obtains current status data in the first or second process of the (R+1)th process cycle, and can use the reference status data (i.e., the stored database) obtained up to the Rth process cycle and the current status data to estimate the current internal state of the chamber.

[0260] That is, the current state data measured in the Rth process cycle can be used as reference state data to estimate the current internal state of the chamber in the (R+1)th process cycle.

[0261] Meanwhile, when an anomaly is determined in the current internal state of the chamber based on the current state data measured in the Rth process cycle, the monitoring element 100 may not add the current state data measured in the Rth process cycle as reference state data. This is because the availability of the current state data determined to be abnormal as reference state data is low.

[0262] Meanwhile, the current internal state of the chamber can exist at coordinates outside the virtual coordinate system used as the basis for determining the Y reference state data.

[0263] In this situation, extrapolation can be used to estimate the current internal state of the chamber. (Refer to...) Figure 19 This will be explained.

[0264] Figure 19 (a) shows Y reference state data configured according to a coordinate system corresponding to region A. However, when calculating the state similarity between the current state data and the Y reference state data, significant similarity may not be found within region A. Alternatively, the state similarity between the current state data and the Y reference state data can be calculated, and interpolation can be performed on region A, but significant similarity may not be found. This could mean that there are no coordinates within region A corresponding to the current internal state of the chamber.

[0265] In this situation, extrapolation can be used to estimate the current internal state of the chamber. Figure 19 (b) and (c) illustrate the use of extrapolation to estimate the current internal state of the chamber. That is, extrapolation can be used to extend the coordinate system when it is determined that no significant similarity is found within region A.

[0266] For example, the monitoring element 100 can perform interpolation in the coordinate system of region A, and select the coordinate with the greatest state similarity among the plurality of second state similarity data for all coordinates in the coordinate system.

[0267] The monitoring element 100 can determine whether the state similarity of the selected coordinates is sufficiently significant to be estimated as the current internal state of the chamber. For example, the monitoring element 100 selects coordinates with the maximum state similarity within the coordinate system. When the selected coordinates are located on the boundary of the region where interpolation is performed within the coordinate system, it can be estimated that the current internal state of the chamber exists outside the coordinate system, and there are no significant coordinates within the coordinate system that are to be estimated as the current internal state of the chamber.

[0268] In this scenario, the monitoring element 100 can estimate the current internal state of the chamber in a region outside the coordinate system and perform extrapolation.

[0269] For example, refer to Figure 20 This illustrates connecting (N+1) coordinates to perform interpolation based on Y first-state similarity data. In other words, in Figure 20 In this process, two elements are selected to generate first-state similarity data for Y coordinates in a two-dimensional coordinate system, and multiple triangular shapes are generated on the coordinate system by connecting the Y coordinates in groups of three. In this case, the boundary of the region in which interpolation is performed can refer to the outermost line among the lines that generate multiple triangular shapes by connecting the Y coordinates in groups of three, as shown in the portion indicated by the dashed line.

[0270] When the monitoring element 100 performs interpolation to select coordinates with the maximum state similarity and the selected maximum state similarity is located on the boundary, the monitoring element 100 estimates that the current internal state of the chamber exists in a region outside the coordinate system, and extrapolation can be performed.

[0271] To perform extrapolation, monitoring element 100 can expand its coordinate system. For example, the coordinate system existing within region A can be expanded to a larger extent. Within the expanded coordinate system, monitoring element 100 can perform extrapolation to select coordinates with the greatest state similarity within the expanded coordinate system. Furthermore, monitoring element 100 can estimate the current internal state of the chamber based on the selected coordinates.

[0272] For example, Figure 19 Images (b) and (c) illustrate examples of using extrapolation with a contour fitting method. Monitoring element 100 can estimate the current internal state of the chamber by using extrapolation within a coordinate system established through the coordinate system of the extended region A. However, extrapolation is not necessarily limited to using only... Figure 17 Instead of using the contour fitting methods in (b) and (c), any known extrapolation method can be used.

[0273] Simultaneously, in S811, the monitoring element 100 can perform extrapolation instead of interpolation. For example, when it is determined that the current internal state of the chamber does not exist in the coordinate system of region A, the monitoring element 100 can perform extrapolation by expanding the coordinate system of region A instead of interpolation. In this case, when the coordinate with the highest state similarity among the state similarity data of the first state similarity data of the Y coordinates in the coordinate system of region A corresponds to the minimum or maximum value of the values ​​included in the Y coordinates, the monitoring element 100 can perform extrapolation by expanding the coordinate system of region A and estimate the current internal state of the chamber based on the coordinate with the highest state similarity in the expanded coordinate system.

[0274] Meanwhile, the methods for performing interpolation and extrapolation will be described in detail in [Example 5].

[0275] Meanwhile, [Example 4] mainly describes the case where N=2, but as mentioned above, the above method can also be applied equivalently to the case where N is 3 or greater than 3.

[0276] Furthermore, as mentioned above, the estimation accuracy increases with increasing N, because the increase in estimation accuracy is greater when N=2 than when N=1. In addition, as N increases, the number of functions that can be used for interpolation or extrapolation can increase. That is, as N increases, the functions that can be used for interpolation and / or extrapolation become more diverse. In this way, since appropriate functions can be used to perform interpolation and / or extrapolation based on the selected elements, the method of configuring the Y reference state data, and / or the Y coordinates corresponding to the Y reference state data, the estimation accuracy of the current internal state of the chamber can be further improved.

[0277] However, when selecting four or more elements from M elements, the coordinate system must have four or more axes, making it difficult to visually represent the coordinates corresponding to the current internal state of the chamber within the coordinate system, and to visually represent the state similarity of the complete coordinates within the coordinate system, for example in... Figures 13 to 17 The outline diagram shown is an example of this. Therefore, there may be limitations in visually providing the user with complete coordinates and state similarity corresponding to the current internal state of the chamber.

[0278] In this scenario, monitoring element 100 may extract two or three elements from the four or more selected elements, and then generate one or more 2D or 3D coordinate graphs for the two or three elements, and provide them to the user. For example, when there are six selected elements and the user is provided with 2D coordinate graphs generated by extracting two elements, monitoring element 100 may combine the 6C2 elements and generate 6C2 2D coordinate graphs for each of the corresponding combinations. Furthermore, upon user request, monitoring element 100 may provide the user with at least some of the 6C2 2D coordinate graphs.

[0279] [Example 5: Interpolation and / or Extrapolation]

[0280] Now, it will be explained in Figure 8 The method for performing interpolation and / or extrapolation in a coordinate system as described in S811.

[0281] When the monitoring element 100 determines the first state similarity data based on the first state similarity of each of the Y coordinates, it can use the Y coordinates in the coordinate system and the first state similarity corresponding to each of the Y coordinates to perform interpolation and / or extrapolation.

[0282] (1) Interpolation

[0283] The monitoring element 100 selects (N+1) coordinates and connects the coordinates to each other. That is, when selecting N elements out of M elements, the monitoring element 100 can select coordinates with (N+1) vertices and connect the coordinates to each other.

[0284] In this scenario, monitoring element 100 may select (N+1) coordinates in the complete coordinate system and connect these coordinates to each other. In this case, monitoring element 100 must ensure that each of the Y coordinates is connected to at least one other coordinate. That is, monitoring element 100 must ensure that among the Y coordinates, there is no coordinate that is not connected to another coordinate. This is because interpolation must be performed on all Y coordinates. Furthermore, the lines connecting the Y coordinates must not intersect each other.

[0285] Figure 20 This illustrates an example of connecting Y coordinates to perform interpolation in a two-dimensional coordinate system.

[0286] Reference Figure 20 By selecting two elements, first state similarity data of Y coordinates in a two-dimensional coordinate system is generated, and by connecting the Y coordinates in groups of three, multiple triangle shapes are generated in the coordinate system.

[0287] Meanwhile, when selecting and connecting Y coordinates in groups of (N+1), the method for selecting (N+1) coordinates can be as follows.

[0288] (1) (N+1) coordinates can be randomly selected. That is, the monitoring element 100 can randomly select and connect coordinates in groups of (N+1) on the coordinate system. However, even in this case, the monitoring element 100 must select coordinates in groups of (N+1) so that the connecting lines do not intersect.

[0289] (2) The coordinates with the highest state similarity can be selected and connected first. That is, the monitoring element 100 connects the coordinates with high state similarity by connecting the first coordinate with the highest state similarity, the second coordinate with the second highest state similarity, and the third coordinate with the third highest state similarity, so that the Y coordinates can be connected on the coordinate system.

[0290] (3) Adjacent coordinates can be connected to each other. That is, the monitoring element 100 can select and connect coordinates such that the interval between coordinates is minimized, or such that the area of ​​the shape formed when the coordinates are connected (e.g., a triangle in the case of a two-dimensional coordinate system) is minimized. In this case, at least one coordinate first selected to connect the coordinates can be the coordinate located at the outermost edge of the coordinates.

[0291] (4) Coordinates can be connected by combining (2) and (3). That is, the monitoring element 100 can first select and connect coordinates with the highest state similarity, but it can also select and connect coordinates such that the interval between coordinates is the shortest, or such that the area of ​​the shape formed when the coordinates are connected (e.g., a triangular shape in the case of a two-dimensional coordinate system) is the smallest.

[0292] The monitoring element 100 connects (N+1) coordinates in the complete coordinate system in the N-dimensional coordinate system and performs interpolation based on the connected coordinates.

[0293] That is, with Figure 20 For example, the monitoring element 100 can perform interpolation on the interior space of each triangle. In this case, a polynomial function of degree 2 or higher can be used to perform the interpolation. For example, a contour fitting method can be used for the interpolation as described above, and the monitoring element 100 can generate a contour map according to the contour fitting method. However, the interpolation method implemented in the embodiments of this disclosure is not limited to the contour fitting method, but any well-known interpolation method can be used.

[0294] For example, interpolation methods such as trigonometric interpolation or cubic interpolation can be used, and any interpolation method utilizing polynomial functions can be used without restriction. Furthermore, as mentioned above, the functions used for interpolation are not limited to polynomial functions of degree 2 or higher, and can also be zero-degree or first-degree functions.

[0295] In other words, Figure 20 The purpose is to facilitate understanding of how to connect the Y coordinates within a coordinate system, and the method of interpolation should not be interpreted as limited to... Figure 18 The diagram.

[0296] Furthermore, as the dimensions of the coordinate system increase, the shape of the connections within the coordinate system can also change. For example, when forming a three-dimensional coordinate system, four coordinates can be connected in each group. In this case, by connecting four coordinates in each group, multiple three-dimensional triangular pyramid shapes can be generated on the coordinate system.

[0297] (2) External insertion

[0298] The extrapolation according to embodiments of this disclosure can be at least one of the well-known extrapolation methods. For example, a polynomial function of degree 2 or higher can be used to perform extrapolation. However, as mentioned above, even the function performed in extrapolation is not necessarily limited to a polynomial function of degree 2 or higher, and can also be a function of degree 0 or 1.

[0299] For example, Figure 19 (b) and (c) illustrate extrapolation performed using a contour fitting method. For example, when using a contour fitting method to perform extrapolation, an ellipse or a circle can be used to estimate the contour.

[0300] In the case of interpolation, the contour line has no predetermined shape and can be formed into an undefined shape other than an ellipse or a circle. However, in the case of extrapolation, since the coordinate system of region A must be expanded to find the coordinates corresponding to the current internal state of the chamber in the expanded coordinate system, assuming a predetermined shape as the contour line is most efficient. Furthermore, among the predetermined shapes that can be assumed as contour lines, ellipses or circles are most effective for finding the coordinates used to estimate the current internal state of the chamber. However, the shape is not limited to ellipses or circles, and the most suitable shape for fitting can be selected in various ways depending on the function applied to extrapolation or the result obtained by interpolation.

[0301] Figure 21 The purpose is to demonstrate a general method for performing extrapolation. Figure 21 (a) concerns the first method of performing extrapolation. Figure 21 In (a), the result of the interpolation performed by the monitoring element 100 in a rectangular one-dimensional coordinate system is represented by a solid line. That is, Figure 21 (a) shows that the monitoring element 100 estimates the state similarity of the "wafer chuck height" by interpolating based on reference state data.

[0302] according to Figure 21 (a) The monitoring element 100 performs extrapolation by selecting some points included in at least one outermost region based on the result of fitting through interpolation. Figure 21 (a) is fitted in the form of a line, and extrapolation is performed using points included in each of the two regions (two dashed elliptical lines) located at opposite ends. That is, extrapolation can be performed in each of the two regions using a specific function.

[0303] Thus, the fitting result derived from the existing interpolation (solid line) and the fitting result derived from the extrapolation (dashed line) can be connected to derive a single fitting result, and the monitoring element 100 can estimate the coordinates that maximize state similarity through this single fitting result.

[0304] Figure 21 (b) concerns the second method of performing extrapolation. Figure 21 In (b), with Figure 21 In (a), the same method is represented by solid lines, indicating the result of fitting by interpolation within a rectangular one-dimensional coordinate system. That is, Figure 21 (b) shows the state similarity of the "wafer chuck height" estimated by interpolation based on reference state data. Figure 21 In (b), all state similarities of "wafer chuck height" represented by solid lines are used for extrapolation fitting. Figure 21 The dashed line in (b) represents the fitting result obtained by using extrapolation.

[0305] When as in Figure 21 When extrapolating in (b), the "wafer chuck height" can be re-estimated not only outside the coordinate system but also inside the coordinate system through the fitting results, based on the state similarity. That is, according to Figure 21 (b) can estimate new state similarity even at coordinates where state similarity has already been estimated.

[0306] Therefore, the monitoring element 100 can be monitored by means of... Figure 21 The fitting results in (b) are used to estimate the coordinates that maximize state similarity.

[0307] [Experimental Data]

[0308] Figure 22 and Figure 23 Experimental results are shown to demonstrate that, as described in [Example 4], the estimation accuracy increases as the number of N elements selected from the M elements increases.

[0309] Specifically, Figure 22 The aim is to demonstrate the accuracy of estimating the current internal state of a chamber based on reference state data in a one-dimensional coordinate system configured by selecting only one element. Figure 23 The aim is to demonstrate the accuracy of estimating the current internal state of a chamber based on reference state data in a two- or three-dimensional coordinate system configured by selecting two or three elements.

[0310] exist Figure 22 and Figure 23 In the experiment, cubic interpolation was used to estimate the multiple second-state similarity data for each of the complete coordinates in the coordinate system.

[0311] The cubic interpolation uses a three-dimensional function and employs the following [Equation 4].

[0312] [Equation 4]

[0313] In addition, experiments were conducted to determine whether the internal state of the chamber after adjustment could be accurately estimated based on the dimensions of the coordinate system by adjusting the wafer chuck height to 0.1 mm, the wafer chuck temperature to 70 degrees, and the APC valve opening rate to 10%.

[0314] Figure 22 This is an experiment on the estimation accuracy conducted by configuring reference state data in a one-dimensional coordinate system of "wafer chuck height".

[0315] Reference Figure 22 (a) The estimated wafer chuck height is 0 mm, which is slightly different from the actual wafer chuck height of 0.1 mm. Figure 22 (b) is Figure 22 A three-dimensional plot of the results in (a) is provided to visualize the experimental results more clearly as the dimensions of the coordinate system increase. Even when observing... Figure 22 As can be seen in (b), there are some differences between the actual wafer chuck height (0.1 mm) and the estimated wafer chuck height (0 mm) (which is the position with the highest state similarity).

[0316] Figure 23 (a) shows the experimental results of the estimation accuracy obtained by configuring reference state data in a two-dimensional coordinate system with wafer chuck height and temperature. That is, compared to Figure 22 When configuring the reference status data, another element called "wafer chuck temperature" was added.

[0317] As a result of the experiment, the wafer chuck height was estimated to be 0.0999 mm, showing an estimation accuracy almost identical to the actual wafer chuck height of 0.1 mm. That is, when using reference state data in a two-dimensional coordinate system incorporating wafer chuck temperature, the estimation accuracy of the wafer chuck height can be significantly improved compared to using reference state data in a one-dimensional coordinate system using only the wafer chuck height.

[0318] Figure 23 (b) shows experimental results for the estimation accuracy obtained by configuring reference state data in a three-dimensional coordinate system with wafer chuck height, wafer chuck temperature, and APC valve opening rate. That is, when configuring the reference state data, compared to... Figure 23 (a) added another element, "APC valve opening rate".

[0319] As a result of the experiment, the wafer chuck height was estimated to be 0.1 mm, demonstrating an estimation accuracy that perfectly matches the actual wafer chuck height of 0.1 mm. It has been confirmed that by configuring reference data that includes the APC valve opening rate, the estimation accuracy of the wafer chuck height can be significantly improved compared to using only one-dimensional coordinate system reference data for wafer chuck height or two-dimensional coordinate system reference data for wafer chuck height and temperature.

[0320] Specifically, when configuring reference state data, the increase in estimation accuracy due to the increase in coordinate system dimensions can vary depending on the degree of independence between the selected N elements. For example, in Figure 22 and Figure 23 In this context, the independence between "wafer chuck height" and "wafer chuck temperature" is relatively weak. That is, "wafer chuck height" and "wafer chuck temperature" may have a dependent relationship. In this case, dependency can be defined as a relationship where, when the value of one of the selected N elements changes by a first rate, the value of the other element changes by a rate greater than a second rate. For example, the first rate could be 10%, and the second rate could be 0.1%. In other words, when the value of one of the N selected elements increases or decreases by 10% and the value of the other element increases or decreases by more than 0.1%, the two elements can be said to have a dependent relationship. On the other hand, when the value of one of the N selected elements increases or decreases by 10% and the value of the other element increases or decreases by 0.1% or less, the two elements can be said to have an independent relationship. That is, independence can be defined as a relationship where, when the value of one of the selected N elements changes by a first rate, the value of the other element changes by a second rate or less than the second rate.

[0321] In this scenario, the estimation accuracy can be significantly improved when the reference state data is configured in a two-dimensional coordinate system of "wafer chuck height" and "wafer chuck temperature" to estimate the "wafer chuck height" compared to when the reference state data is configured in a one-dimensional coordinate system of "wafer chuck height".

[0322] In fact, when estimating the internal state of the chamber by configuring reference state data in a one-dimensional coordinate system of the wafer chuck height when the wafer chuck height is 0 mm and the wafer chuck temperature is 100 degrees Celsius, the estimated wafer chuck height varies depending on the wafer chuck temperature. Specifically, it was found that when using reference state data of 0 mm wafer chuck height and 100 degrees Celsius in the same manner to estimate the internal state of the chamber when the wafer chuck height is 0 mm, the estimated wafer chuck height is 0.03 mm when the wafer chuck temperature is 90 degrees Celsius, 0.06 mm when the wafer chuck temperature is 80 degrees Celsius, and 0.1 mm when the wafer chuck temperature is 70 degrees Celsius, resulting in... Figure 10 The issues discussed in the text are similar to those in the text.

[0323] Therefore, in this situation, through Figure 20 and Figure 21 It has been confirmed that estimation accuracy can be improved by configuring and measuring reference state data in a two-dimensional coordinate system for wafer chuck temperature and height. For example, estimation accuracy can be further improved when a two-dimensional coordinate system is formed by generating reference state data for wafer chuck heights of 0 mm, 0.03 mm, 0.06 mm, and 0.1 mm at wafer chuck temperatures of 100°C, 90°C, 80°C, and 70°C, respectively.

[0324] On the other hand, when the independence between the selected N elements is strong, the improvement in estimation accuracy decreases as the dimension of the coordinate system increases. That is, as mentioned above, if the value of one element changes at a first ratio while the value of another element changes at a second ratio or less, the estimation accuracy will be similar regardless of the dimension of the coordinate system. In fact, "ACP valve opening rate" and "wafer chuck height" are factors with strong independent relationships. In this case, it was found that when the "ACP valve opening rate" is 100% and the "wafer chuck height" is 0.1 mm, when the reference state data is configured in the one-dimensional coordinate system of "wafer chuck height", even when the "ACP valve opening rate" is 80%, 60%, 40%, and 10%, the "wafer chuck height" shows the highest state similarity at 0.1 mm (this is the actual internal state of the chamber), thereby reducing the effect of increasing the size to some extent. However, although the state similarity is highest at 0.1 mm “wafer chuck height”, the differences between the state similarities at 80%, 60%, 40% and 10% “ACP valve opening rate” are more clearly observed in a two-dimensional coordinate system than in a one-dimensional coordinate system. Therefore, as the dimension of the coordinate system increases, the current internal state of the chamber relative to the “wafer chuck height” can show clearer differences, making it easier to distinguish.

[0325] [Example 6: Monitoring System]

[0326] A monitoring system comprising one or more of the aforementioned monitoring elements may be provided. The monitoring system may be installed in a process apparatus comprising one or more chambers.

[0327] Figure 24 This is a block diagram of a monitoring system according to an embodiment.

[0328] Reference Figure 24 The monitoring system may include one or more monitoring elements 100 and management elements 200. Here, the monitoring element 100 is the aforementioned monitoring element 100, and therefore will not be described in detail again.

[0329] The monitoring system may include a management element 200. The management element 200 can manage the monitoring element 100.

[0330] The management element 200 may include a communication unit 210, a storage unit 220, and a control unit 230.

[0331] The management element 200 can communicate with external elements via the communication unit 210. For example, the management element 200 can obtain information about the current internal state of the chamber from the monitoring element 100 via the communication unit 210. As another example, the management element 200 can transmit information about the current internal state of the chamber to external elements, such as process equipment or a manufacturing plant, via the communication unit 210. Details similar to the communication unit 130 of the monitoring element 100 will not be described further.

[0332] The management element 200 can store various data and programs in the storage unit 220. For example, the storage unit 220 can store information about the current internal state of the chamber. As another example, the storage unit 220 can store reference state data. In embodiments of this disclosure, the storage unit 220 can store Y reference state data.

[0333] The parts similar to the storage unit 150 of the monitoring element 100 will not be described in detail.

[0334] The control unit 230 can perform various information processing and calculations within the management element 200. The control unit 230 can control other components constituting the management element 200. Details similar to the control unit 140 of the monitoring element 100 will not be repeated. For example, the control unit 230 of the management element 200 can control the generation of Y reference state data and their storage in the storage unit 220, just like the control unit 140 of the monitoring element 100. Furthermore, the control unit 230 of the management element 200 can receive current state data from the monitoring element 100 to calculate Y first state similarities and generate Y first state similarity data. Additionally, the control unit 230 of the management element 200 can perform interpolation and / or extrapolation to determine estimated state similarity data and estimate the current internal state of the chamber based on the estimated state similarity data.

[0335] That is, in the operations performed by the monitoring element 100 in [Embodiments 1] to [Embodiments 5] above, all operations except for measuring the frequency characteristics of a specific frequency range by transmitting and receiving radio waves can be performed by the control unit 230 of the management element 200 or controlled by the control unit 230. When the operations described in [Embodiments 1] to [Embodiments 5] are performed or controlled by the control unit 230 of the management element 200, the control unit 230 of the management element 200 can perform or control the operations described in [Embodiments 1] to [Embodiments 5] for each of the plurality of monitoring elements 100.

[0336] Alternatively, when the monitoring element 100 performs or controls the operations described in [Examples 1] to [Examples 5], the control unit 230 of the management element 200 can control the storage unit 220 and the communication unit 210 to transmit information about the Y reference state data stored in the storage unit 220 to the monitoring element 100 according to the request of the monitoring element 100.

[0337] Figure 25 This is a schematic diagram of a monitoring system installed in a process equipment according to an embodiment, wherein the monitoring element is integral. (Refer to...) Figure 25 Each chamber 10 of the process equipment 1 may be equipped with multiple monitoring elements 100. Even in Figure 25 In this case, each of the plurality of monitoring elements 100 may also perform the operations described in [Examples 1] to [Examples 5]. Alternatively, the management element 200 may perform the operations described in [Examples 1] to [Examples 5].

[0338] [Implementation Examples]

[0339] The embodiments 1 to 6 described above are not implemented independently, but can be used in combination. That is, each embodiment should not be regarded as a separate implementation instance, but should be understood as an organically connected single implementation instance.

[0340] For example, the execution entity of the operations in [Example 1] to [Example 5] can vary. When the execution entity is the monitoring element 100, the operations in [Example 1] to [Example 5] can be performed and controlled by the monitoring element 100 or the control unit 140 of the monitoring element 100. When the execution entity is the management element 200, as described in [Example 6], the operations in [Example 1] to [Example 5] can be performed and controlled by the control unit 230 of the management element 200.

[0341] Furthermore, for example, by combining at least some of the embodiments in [Example 1] to [Example 5], the current internal state of the chamber can be estimated. For example, according to [Example 1] and... Figure 5 The relevant description shows that Y reference state data can be generated, and based on [Example 3] and Figure 8 The relevant description allows for estimation of the current internal state of the chamber. In this case, [Example 3] and [Example 5] can be implemented accordingly. Figure 8 The method of interpolation and / or extrapolation is implemented. Furthermore, [Example 3] can be implemented according to the description related to [Equations 1] to [Equations 3] of [Example 2]. Figure 8 Methods for calculating state similarity in [the context of the text].

[0342] As another example, based on [Example 1] and Figure 5 The relevant description shows that Y reference state data can be generated, and according to [Example 4], the current internal state of the chamber can be estimated. In this case, the method for estimating the current internal state of the chamber can be applied to... Figure 8 At least some related explanations are provided, as described in [Example 4]. In this case, the interpolation and / or extrapolation method in [Example 4] can be implemented according to [Example 5]. Additionally, the method for calculating state similarity in [Example 4] can be implemented according to the explanations related to [Equations 1] to [Equations 3] of [Example 2].

[0343] The method according to the embodiments can be implemented by processing logic including hardware, firmware, software, or a combination thereof. The method according to the embodiments can be implemented by a processor for executing code stored in a non-transitory computer-readable medium. Examples of non-transitory computer-readable media include: magnetic media, such as hard disks, floppy disks, and magnetic tapes; optical media, such as compact disc ROMs (CD-ROMs) and digital versatile disc ROMs (DVD-ROMs); magneto-optical media, such as floppy disks; and hardware elements, such as ROMs, RAMs, and flash memory, the structure of which is specifically configured to store and execute program instructions.

[0344] Although this disclosure has been described above with reference to embodiments, it is not limited thereto. It will be apparent to those skilled in the art to which this application pertains that various changes or modifications can be made within the spirit and scope of this disclosure, and such changes or modifications fall within the scope of the appended claims.

Claims

1. A method for estimating chamber state using a chamber monitoring element, characterized in that, The method includes: Obtain Y reference state data corresponding to Y coordinates in an N-dimensional coordinate system with each of the N elements as an axis. Where Y is a natural number equal to or greater than 2, and is a portion of the entire coordinate system that can be represented in the N-dimensional coordinate system, and The N elements are selected from M elements that define the state of the chamber, where M is a natural number equal to or greater than 1, N is a natural number equal to or greater than 1, and M is equal to or greater than N. Radio waves of a specific frequency range are transmitted into the interior of the chamber, and radio waves reflected from the interior of the chamber are received. The current state data representing the state of the chamber is generated based on the received radio waves; The Y first state similarities are determined by calculating the similarity between the current state data and each of the Y reference data. Y first-state similarity data are generated by mapping the Y first-state similarities to the Y coordinates; Multiple second-state similarity data of the entire coordinate system are determined by performing at least one of interpolation or extrapolation in the N-dimensional coordinate system based on the Y first-state similarity data, wherein each of the multiple second-state similarity data includes multiple second-state similarities of each of the entire coordinate system. The second state similarity data corresponding to the second state similarity data with the maximum value among the multiple second state similarities included in the multiple second state similarity data is determined as the estimated state similarity data; and The current state of each of the N elements is estimated based on the coordinates included in the estimated state similarity data.

2. The method according to claim 1, characterized in that, Obtaining the Y reference state data includes: The Y reference state data are obtained by performing a first operation on each of the Y coordinates. The first operation includes: The N elements are manually adjusted to correspond to one of the Y coordinates; Transmitting radio waves within the specified frequency range into the interior of the cavity, and receiving radio waves reflected from the interior of the cavity; and Reference state data representing the state of the chamber is generated based on the received radio waves.

3. The method according to claim 2, characterized in that, The remaining elements among the M elements, excluding the N elements, were not manually adjusted.

4. The method according to claim 1, characterized in that, The plurality of second state similarities are determined as the similarity between the current state data and the chamber state when N elements have values ​​corresponding to one of the entire coordinates.

5. The method according to claim 1, characterized in that, Determining the plurality of second-state similarity data includes: The interpolation or extrapolation is performed using a function of dimension Z or greater than Z, where Z is a natural number equal to or greater than 0.

6. The method according to claim 1, characterized in that, The Y coordinates are selected such that the interval between adjacent coordinates in the N-dimensional coordinate system is constant.

7. The method according to claim 1, characterized in that, The Y coordinates are randomly selected in the N-dimensional coordinate system.

8. The method according to claim 1, characterized in that, The Y coordinates are selected in the N-dimensional coordinate system according to the pre-configured pattern.

9. The method according to claim 1, characterized in that, N is a natural number equal to or greater than 2, and the N elements are selected such that the value of one of the N elements changes by a first ratio, and at least one of the remaining N elements changes by a ratio greater than a second ratio.

10. A chamber monitoring element for estimating chamber status, characterized in that, The chamber monitoring element includes: An antenna is configured to transmit radio waves within a specific frequency range into the interior of the cavity and to receive radio waves reflected from the interior of the cavity; A bracket is configured to secure the antenna to the outside or inside of the cavity; A signal processor is configured to apply an electrical signal to the antenna and receive an electrical signal from the antenna; and The controller is configured to control the signal processor and generate state data of the chamber based on the acquired electrical signals. The controller is configured to: Obtain Y reference state data corresponding to Y coordinates in an N-dimensional coordinate system with each of the N elements as an axis. Where Y is a natural number equal to or greater than 2, and is a portion of the entire coordinate system that can be represented in the N-dimensional coordinate system, and The N elements are selected from M elements that define the state of the chamber, where M is a natural number equal to or greater than 1, N is a natural number equal to or greater than 1, and M is equal to or greater than N. The signal processor is controlled to transmit radio waves of a specific frequency range into the interior of the cavity, receive radio waves reflected from the interior of the cavity, and obtain electrical signals based on the received radio waves. The current state data representing the state of the chamber is generated based on the received radio waves; The Y first state similarities are determined by calculating the similarity between the current state data and each of the Y reference data. Y first-state similarity data are generated by mapping the Y first-state similarities to the Y coordinates; Multiple second-state similarity data of the entire coordinate system are determined by performing at least one of interpolation or extrapolation in the N-dimensional coordinate system based on the Y first-state similarity data, wherein each of the multiple second-state similarity data includes multiple second-state similarities of each of the entire coordinate system. The second state similarity data corresponding to the second state similarity data that has the maximum value among the multiple second state similarities included in the multiple second state similarity data is determined as the estimated state similarity data; and The current state of each of the N elements is estimated based on the coordinates included in the estimated state similarity data.

11. The chamber monitoring element according to claim 10, characterized in that, The controller is configured to: The Y reference state data are obtained by performing a first operation on each of the Y coordinates. The first operation includes: The N elements are manually adjusted to correspond to one of the Y coordinates; Transmitting radio waves within the specified frequency range into the interior of the cavity, and receiving radio waves reflected from the interior of the cavity; and Reference state data representing the state of the chamber is generated based on the received radio waves.

12. The chamber monitoring element according to claim 11, characterized in that, The remaining elements among the M elements, excluding the N elements, were not manually adjusted.

13. The chamber monitoring element according to claim 10, characterized in that, The plurality of second state similarities are determined as the similarity between the current state data and the chamber state when N elements have values ​​corresponding to one of the entire coordinates.

14. The chamber monitoring element according to claim 10, characterized in that, The controller is configured to: The interpolation or extrapolation is performed using a function of dimension Z or greater than Z, where Z is a natural number equal to or greater than 0.

15. The chamber monitoring element according to claim 10, characterized in that, The Y coordinates are selected such that the interval between adjacent coordinates in the N-dimensional coordinate system is constant.

16. The chamber monitoring element according to claim 10, characterized in that, The Y coordinates are randomly selected in the N-dimensional coordinate system.

17. The chamber monitoring element according to claim 10, characterized in that, The Y coordinates are selected in the N-dimensional coordinate system according to the pre-configured pattern.

18. The chamber monitoring element according to claim 10, characterized in that, N is a natural number equal to or greater than 2, and the N elements are selected such that the value of one of the N elements changes by a first ratio, and at least one of the remaining N elements changes by a ratio greater than a second ratio.

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