Control and monitoring system for a gas delivery system

Abstract

A method for monitoring a semiconductor processing system, the semiconductor processing system including a gas delivery system, a thermal system, and a fluid flow line, the method including obtaining a plurality of operational data from the gas delivery system, the thermal system, or a combination thereof, and determining a performance characteristic of the fluid flow line based on one or more of the plurality of operational data. The method includes identifying one or more locations in a reference virtual model associated with the one or more operational data, and generating a dynamic state model of the fluid flow line based on the reference virtual model, the one or more identified locations, and the determined performance characteristic, wherein the dynamic state model is a digital representation of the fluid flow line.

Description

[0001] Cross-references to related applications

[0002] This application claims priority and benefit to U.S. Provisional Application No. 62 / 930,272, filed November 4, 2019. The disclosure of the above application is incorporated herein by reference. Technical Field

[0003] This disclosure generally relates to semiconductor processing systems having gas delivery systems and gas emission systems, and more particularly to control and monitoring systems for gas delivery systems and gas emission systems. Background Technology

[0004] The statements in this section are provided only as background information in connection with this disclosure and may not constitute prior art.

[0005] Semiconductor processing systems typically include a processing chamber and a gas delivery system for delivering process gases into the processing chamber and for delivering exhaust gases to the outside of the processing chamber. Heaters are usually positioned near the gas lines of the gas delivery system and, in some cases, around the gas lines. As the process gases are delivered from a gas source into the processing chamber via the gas lines, they can be heated to a predetermined temperature to facilitate reaction processes within the processing chamber. As the exhaust gases are delivered out of the processing chamber, they can be heated to facilitate emission reduction processes within the gas emission reduction system.

[0006] However, the heater requires time to generate the heat needed to heat the process gas and / or exhaust gas in the gas line to the desired temperature. Blockages can occur in the gas line when cold spots are present. The condition of the gas flowing in the gas line is often unknown to the operator. As a result, it is typically impossible for the operator to control the heater in a way that reduces the presence of cold spots before a blockage occurs.

[0007] Among other issues, this invention solves problems related to the monitoring of gas pipelines and the slow response of heaters used to heat gases. Summary of the Invention

[0008] This section provides a general overview of this disclosure, rather than a full disclosure of its entire scope or all its features.

[0009] The present disclosure provides a method for monitoring a semiconductor processing system, the semiconductor processing system including a gas delivery system, a thermal system, and a fluid flow line. The method includes obtaining a plurality of operational data from the gas delivery system, the thermal system, or a combination thereof, and determining a performance characteristic of the fluid flow line based on one or more of the plurality of operational data. The method includes identifying one or more locations in a reference virtual model associated with the one or more operational data, and generating a dynamic state model of the fluid flow line based on the reference virtual model, the one or more identified locations, and the determined performance characteristic, wherein the dynamic state model is a digital representation of the fluid flow line.

[0010] In some forms, the method further includes identifying a reference virtual model of the fluid flow line from among a plurality of reference virtual models stored in a database.

[0011] In some forms, the digital representation is one of a two-dimensional image and a three-dimensional image.

[0012] In some forms, the plurality of operational data includes temperature data of a heater, temperature data of the fluid flow line, electrical characteristic data of the heater, pump data of a pump, or a combination thereof.

[0013] In some forms, the electrical characteristic data includes a voltage of the heater, a current of the heater, or a combination thereof.

[0014] In some forms, the performance characteristic includes a fluid flow temperature value based on the temperature data of the heater, the temperature data, or a combination thereof.

[0015] In some forms, the performance characteristic is determined based on a statistical analysis of the operational data.

[0016] In some forms, the statistical analysis is a deviation from a predetermined setpoint, a statistical representation of the operational data as a function of time, or a combination thereof.

[0017] In some forms, the statistical analysis is a statistical representation of a heater region of the thermal system, wherein the heater region includes one or more heaters of a plurality of heaters of the thermal system.

[0018] In some forms, the reference virtual model is a digital representation of the gas delivery system, the thermal system, the fluid flow line, or a combination thereof.

[0019] In some forms, the reference virtual model provides a location of one or more heaters of the thermal system disposed at the fluid flow line, one or more sensors disposed at the fluid flow line, or a combination thereof.

[0020] In certain forms, the dynamic state model is a thermal profile representation of the fluid flow line.

[0021] In some forms, the method further includes displaying the dynamic state model using a display device and causing the display device to selectively display one or more filter user interface elements of the set of performance characteristics in response to user input.

[0022] In some forms, the method further includes generating an operational recommendation for one or more heaters of the thermal system based on one or more precursors of the semiconductor processing system.

[0023] The present disclosure also provides a system for monitoring a semiconductor processing system, the semiconductor processing system including a gas delivery system, a thermal system, and a fluid flow line. The system includes a processor and a non-transitory computer-readable medium including instructions executable by the processor. The instructions include obtaining a plurality of operational data from the gas delivery system, the thermal system, or a combination thereof, and determining a performance characteristic of the fluid flow line based on one or more of the plurality of operational data. The instructions include identifying one or more locations in a reference virtual model associated with the one or more operational data, and generating a dynamic state model of the fluid flow line based on the reference virtual model, the one or more identified locations, and the determined performance characteristic, wherein the dynamic state model is a digital representation of the fluid flow line.

[0024] In some forms, the instructions further include identifying a reference virtual model of the fluid flow line from among a plurality of reference virtual models stored in a database.

[0025] In some forms, the digital representation is one of a two-dimensional image and a three-dimensional image.

[0026] In some forms, the plurality of operational data includes temperature data of the heater, temperature data of the fluid flow line, electrical characteristic data of the heater, pump data of the pump, or a combination thereof.

[0027] In some forms, the electrical characteristic data includes a voltage of the heater, a current of the heater, or a combination thereof.

[0028] In some forms, the performance characteristic includes a fluid flow temperature value based on the temperature data of the heater, the temperature data, or a combination thereof.

[0029] In some forms, the performance characteristic is determined based on a statistical analysis of the operational data.

[0030] In some forms, the statistical analysis is a deviation from a predetermined setpoint, a statistical representation of the operational data as a function of time, or a combination thereof.

[0031] In some forms, the statistical analysis is a statistical representation of a heater region of the thermal system, wherein the heater region includes one or more heaters of a plurality of heaters of the thermal system.

[0032] In some forms, the reference virtual model is a digital representation of a gas delivery system, a thermal system, a fluid flow line, or a combination thereof.

[0033] In some forms, the reference virtual model provides a location of one or more heaters of the thermal system disposed at the fluid flow line, one or more sensors disposed at the fluid flow line, or a combination thereof.

[0034] In certain forms, the dynamic state model is a thermal profile representation of the fluid flow line.

[0035] In some forms, the instructions further include displaying the dynamic state model using a display device and causing the display device to selectively display one or more filter user interface elements of the set of performance characteristics in response to user input.

[0036] In some forms, the instructions further include generating an operational recommendation for one or more heaters of the thermal system based on one or more precursors of the semiconductor processing system.

[0037] Additional areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0038] For the purposes of this disclosure, various forms of the present disclosure will now be described, by way of example only, with reference to the accompanying drawings in which:

[0039] Figure 1 is a functional block diagram of a semiconductor processing system, a thermal control system, and a monitoring system for monitoring operation of the semiconductor processing system in accordance with the teachings of this disclosure;

[0040] Figure 2 is a functional block diagram of a monitoring system in accordance with the teachings of this disclosure; Figure 1

[0041] Figure 3 is a schematic diagram of a user interface of a user interface device in accordance with the teachings of this disclosure;

[0042] Figure 4 is a schematic diagram of a user interface of a user interface device in accordance with the teachings of this disclosure;

[0043] Figure 5 is a schematic diagram of a user interface of a user interface device in accordance with the teachings of this disclosure; and

[0044] Figure 6 is a flowchart illustrating an example control routine in accordance with the teachings of this disclosure;

[0045] ​The drawings described herein are for purposes of illustration only and are not intended to limit the scope of the present disclosure in any way. DETAILED DESCRIPTION

[0046] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features.

[0047] Reference Figure 1 FIG. 1 shows a system 5 including a semiconductor processing system 10, a monitoring system 30 for monitoring operation of the semiconductor processing system 10, a thermal control system 120, and a user interface device 130. In one form, components of the monitoring system 30, the semiconductor processing system 10, the thermal control system 120, and the user interface device 130 are communicably coupled using a wired communication protocol and / or a wireless communication protocol (e.g., a Bluetooth-type protocol, a cellular protocol, a wireless fidelity (Wi-Fi) type protocol, a near-field communication (NFC) protocol, an ultra-wideband (UWB) protocol, etc.).

[0048] In one form, the semiconductor processing system 10 generally includes a process chamber 12, a semiconductor control system 13, a gas delivery system 14, and a thermal system 16. In one form, the gas delivery system 14 includes a gas source 18, a gas supply line 20 for delivering process gas from the gas source 18 to the process chamber 12, a gas abatement system 22, and an exhaust line 24 for delivering exhaust gas (e.g., unused process gas and byproducts) from the process chamber 12 to the gas abatement system 22. In one form, process gases used in semiconductor wafer processing can be toxic, pyrophoric, or corrosive (e.g., ammonia, silane, argon, arsine, and / or phosphine, among other gases). In some forms, unused process gas and hazardous byproducts are delivered to the gas abatement system 22, where the unused process gas and byproducts are cleaned and neutralized before being released into the environment. Hereinafter, process gas and exhaust gas can be collectively referred to as “gas”.

[0049] In one form, the thermal system 16 includes a plurality of heaters 25 disposed at different locations along the gas supply line 20 and the exhaust line 24 to heat the gas flowing in the gas supply line 20 and the exhaust line 24. In one form, the plurality of heaters 25 are flexible heaters wrapped around the gas supply line 20 and the exhaust line 24 to heat the gas therein. In another example, the plurality of heaters 25 are cartridge heaters disposed to directly heat the gas flowing through the gas supply line 20 and the exhaust line 24. Heating the gas as it is delivered to the processing chamber 12 and the gas abatement system 22 facilitates wafer processing in the processing chamber 12 and exhaust gas processing in the gas abatement system 22. Additionally, heating the gas inhibits the deposition of contaminants along the walls of the gas supply line 20 and the exhaust line 24 and thus inhibits plugging in the gas supply line 20 and the exhaust line 24. In one form, the plurality of heaters 25 are independently controlled by the thermal control system 120.

[0050] In one form, the thermal system 16 includes a plurality of thermal sensors 26 for measuring thermal system data including, but not limited to, the temperature of the heaters 25, electrical property data of the heaters 25 (e.g., voltage, current, electrical power, and / or resistance of the heaters 25), etc. The plurality of thermal sensors 26 can include thermocouples, resistance temperature detectors, infrared cameras, current sensors, and / or voltage sensors, etc.

[0051] In one form, the plurality of heaters 25 can generate performance characteristics instead of or in addition to one or more thermal sensors 26 that generate performance characteristics. As an example, the heaters 25 are provided as two-wire heaters that include one or more resistive heating elements that operate as sensors to measure the average temperature of the resistive heating elements based on the resistance of the resistive heating elements. More particularly, such two-wire heaters are disclosed in U.S. Patent No. 7,196,295, which is commonly owned with the present application, and the contents of which are incorporated herein by reference in their entirety. In a two-wire thermal system, the thermal system 16 is a self-adaptive thermal system that combines heater design with the control of power, resistance, voltage, and current in a customizable feedback control system that limits one or more of these parameters (i.e., power, resistance, voltage, and current) while controlling another parameter. In one form, the controller is configured to monitor at least one of the current, voltage, and power delivered to the resistive heating elements to determine the resistance, and thus the temperature of the resistive heating elements.

[0052] In one form, the gas delivery system 14 includes a plurality of fluid line sensors 27 disposed proximate (i.e., adjacent and / or in the vicinity of) the gas supply line 20 and the exhaust line 24 for measuring fluid line data. As an example, the plurality of fluid line sensors 27 are mounted to the gas supply line 20 and the exhaust line 24 to monitor cold spots that can lead to clogging, heat sinks, and hot spots that can lead to system degradation and downtime. In one form, the fluid line data can include, but is not limited to, temperature, flow rate, and pressure of the gas, and the process gas being used. Accordingly, the fluid line sensors 27 include, but are not limited to, temperature sensors, pressure sensors, flow meters, and gas sensors, among others.

[0053] In one form, the gas delivery system 14 includes a pump sensor 28 disposed proximate a pump 29 of the gas source 18 for measuring pump data, such as temperature and / or pressure of the pump. Accordingly, the pump sensor 28 can include a temperature sensor or other similar sensor configured to measure the temperature of the pump 29. In one form, the operating temperature of the pump can be used to control the temperature generated by the heater 25 located proximate the pump. In particular, when the pump is running hot, the heater next to the pump can provide little or no heat. In one form, the pump 29 is configured to remove exhaust gas from the processing chamber 12 to the gas abatement system 22. In some forms, the pump temperature data can be provided to the semiconductor control system 13 to control the operation of the semiconductor processing system 10.

[0054] In one form, the thermal control system 120 is configured to control the electrical power provided to the thermal system 16 based on a defined control process and / or thermal system commands received from the monitoring system 30 and / or user inputs received from the user interface device 130 (e.g., a human machine interface (HMI)). As an example, the thermal control system 120 can employ a proportional-integral-derivative (PID) control routine, a model predictive control routine, a cascade control routine, or a derivative control routine as the defined control process to adjust the electrical power provided to the thermal system 16, and thus the temperature of at least one of the heaters 25, based on the thermal sensor data. As described herein, a user can also input commands to the thermal system through the user interface device 130 to control the heaters 25.

[0055] In one form, if the heater 25 is a heater having a sufficiently high temperature coefficient of resistance (TCR), the thermal control system 120 is configured to determine based on the resistance of the resistive heating element of the heater 25. As an example, if the heater 25 is a two-wire heater, the thermal control system 20 is provided as a two-wire thermal control system. Typically, in a two-wire system, the resistive heating element is defined by a material that exhibits a change in resistance with a change in temperature, such that the average temperature of the resistive heating element is determined based on the change in resistance of the resistive heating element. In one form, the resistance of the resistive heating element is determined by first measuring the voltage across the heating element and the current through the heating element and then using Ohm's law to determine the resistance. In one form, a resistance-temperature correlation (e.g., an algorithm, a lookup table, etc.) is used to determine the temperature based on the resistance. The two-wire thermal control system is configured to perform one or more control processes to determine the desired power to be applied to the heater. Exemplary two-wire control systems and associated control processes are described in co-pending U.S. Application Serial No. 15 / 624,060, filed June 15, 2017, entitled "Power Converter for a Thermal System," and co-pending U.S. Application Serial No. 16 / 100,585, filed August 10, 2018, and entitled "System and Method for Controlling Power to a Heater," which are commonly owned with the present application and the contents of which are incorporated herein by reference in their entirety.

[0056] In one form, the semiconductor control system 13 is configured to control and includes information for controlling the semiconductor processing system 10. As an example, the semiconductor control system 13 stores precursors and times at which the precursors are introduced into the processing chamber 12 during an atomic layer deposition (ALD) process. As another example, the semiconductor control system 13 includes information indicative of how the heater 25 is to respond to a setpoint adjustment, such as a percentage of power or a cooling rate required to achieve a target setpoint.

[0057] In one form, the thermal control system 120 is configured to provide thermal system data to the monitoring system 30. For example, the system 120 provides an amount of power / energy supplied to the heater 25. If a two-wire control system, the thermal control system 120 is configured to provide the temperature, resistance, voltage, current, and / or power to the monitoring system 30.

[0058] Reference Figure 2The monitoring system 30 includes an information processing module 50, an analysis module 60, a dynamic response module 70, and a dynamic state model generator module 80. It should be readily understood that any of the components of the control system 40 can be disposed at the same location or distributed at different locations (e.g., through one or more edge computing devices) and communicably coupled accordingly. While the dynamic response module 70 is shown as part of the monitoring system 30, it should be understood that the dynamic response module 70 can be implemented in other forms in place of the monitoring system 30 as part of the thermal control system 120.

[0059] In one form, the information processing module 50 is configured to process operational data and / or user inputs received from the user interface device 130 to provide the operational data and / or user inputs to the appropriate modules. The operational data includes pump data, fluid line data, semiconductor control system data, and / or thermal system data. As an example, the information processing module 50 provides user inputs to the dynamic state model generator module 80 and provides operational data to at least one of the analysis module 60, the dynamic response module 70, or the dynamic state model generator module 80.

[0060] In one form, the analysis module 60 is configured to determine performance characteristics of the fluid flow line (i.e., the gas supply line 20 and / or the exhaust line 24), the thermal system 16, and / or the gas source 18 by performing statistical analysis on one or more operational data. The statistical analysis can include, but is not limited to, a deviation from a predetermined setpoint (as a percentage or a value), a statistical representation of the operational data as a function of time (e.g., mean, median, standard deviation, variance, minimum, maximum, and other statistical representations), a statistical representation of the heater zones of the thermal system, and the like.

[0061] As an example, based on the temperature of the heaters 25, the analysis module 60 determines a thermal profile representation of the fluid flow line as a performance characteristic. In one form, the thermal profile representation provides a digital temperature value and / or a heat map of the fluid flow line, and the like. In another example, using the power applied to the heaters 25, the analysis module 60 is configured to correlate the temperature of the heaters 25 to the amount of energy applied to the heaters 25. More particularly, the analysis module 60 is configured to track the energy applied to the heaters 25 with the temperature characteristic(s) of the heaters 25, such as the average temperature of the heaters over a period of time and / or the temperature deviation of the heaters based on the measured temperature and the desired temperature setpoint. As another example, the analysis module 60 determines a material buildup within the fluid flow line based on the time required to heat a particular zone of the gas line to the desired temperature indicated by the fluid line data as a performance characteristic.

[0062] As an additional example, the heaters 25 are grouped into multiple zones, and the thermal system data associated with the respective zones is used to determine performance characteristics for that particular zone. In particular, the analysis module 60 performs an analysis for each zone based on the data associated with the respective zone. For example, if a first group of temperature data is associated with a first zone of the fluid line system, the analysis module 60 determines a zone temperature as a performance characteristic based on a statistical representation of the first group of temperature data. In yet another example, the analysis module 60 is configured to determine a zone power based on a statistical representation of electrical characteristics (e.g., power, current, voltage, energy, etc.) of the heaters of the first zone. While specific examples are provided with respect to temperature and energy data, the analysis module 60 is configured to employ other types of operational data (such as pump data) to perform similar statistical analyses. As a further example, the analysis module 60 can determine data related to the pumps 29 and to the abatement of exhaust gases in the gas abatement system 22 based on temperature data from the pump sensors 28.

[0063] In one form, the dynamic response module 70 receives semiconductor control system data and dynamically provides operational recommendations for the heaters 25 to the thermal control system 120. As an example, the dynamic response module 70 receives semiconductor control system data related to the type of precursor and when the precursor is introduced into the process chamber 12. Employing a predetermined control model and / or algorithm and data from the analysis module 60, the dynamic response module 70 determines an operational recommendation (e.g., a recommended setpoint for the heaters 25) for one or more heaters and provides the recommendation to the thermal control system 120. Example precursors include, but are not limited to, a new wafer introduced into the process chamber, a new gas and / or additional gas introduced into the process chamber, and / or a time for a cleaning cycle. In one form, the predetermined control model and / or algorithm is determined based on historical data and / or experiments that indicate a response of the semiconductor processing system 10 when a given precursor is applied to the system 10. Thus, with the operational recommendations from the dynamic response module 70, the thermal control system 120 can adjust the setpoints of the heaters 25 prior to, for example, a new wafer or process to improve the response of the heaters 25.

[0064] In one form, the dynamic state model generator module 80 is configured to generate a dynamic state model of the fluid flow line that is one of a two-dimensional or three-dimensional image representing the corresponding fluid flow line and performance characteristics determined by the analysis module 60. In one form, the dynamic state model generator module 80 includes a reference virtual model database 90, a rendering module 100, and a user interface module 110.

[0065] In one form, the reference virtual model database 90 includes a plurality of reference virtual models, where each reference virtual model is a digital representation of a corresponding component of the semiconductor processing system 10 and its location. As an example, a first reference virtual model corresponds to a digital representation of the size and location of the gas supply line 20, and a second reference virtual model corresponds to a digital representation of the size and location of the exhaust line 24. Additionally, additional reference virtual models can correspond to the size and / or location of the heater 25, the thermal sensor 26, the processing chamber 12, and / or any other component of the semiconductor processing system 10.

[0066] In one form, the rendering module 100 identifies one or more locations associated with the operational data of one or more of the identified reference virtual models. As an example, the rendering module 100 identifies the location of the thermal sensor 26 and / or the corresponding heater 25 based on the identification information that uniquely identifies the thermal system data of the thermal sensor 26 and / or the corresponding heater 25. In one form, the rendering module 100 generates a dynamic state model based on the reference virtual models, the one or more identified locations, and / or the determined performance characteristics. In one form, the dynamic state model is a two-dimensional image representing the fluid flow lines and performance characteristics (e.g., thermal profile representation) determined by the analysis module 60.

[0067] In one form, the user interface module 110 provides the dynamic state model to the user interface device 130 as a user interface command for display and visualization by the user. In some forms, the user interface module 110 can also provide operational data, statistical analysis, and / or dynamic responses to the user interface device 130 for display and visualization by the user.

[0068] In an example application, the dynamic response module 70 provides operational data, performance characteristics (e.g., statistical analysis), and adjustment recommendations to the rendering module 100. In response, the rendering module 100 generates a dynamic state model based on the reference virtual models, the one or more identified locations associated with the operational data, and the determined performance characteristics. Additionally, the rendering module 100 generates a dynamic response report and user interface elements for controlling the thermal system 14 based on the adjustment recommendations generated by the dynamic response module 70. Subsequently, the user interface module 110 transmits user interface commands to the user interface device 130 to display the dynamic state model, the dynamic response report, and the user interface elements. The user interface elements can enable the user to adjust parameters of the thermal system 14, such as the temperature of at least one of the electrical power provided to the thermal system 16 and the heater 25 by a thermal system command. In some forms, the user interface elements can enable the user to filter the dynamic response report to view only desired operational data of the semiconductor processing system 10.

[0069] Reference Figure 3, showing an example interface 300 generated by the user interface module 110 and displayed by the user interface device 130. The interface 300 includes a dynamic state model 302, which is a two-dimensional virtual image of the fluid flow lines of the semiconductor processing system 10. In some forms, the dynamic state model 302 includes overlaid status regions 304 that selectively output a predetermined color or other distinguishing graphic that indicates whether the corresponding fluid flow line is operating in an intended operating state (e.g., normal operating state) or a non-intended operating state (e.g., abnormal operation). For example, for normal operation, the overlaid status regions 304 can be shown in green, for abnormal operation in red, and when the operating state is within a defined threshold in yellow. In some forms, the interface 300 includes an alert bar element 306 that indicates the type and / or time of an alert associated with a non-intended / below optimal operating state.

[0070] In some forms, the interface 300 includes menu filter elements 310, 312, 314, 316, 318, 320, 322, 324 that, when selected by a user, cause the user interface device 130 to display relevant information associated with the selected filter element. As an example, selecting filter element 310 can cause the user interface device 130 to display Figure 4 The user interface 400 shown in FIG. 4 includes a dynamic state model 402 and status regions 404, 406 that selectively output a predetermined color or other distinguishing graphic that indicates whether the corresponding fluid flow line at the relative location is operating in an intended operating state or a non-intended operating state. In addition, the user interface 400 can include a trend graph 408 that indicates a trend of operating data as a function of time.

[0071] As another example, selecting filter element 324 can cause the user interface device 130 to display Figure 5 The user interface 500 shown in FIG. 5 includes a menu 502 that shows heater region information (e.g., temperature, wattage, voltage, pressure, resistance, etc.) for each heater region of the corresponding fluid flow line. While a particular interface is shown, the user interface can be configured in various suitable ways to provide a virtual image, status of the fluid flow line, and other information.

[0072] Reference is made to Figure 6FIG. 6 shows a routine 600 for monitoring a semiconductor processing system 10 and performed by the monitoring system 30. At 604, the monitoring system 30 obtains a plurality of operational data from a gas delivery system, a thermal system, or a combination thereof. At 608, the monitoring system 30 determines a performance characteristic of a fluid flow line based on the operational data. At 612, the monitoring system 30 identifies one or more locations associated with the operational data in a reference virtual model associated with the fluid flow line. At 616, the monitoring system 30 generates a dynamic state model of the fluid flow line based on the reference virtual model, the one or more identified locations, and the determined performance characteristic.

[0073] The monitoring system 30 described herein enables one to visualize changes in the semiconductor processing system 10 as different process gases flow through the fluid flow line and their impact on the above-mentioned variables. The energy being supplied to the line can be visualized to their respective control areas and the semiconductor processing system 10 can be optimized for efficiency. Additionally, cold spots on the gas supply line 20 or exhaust line 24 that can cause plugging can be identified and located for system maintenance. By plotting the plugging prediction locations, a repair team can locate where the line needs to be torn down and replaced. As an example, thermal data can be collected by the fluid line sensors 27. The dynamic state model generator module 80 compiles and formats the thermal data into a virtual image that can show the thermal data in different colors based on temperature. Thus, an operator can determine whether the temperature is uniform and / or the location of cold spots on the fluid flow line based on the colors.

[0074] Further, the monitoring system 30 described herein performs virtual plotting based on the measured data and statistical analysis thereof to produce a virtual image that provides an operator with a visual representation of the data of interest. Thus, an operator can identify the location of cold spots and possible plugging before it occurs. Additionally, the monitoring system 30 can provide instructions for enhancing the operation of the gas source 18 or for validating the operation of the gas source 18. By using the monitoring system 30 described herein, the visualization of the collected and analyzed data can be used to reduce heat loss and increase efficiency.

[0075] Unless otherwise expressly specified herein, in describing the scope of the present disclosure, all numerical values are to be interpreted in a loose and liberal sense, and expressed to the closest whole number only, with any and all recited numerical properties being understood as being modified by the term "about." Such modification is desired for a variety of reasons, including industrial practice, material, manufacturing and assembly tolerance, and testing capabilities.

[0076] As used herein, the phrase "at least one of A, B, and C" should be interpreted as using the non-exclusive logical "or" as it is represented by the following inclusions: A, B, C, A+B, A+C, B+C, and A+B+C.

[0077] The description of the present disclosure is merely exemplary in nature and, thus, variations that do not depart from the essence of the present disclosure are intended to be within the scope of the present disclosure. Such variations are not to be regarded as a departure from the spirit and scope of the present disclosure.

[0078] In the figures, the direction of the arrows generally indicates the flow of information (such as data or instructions) of interest to the illustration. For example, when elements A and B exchange various information, but the information transmitted from element A to element B is relevant to the illustration, an arrow can point from element A to element B. This one-way arrow does not mean that no other information is transmitted from element B to element A. Further, for the information sent from element A to element B, element B can send a request for the information or a receipt acknowledgment of the information to element A.

[0079] In this application, the term “controller” can refer to, be part of, or include an Application Specific Integrated Circuit (ASIC); a digital, analog, or mixed analog / digital discrete circuit; a digital, analog, or mixed analog / digital integrated circuit; a combination of combinational logic circuits; a field programmable gate array (FPGA); a processor circuit that executes code (shared, dedicated, or group); a memory circuit that stores code executed by the processor circuit (shared, dedicated, or group); other suitable hardware components that provide the described functionality (such as, but not limited to, mobile drives and systems, transceivers, routers, input / output interface hardware, etc.); or a combination of some or all of the above, such as in a system-on-a-chip.

[0080] The term memory is a subset of the term computer-readable medium. The term computer-readable medium as used herein does not encompass transitory propagating signals or electromagnetic waves propagating on a medium such as a carrier wave; thus, the term computer-readable medium can be considered tangible and non-transitory. Non-limiting examples of non-transitory tangible computer-readable media are nonvolatile memory circuits (such as flash memory circuits, erasable programmable read-only memory circuits, or mask read-only circuits), volatile memory circuits (such as static random access memory circuits or dynamic random access memory circuits), magnetic storage media (such as analog or digital magnetic tape or a hard disk drive), and optical storage media (such as CD, DVD, or Blu-ray disk).

[0081] The apparatus and methods described in this application can be implemented partially or wholly by a special purpose computer created by one or more specific functions contained in computer programs executed by a general purpose computer. The functional blocks, flowchart components, and other elements described above serve as software specifications, which can be translated by a skilled artisan or programmer into computer programs by using routine techniques of the trade.

Claims

1. A method for monitoring a semiconductor processing system, the semiconductor processing system comprising a gas delivery system, a thermal system, and fluid flow lines, the method comprising: Multiple operational data are obtained from the gas delivery system, the thermal system, or a combination thereof; The performance characteristics of the fluid flow pipeline are determined based on one or more of the plurality of operational data. Identify one or more locations in the reference virtual model that are associated with the one or more operational data; as well as A dynamic state model of the fluid flow pipeline is generated based on the reference virtual model, the one or more identified locations, and the determined performance characteristics, wherein the dynamic state model is a digital representation of the fluid flow pipeline. The digital representation is one of a two-dimensional image and a three-dimensional image of the fluid flow pipeline, and the digital representation includes at least one state region that graphically indicates the performance characteristics of the fluid flow pipeline.

2. The method of claim 1, further comprising identifying a reference virtual model of the fluid flow pipeline from a plurality of reference virtual models stored in a database.

3. The method according to claim 1, wherein, The multiple operational data include heater temperature data, fluid flow line temperature data, heater electrical characteristic data, pump data, or a combination thereof.

4. The method according to claim 3, wherein, The electrical characteristic data includes the voltage of the heater, the current of the heater, or a combination thereof.

5. The method according to claim 3, wherein, The performance characteristics include fluid flow rate temperature values ​​based on the temperature data of the heater, the temperature data, or a combination thereof.

6. The method according to claim 1, wherein, The performance characteristics are determined based on statistical analysis of the operational data.

7. The method according to claim 6, wherein, The statistical analysis is the deviation from a predetermined set point, the statistical representation of the operational data as a function of time, or a combination thereof.

8. The method according to claim 6, wherein, The statistical analysis is a statistical representation of the heater region of the thermal system, wherein the heater region includes one or more heaters among the plurality of heaters in the thermal system.

9. The method according to claim 1, wherein, The reference virtual model is a digital representation of the gas delivery system, the thermal system, the fluid flow pipeline, or a combination thereof.

10. The method according to claim 1, wherein, The reference virtual model provides the locations of one or more heaters of the thermal system located at the fluid flow line, one or more sensors located at the fluid flow line, or a combination thereof.

11. The method according to claim 10, wherein, The location of the one or more heaters and the one or more sensors is provided based on the identification information of the one or more heaters.

12. The method according to claim 1, wherein, The dynamic state model is a representation of the thermal distribution of the fluid flow pipeline.

13. The method of claim 1, further comprising using a display device to display the dynamic state model and causing the display device to selectively display one or more filter user interface elements of a set of performance characteristics in response to user input.

14. The method of claim 1, further comprising generating operating recommendations for one or more heaters of the thermal system based on one or more precursors of the semiconductor processing system.

15. A system for monitoring a semiconductor processing system, the semiconductor processing system comprising a gas delivery system, a thermal system, and a fluid flow line, the system comprising: processor; as well as A non-transitory computer-readable medium comprising instructions executable by the processor, wherein the instructions include: Multiple operational data are obtained from the gas delivery system, the thermal system, or a combination thereof; The performance characteristics of the fluid flow pipeline are determined based on one or more of the plurality of operational data. Identify one or more locations in the reference virtual model that are associated with the one or more operational data; and A dynamic state model of the fluid flow pipeline is generated based on the reference virtual model, the one or more identified locations, and the determined performance characteristics, wherein the dynamic state model is a digital representation of the fluid flow pipeline. The digital representation is either a two-dimensional image or a three-dimensional image, and the digital representation includes at least one state region that graphically indicates the performance characteristics of the fluid flow pipeline.

16. The system according to claim 15, wherein, The instructions also include identifying a reference virtual model of the fluid flow pipeline from a plurality of reference virtual models stored in a database.

17. The system according to claim 15, wherein, The multiple operational data include heater temperature data, fluid flow line temperature data, heater electrical characteristic data, pump data, or a combination thereof.

18. The system according to claim 17, wherein, The electrical characteristic data includes the voltage of the heater, the current of the heater, or a combination thereof.

19. The system according to claim 17, wherein, The performance characteristics include fluid flow rate temperature values ​​based on the temperature data of the heater, the temperature data, or a combination thereof.

20. The system according to claim 15, wherein, The performance characteristics are determined based on statistical analysis of the operational data.

21. The system according to claim 20, wherein, The statistical analysis is the deviation from a predetermined set point, the statistical representation of the operational data as a function of time, or a combination thereof.

22. The system according to claim 20, wherein, The statistical analysis is a statistical representation of the heater region of the thermal system, wherein the heater region includes one or more heaters among the plurality of heaters in the thermal system.

23. The system according to claim 15, wherein, The reference virtual model is a digital representation of the gas delivery system, the thermal system, the fluid flow pipeline, or a combination thereof.

24. The system according to claim 15, wherein, The reference virtual model provides the locations of one or more heaters of the thermal system located at the fluid flow line, one or more sensors located at the fluid flow line, or a combination thereof.

25. The system according to claim 24, wherein, The location of the one or more heaters and the one or more sensors is provided based on the identification information of the one or more heaters.

26. The system according to claim 15, wherein, The dynamic state model is a representation of the thermal distribution of the fluid flow pipeline.

27. The system according to claim 15, wherein, The instructions also include using a display device to display the dynamic state model and causing the display device to selectively display one or more filter user interface elements of a set of performance characteristics in response to user input.

28. The system according to claim 15, wherein, The instructions also include generating operational recommendations for one or more heaters of the thermal system based on one or more precursors of the semiconductor processing system.

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