Management system, management method and management program

Abstract

To provide a management system, a management method, and a management program for making a substrate processing device autonomous.SOLUTION: A management system for managing a substrate manufacturing process includes: agent units configured to monitor a state of a substrate processing device that performs the substrate manufacturing process and detect a predetermined event; and transmission paths configured to, when a predetermined event is detected in any one of the agent units, transmit and receive information between the agent units based on the detected event. Therein the one agent unit derives an instruction to the substrate processing device on the basis of the information transmitted and received via the transmission paths so that an index value of the substrate manufacturing process is optimized.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a management system, a management method, and a management program. [Background technology]

[0002] In recent years, various efforts have been made in the field of circuit board manufacturing processes to realize smart factories. Specifically, progress is being made on the development of digital twin technology, in which a management system collects various data (data in the physical space) measured in the circuit board manufacturing process and reproduces the physical space in cyberspace.

[0003] On the other hand, in order to realize smart factories, it is also necessary to build mechanisms for appropriately dealing with various events that occur in the physical space and to make each substrate processing apparatus that performs the substrate manufacturing process autonomous. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2020 / 050072 [Patent Document 2] Special Publication No. 2020-518079 [Patent Document 3] JP 2018-092511 A Summary of the Invention [Problem to be solved by the invention]

[0005] The present disclosure provides a management system, a management method, and a management program for making a substrate processing apparatus autonomous. [Means for solving the problem]

[0006] A management system according to an aspect of the present disclosure has, for example, the following configuration. A management system for managing a substrate manufacturing process, a plurality of agents that monitor a state of a substrate processing apparatus that executes the substrate manufacturing process and detect a predetermined event; a transmission path for transmitting and receiving information between the agents based on a predetermined event detected by any of the agents; The agent derives an instruction for the substrate processing apparatus based on information transmitted and received via the transmission path so that an index value of the substrate manufacturing process is optimized. Effect of the Invention

[0007] According to the present disclosure, it is possible to provide a management system, a management method, and a management program for making a substrate processing apparatus autonomous. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an example of a system configuration of a cyber-physical system including a plurality of substrate processing apparatuses that execute a substrate manufacturing process. [Diagram 2] FIG. 2 is a diagram illustrating an example of a hardware configuration of the management apparatus. [Diagram 3] FIG. 3 is a first diagram illustrating an example of a functional configuration of the cyber-physical system according to the first embodiment. [Figure 4] FIG. 4 is a second diagram illustrating an example of the functional configuration of the cyber-physical system according to the first embodiment. As illustrated in FIG. [Diagram 5] FIG. 5 is a third diagram illustrating an example of a functional configuration of the cyber-physical system according to the first embodiment. As shown in FIG. [Figure 6] FIG. 6 is a diagram illustrating an example of various processes executed in the cyber-physical system according to the first embodiment. [Figure 7] Figure 7 is a diagram showing an overview of the functional configuration of a gas-related digital twin. [Figure 8] Figure 8 is a diagram showing the detailed functional configuration of a gas-related digital twin. [Figure 9A] FIG. 9A is a flowchart showing the flow of the gas flow rate control process. [Figure 9B] FIG. 9B is a flowchart showing the flow of the adjustment process. [Figure 10] FIG. 10 is a diagram illustrating an example of a functional configuration of a cyber-physical system according to the second embodiment. As illustrated in FIG. [Figure 11] FIG. 11 is a diagram illustrating an example of various processes executed in the cyber-physical system according to the second embodiment. [Figure 12] FIG. 12 is a diagram illustrating an example of a functional configuration of a cyber-physical system according to the third embodiment. As illustrated in FIG. [Figure 13] FIG. 13 is a diagram illustrating an example of various processes executed in the cyber-physical system according to the third embodiment. [Figure 14] FIG. 14 is a diagram illustrating an example of the functional configuration of a Fab layer digital twin. [Figure 15] FIG. 15 is a diagram illustrating the detailed functional configuration of a Fab layer digital twin. [Figure 16] FIG. 16 is a diagram showing an example of the contents of conversations transmitted and received between hierarchical levels during production management processing. [Figure 17] FIG. 17 is a flowchart showing the flow of the production management process. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, each embodiment will be described with reference to the accompanying drawings. In this specification and the drawings, components having substantially the same functional configurations are denoted by the same reference numerals, and redundant description will be omitted.

[0010] [First embodiment] <System configuration of cyber-physical system> First, a system configuration of a cyber-physical system including a plurality of substrate processing apparatuses that execute a substrate manufacturing process will be described. Fig. 1 is a diagram showing an example of a system configuration of a cyber-physical system including a plurality of substrate processing apparatuses that execute a substrate manufacturing process.

[0011] As shown in FIG. 1, the cyber-physical system 100 includes server devices 110_1 to 110_3, management devices 120_1 to 120_n, substrate processing devices 130_1 to 130_n, and an administrator terminal 140.

[0012] In the cyber-physical system 100, the server devices 110_1 to 110_3, the management devices 120_1 to 120_n, and the administrator terminal 140 are connected via a network 150 so as to be able to communicate with each other.

[0013] The server devices 110_1-110_3 are devices that control the entire cyber-physical system 100. The server devices 110_1-110_3 perform, for example, manufacturing management, data management, and device management of the substrate manufacturing process executed by each of the substrate processing devices 130_1-130_n, and management of models used in cyberspace by each of the management devices 120_1-120_n.

[0014] The management apparatuses 120_1 to 120_n are connected to the substrate processing apparatuses 130_1 to 130_n, respectively, to form a management system.

[0015] The management devices 120_1 to 120_n have various models that reproduce the functions of the corresponding substrate processing apparatuses 130_1 to 130_n, and form a cyberspace. The management devices 120_1 to 120_n collect data in the physical space acquired by the substrate processing apparatuses 130_1 to 130_n, Grasping the state of the substrate processing apparatuses 130_1 to 130_n, Detection of events occurring in the substrate processing apparatuses 130_1 to 130_n, - Coordination with other management devices to deal with detected events; Instructions to the substrate processing apparatuses 130_1 to 130_n to deal with the detected event; etc., to appropriately deal with various events that occur in the physical space.

[0016] In this manner, the management devices 120_1 to 120_n appropriately handle various events occurring in the substrate processing apparatuses 130_1 to 130_n in cyberspace and derive instructions to the substrate processing apparatuses 130_1 to 130_n. Thus, the management devices 120_1 to 120_n can make the substrate processing apparatuses autonomous.

[0017] The substrate processing apparatuses 130_1 to 130_n are apparatuses that execute a substrate manufacturing process and constitute a physical space. The substrate processing apparatuses 130_1 to 130_n include, for example, an apparatus that executes a film formation process, an apparatus that executes a lithography process, an apparatus that executes an etching process, an apparatus that executes a cleaning process, etc. The substrate processing apparatuses 130_1 to 130_n transmit data in the physical space acquired during the execution of the substrate manufacturing process to the management apparatuses 120_1 to 120_n.

[0018] The administrator terminal 140 is a terminal operated by an administrator who manages the cyber-physical system 100. The administrator terminal 140 is used, for example, when generating various models possessed by the management devices 120_1 to 120_n.

[0019] 1 illustrates a case in which the management devices 120_1 to 120_n and the substrate processing devices 130_1 to 130_n are configured as separate entities in the cyber-physical system 100. However, the management devices 120_1 to 120_n and the substrate processing devices 130_1 to 130_n may be configured as an integrated entity.

[0020] <Hardware configuration of management device> Next, the hardware configuration of the management devices 120_1 to 120_n will be described. Since the management devices 120_1 to 120_n all have the same hardware configuration, they will be collectively described here with reference to Fig. 2. Fig. 2 is a diagram showing an example of the hardware configuration of the management device.

[0021] 2, the management devices 120_1 to 120_n each include a processor 201, a memory 202, an auxiliary storage device 203, an I / F (Interface) device 204, a communication device 205, and a drive device 206. The hardware components of the management devices 120_1 to 120_n are connected to each other via a bus 207.

[0022] The processor 201 has various arithmetic devices such as a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), etc. The processor 201 reads various programs (for example, a management program described later) onto the memory 202 and executes them.

[0023] The memory 202 has a main storage device such as a Read Only Memory (ROM) and a Random Access Memory (RAM). The processor 201 and the memory 202 form a so-called computer, and the processor 201 executes various programs read onto the memory 202, causing the computer to realize various functions.

[0024] The auxiliary storage device 203 stores various programs and various data used when the processor 201 executes the various programs.

[0025] The I / F apparatus 204 is a connection device that connects the substrate processing apparatuses 130_1 to 130_n, which are examples of external apparatuses, with the management apparatuses 120_1 to 120_n.

[0026] The communication apparatus 205 is a communication device for communicating with other apparatuses (in this embodiment, the server apparatuses 110_1 to 110_3, other management apparatuses, the administrator terminal 140, etc.) via the network 150.

[0027] The drive device 206 is a device for setting the recording medium 210. The recording medium 210 here includes media that record information optically, electrically, or magnetically, such as a CD-ROM, a flexible disk, a magneto-optical disk, etc. The recording medium 210 may also include semiconductor memories that record information electrically, such as ROM, flash memory, etc.

[0028] The various programs to be installed in the auxiliary storage device 203 are installed, for example, by setting the distributed recording medium 210 in the drive device 206 and reading out the various programs recorded in the recording medium 210 by the drive device 206. Alternatively, the various programs to be installed in the auxiliary storage device 203 may be installed by being downloaded from a network via the communication device 205.

[0029] <Functional configuration of cyber-physical systems (1)> Next, a description will be given of the functional configuration of the cyber-physical system 100. Fig. 3 is a first diagram showing an example of the functional configuration of the cyber-physical system according to the first embodiment.

[0030] As shown in FIG. 3, a cyberspace 310 formed by the management devices 120_1 to 120_n includes a plurality of digital twins including various models that reproduce the functions of the substrate processing devices 130_1 to 130_n.

[0031] The example of Fig. 3 shows that the multiple digital twins include an entire process-related digital twin 311, an APC / AEC-related digital twin 312, a process recipe-related digital twin 313, and a maintenance-related digital twin 314. The example of Fig. 3 also shows that the multiple digital twins include a transport-related digital twin 315, a gas-related digital twin 316, a temperature-related digital twin 317, a particle-related digital twin 318, and an operation-related digital twin 319.

[0032] 3, each digital twin included in cyberspace 310 is connected to some of the other digital twins via transmission paths (see dotted lines in cyberspace 310), and transmits and receives information between the other digital twins. For example, entire process-related digital twin 311 is connected to APC / AEC-related digital twin 312, maintenance-related digital twin 314, and transportation-related digital twin 315 via respective transmission paths, and transmits and receives information between them.

[0033] In addition, it is assumed that the direction of information transmission and reception between the connected digital twin and the connected digital twin via a transmission path is predefined.

[0034] 3, data in the physical space 330 is input to a specific digital twin contained in the cyberspace 310. This makes it possible for the specific digital twin contained in the cyberspace 310 to grasp a state, detect an event, cooperate with other digital twins, give instructions to the substrate processing apparatus, and the like (hereinafter, these are referred to as "digital twin processing").

[0035] The example in Fig. 3 shows that gas-related digital twin 316 performs digital twin processing by inputting gas flow rate information, temperature information, pressure information, etc. 321 as data in the physical space into gas-related digital twin 316. Note that in the example in Fig. 3, when linking with other digital twins, gas-related digital twin 316 transmits and receives information to and from process recipe-related digital twin 313 and temperature-related digital twin 317.

[0036] 3 shows that gas flow rate information, temperature information, pressure information, etc. 321 are input to the temperature-related digital twin 317 as data in the physical space, and the temperature-related digital twin 317 performs digital twin processing. In the example of FIG. 3, the temperature-related digital twin 317 transmits and receives information to and from the process recipe-related digital twin 313 and the gas-related digital twin 316 when linking with other digital twins.

[0037] 3 shows that particle information 323 is input to the particle-related digital twin 318 as data in the physical space, causing the particle-related digital twin 318 to perform digital twin processing. In the example of FIG. 3, the particle-related digital twin 318 transmits and receives information to and from the maintenance-related digital twin 314 when linking with other digital twins.

[0038] 3 shows that maintenance information 324 and equipment configuration information 325 are input as data in the physical space to the process recipe-related digital twin 313, causing the process recipe-related digital twin 313 to perform digital twin processing. Note that in the example of FIG. 3, when the process recipe-related digital twin 313 cooperates with other digital twins, it transmits and receives information to and from the gas-related digital twin 316, the temperature-related digital twin 317, and the APC / AEC-related digital twin 312.

[0039] 3 shows that maintenance information 324 is input to the maintenance-related digital twin 314 as data in the physical space, causing the maintenance-related digital twin 314 to perform digital twin processing. In the example of FIG. 3, when the maintenance-related digital twin 314 links with other digital twins, it transmits and receives information to and from the particle-related digital twin 318 and the operation-related digital twin 319. Furthermore, when the maintenance-related digital twin 314 links with other digital twins, it transmits and receives information to and from the APC / AEC-related digital twin 312 and the entire process-related digital twin 311.

[0040] Furthermore, the example in Fig. 3 shows that operation-related digital twin 319 performs digital twin processing by inputting operation information as data in physical space into operation-related digital twin 319. Note that in the example in Fig. 3, when linking with other digital twins, operation-related digital twin 319 transmits and receives information to and from maintenance-related digital twin 314 and transportation-related digital twin 315.

[0041] 3 shows that the transportation-related digital twin 315 performs digital twin processing by inputting equipment configuration information 325 as data in the physical space into the transportation-related digital twin 315. In the example of FIG. 3, when the transportation-related digital twin 315 cooperates with other digital twins, it transmits and receives information between the entire process-related digital twin 311 and the operation-related digital twin 319.

[0042] 3 shows that equipment configuration information 325 is input to the APC / AEC-related digital twin 312 as data in the physical space, causing the APC / AEC-related digital twin 312 to perform digital twin processing. In the example of FIG. 3, when the APC / AEC-related digital twin 312 cooperates with other digital twins, it transmits and receives information between the entire process-related digital twin 311, the process recipe-related digital twin 313, and the maintenance-related digital twin 314.

[0043] Meanwhile, the physical space 330 constituted by the substrate processing apparatuses 130_1 to 130_n includes elements for providing data to be input to the cyberspace 310, or elements to which instructions are transmitted from the cyberspace 310.

[0044] The example of Fig. 3 shows that elements for providing data to be input to the cyberspace 310 include a sensor 331, an external measuring device 333, a maintenance information storage unit 334, an apparatus configuration information storage unit 335, and an operation information storage unit 336. The example of Fig. 3 also shows that elements to which instructions are transmitted from the cyberspace 310 include an actuator 332.

[0045] The sensor 331 measures gas flow rate information, temperature information, pressure information, etc. 321. The gas flow rate information, temperature information, pressure information, etc. 321 measured by the sensor 331 is input to the cyberspace 310 as data in the physical space.

[0046] The external measuring device 333 measures the particle information 323. The particle information 323 measured by the external measuring device 333 is input to the cyberspace 310 as data in the physical space. The device for measuring the particle information 323 is not limited to the external measuring device, and may be an internal measuring device installed in the substrate processing apparatuses 130_1 to 130_n. For example, the device may be a device for measuring the state inside the substrate processing apparatuses 130_1 to 130_n through a window provided in the wall of the substrate processing apparatuses 130_1 to 130_n. The device for measuring the particle information 323 may be a device for observing the state on the substrate to be processed, or a device for acquiring the state of the processing space in which the substrate to be processed is processed.

[0047] The maintenance information storage unit 334 stores maintenance information 324 related to maintenance (repair, replacement) of major components of the substrate processing apparatus performed in the physical space 330. The maintenance information 324 stored in the maintenance information storage unit 334 is input to the cyber space 310 as data in the physical space.

[0048] The equipment configuration information storage unit 335 stores equipment configuration information 325 indicating the equipment configuration of each of the substrate processing apparatuses 130_1 to 130_n in the physical space 330. The equipment configuration information 325 stored in the equipment configuration information storage unit 335 is input to the cyber space 310 as data in the physical space.

[0049] The operation information storage unit 336 stores operation information 326 indicating various operations performed on the substrate processing apparatus in the physical space 330. The operation information 326 stored in the operation information storage unit 336 is input to the cyber space 310 as data in the physical space.

[0050] The actuator 332 operates based on instructions from the cyberspace 310. The example of Fig. 3 shows that the actuator 332 operates based on control information 322 (an example of a control value) calculated by the gas-related digital twin 316 and the temperature-related digital twin 317.

[0051] <Functional configuration of cyber-physical systems (2)> Next, as another functional configuration of the cyber-physical system 100, a functional configuration in which the connection mode of the transmission path is different from that in Fig. 3 will be described. Fig. 4 is a second diagram showing an example of the functional configuration of the cyber-physical system according to the first embodiment.

[0052] The difference from Figure 3 is that in Figure 4, among the multiple digital twins, the digital twins other than the entire process-related digital twin 311 are each connected to the entire process-related digital twin 311 via a transmission path.

[0053] For example, the APC / AEC-related digital twin 312 is connected to the entire process-related digital twin 311 via a transmission path, and transmits and receives information between the entire process-related digital twin 311. Also, the process recipe-related digital twin 313 is connected to the entire process-related digital twin 311 via a transmission path, and transmits and receives information between the entire process-related digital twin 311. The same applies to the maintenance-related digital twin 314 to the operation-related digital twin 319.

[0054] <Functional configuration of cyber-physical systems (3)> Next, as another functional configuration of the cyber-physical system 100, a functional configuration in which the connection mode of the transmission path is different from that in Fig. 3 and Fig. 4 will be described. Fig. 5 is a third diagram showing an example of the functional configuration of the cyber-physical system according to the first embodiment.

[0055] The difference between Figures 3 and 4 is that in Figure 5, all of the multiple digital twins are connected to each other via transmission paths.

[0056] For example, the gas-related digital twin 316 is connected via a transmission path to the entire process-related digital twin 311 to the transport-related digital twin 315, and the temperature-related digital twin 317 to the operation-related digital twin 319. In other words, the gas-related digital twin 316 transmits and receives information to and from digital twins other than the gas-related digital twin 316.

[0057] Furthermore, the process recipe-related digital twin 313 is connected via a transmission path to the entire process-related digital twin 311 to the APC / AEC-related digital twin 312 and the maintenance-related digital twin 314 to the operation-related digital twin 319. In other words, the process recipe-related digital twin 313 transmits and receives information to and from digital twins other than the process recipe-related digital twin 313. The same applies to the other digital twins below.

[0058] <Various processes executed in cyber-physical systems> Next, various processes executed in the cyber-physical system 100 will be described. Fig. 6 is a diagram showing an example of various processes executed in the cyber-physical system according to the first embodiment. Note that Fig. 6 shows an example of various processes executed when the connection mode of the transmission path is the connection mode shown in Fig. 3.

[0059] In Fig. 6, the processes shown in thick black frames are examples of processes that are mainly executed by the corresponding digital twins. As shown in Fig. 6, for example, the entire process related digital twin 311 executes index value management processing.

[0060] The index value management process is a process for managing index values ​​for the entire substrate manufacturing process, and the index values ​​include sub-index values ​​such as the yield of the entire substrate manufacturing process, the processing volume per unit time of the entire substrate manufacturing process, and the energy consumption of the entire substrate manufacturing process.

[0061] The entire process related digital twin 311, for example, acquires the sub-index values ​​by transmitting and receiving information to and from other digital twins via a transmission path, and calculates index values ​​for the entire substrate manufacturing process based on the acquired sub-index values. Also, the entire process related digital twin 311 transmits various instructions to the other digital twins so as to optimize the calculated index values.

[0062] The index value management process executed by the entire-process related digital twin 311 is related to various processes executed primarily by other digital twins. In other words, the various processes executed primarily by other digital twins are executed so as to optimize the index values ​​of the entire board manufacturing process.

[0063] The recipe optimization process is a process for optimizing a process recipe, which includes optimization of the substrate processing quality in a given equipment state (such as the state of wear of parts and the state of deposits on the inner wall of the chamber) as well as optimization of the substrate processing time or the substrate processing amount.

[0064] In the process recipe-related digital twin 313, for example, the current equipment status is grasped by sending and receiving information with other digital twins via a transmission path, and the optimal process recipe for the grasped equipment status is derived from the learning results based on past data.

[0065] The maintenance optimization process is a process for optimizing target parts to be replaced or repaired among the main parts constituting the substrate processing apparatus, and the timing for replacing or repairing the target parts.

[0066] The maintenance-related digital twin 314, for example, grasps the wear state of major parts by sending and receiving information with other digital twins via a transmission path, and predicts the lifespan of major parts based on the future operating status of the equipment. Furthermore, the maintenance-related digital twin 314 derives the optimal timing for replacing or repairing each major part based on the predicted lifespan.

[0067] The transport optimization process is a process for optimizing the transport of substrates, and includes maximizing the amount of processing per unit time by the substrate processing apparatus.

[0068] In the transport-related digital twin 315, for example, by sending and receiving information with other digital twins via a transmission path, the processing volume that the substrate processing apparatus should process is determined, and the optimal transport method for processing the determined processing volume is derived from the learning results based on past data.

[0069] The gas flow rate control process is a process for deriving control information that causes the flow rate of the gas used in substrate processing to reach a predetermined target value.

[0070] In the gas-related digital twin 316, for example, when an event occurs in a substrate processing apparatus, information is sent and received between other digital twins via a transmission path to calculate a processable target value and derive control information to realize the calculated target value.

[0071] 6 are examples of processes executed in the cyber-physical system 100, and each of the digital twins described above may execute processes other than those described above. Furthermore, the subject digital twin is not limited to the one shown in FIG. 6, and any other digital twin whose process is not exemplified in FIG. 6 may be the subject and execute any process.

[0072] Among the various processes shown in FIG. 6, the gas flow rate control process executed by the gas-related digital twin 316 will be described in detail below.

[0073] <Outline of the functional configuration of gas-related digital twin> First, an overview of the functional configuration of a gas-related digital twin that executes gas flow control processing will be described. Fig. 7 is a diagram showing an overview of the functional configuration of a gas-related digital twin. In Fig. 7, cyberspace 310 and physical space 330 show an excerpt of the digital twin and each element related to the gas-related digital twin 316 from the cyberspace 310 and physical space 330 shown in Fig. 3. Also, Fig. 7 shows an excerpt of data and instructions related to the gas-related digital twin 316 from the data input to cyberspace 310 and instructions to the substrate processing apparatus in physical space 330.

[0074] The gas-related digital twin 316 has, as functional blocks for executing the gas flow rate control process, an agent unit 710, a state estimation unit 720, and a model prediction control unit 730. The models of each unit are stored in a model storage unit 740, and are read out from the model storage unit 740 when the gas flow rate control process is executed.

[0075] The agent unit 710 manages the state estimation unit 720 and the model prediction control unit 730. Specifically, the agent unit 710 grasps in real time the state of the substrate processing apparatus estimated by the state estimation unit 720, and monitors whether an event occurs that requires a change in the target value in the gas flow rate control process.

[0076] Furthermore, when the agent unit 710 determines that an event has occurred that requires a change in the target value in the gas flow rate control process, it changes the target value. At this time, the agent unit 710 determines whether or not it is necessary to transmit and receive information with the agent unit of another digital twin (i.e., between agents), and if it is determined that it is necessary, it changes the target value after transmitting and receiving information with the other digital twin. Furthermore, the agent unit 710 notifies the model prediction control unit 730 of the changed target value.

[0077] The state estimation unit 720 acquires gas flow rate information, temperature information, pressure information, etc. 321 measured by the sensor 331, and estimates the state of the gas flow rate control system that is the control target of the gas flow rate control process of the substrate processing apparatus. In addition, the state estimation unit 720 notifies the agent unit 710 of the estimated state of the gas flow rate control system.

[0078] The model prediction control unit 730 is an example of a control unit, and derives control information 322 for realizing the changed target value notified by the agent unit 710. In addition, the model prediction control unit 730 transmits the derived control information 322 as an instruction to the substrate processing apparatus (specifically, the actuator 332 in the physical space 330).

[0079] <Details of the functional configuration of the gas-related digital twin> Next, a detailed description will be given of the functional configuration of the gas-related digital twin 316 that executes the gas flow rate control process. Fig. 8 is a diagram showing the detailed functional configuration of the gas-related digital twin.

[0080] 8, the state estimation unit 720 is an example of an acquisition unit, and has a state estimation model 821. The state estimation model 821 receives the gas flow rate information, temperature information, pressure information, etc. 321 as input, and estimates state information indicating, for example, the state of a gas flow rate control system of the substrate processing apparatus 130_1.

[0081] The agent unit 710 includes an event detection model 811 , a judgment unit 812 , a transmission unit / reception unit 813 , and an analysis model 814 .

[0082] Event detection model 811 is an example of a detection unit, and receives state information estimated by state estimation model 821 as an input to estimate the occurrence of an event that requires a change in the target value in the gas flow rate control process and the type of the event.

[0083] When the event detection model 811 estimates that an event that requires a change in the target value has occurred, the determination unit 812 acquires the type of event from the event detection model 811. Furthermore, the determination unit 812 calculates a target value according to the acquired type of event, notifies the model prediction control unit 730, and determines whether control is possible, thereby determining whether transmission and reception of information with other digital twins is necessary.

[0084] If the determination unit 812 determines that the digital twin is controllable, it determines that it is not necessary to transmit and receive information to and from other digital twins. On the other hand, if the determination unit 812 determines that the digital twin is not controllable, it determines that it is necessary to transmit and receive information to and from other digital twins.

[0085] If it is determined that it is necessary to send and receive information between other digital twins, the judgment unit 812 notifies the transmission / reception unit 813 of the conversation content, including the target value calculated according to the type of event.

[0086] The transmitter / receiver 813 transmits and receives conversation content between the gas-related digital twin 316 and other digital twins (in the case of FIG. 7, the process recipe-related digital twin 313 and the temperature-related digital twin 317).

[0087] For example, the transmission unit / reception unit 813 transmits the conversation content notified by the determination unit 812 to the other digital twin. The transmission unit / reception unit 813 also receives the conversation content (response) transmitted from the other digital twin and inputs it to the analysis model 814. The transmission unit / reception unit 813 also retransmits the conversation content output from the analysis model 814 to the other digital twin. The conversation content transmitted and received by the transmission unit / reception unit 813 between the other digital twin and the transmission unit / reception unit 813 is stored in the information storage unit 815.

[0088] The analysis model 814 takes as input the conversation content (response) notified by the transmitter / receiver 813, and outputs the conversation content to be transmitted to the other digital twin. In the case of gas flow control processing, an acceptable target value or constraint conditions, etc. are transmitted from the other digital twin in response to the target value transmitted to the other digital twin. For this reason, the analysis model 814 calculates a new target value using as input the acceptable target value or constraint conditions, etc. transmitted from the other digital twin.

[0089] In the analysis model 814, by repeatedly sending and receiving conversation content with other digital twins, an appropriate target value is calculated and notified to the model prediction control unit 730.

[0090] Note that the conversation content (response) transmitted from the other digital twin to the transmitter / receiver 813 reflects various instructions transmitted by the entire-process related digital twin 311 to optimize the index values ​​of the entire board manufacturing process. In other words, in the analysis model 814, a target value is calculated to optimize the index values ​​of the entire board manufacturing process.

[0091] The model prediction control unit 730 includes a prediction model 831 , an objective function unit 832 , an optimization unit 833 , and a verification unit 834 .

[0092] Prediction model 831 is a model of the behavior of the gas flow rate control system in physical space 330 (the behavior of sensor 331, actuator 332, and controller (not shown)), and predicts the gas flow rate using control information as an input.

[0093] The objective function unit 832 calculates the error between the gas flow rate predicted by the prediction model 831 and a target value, and notifies the optimization unit 833 of the error.

[0094] The optimization unit 833 searches for control information that reduces the error notified by the objective function unit 832. The optimization unit 833 also inputs the searched control information to the prediction model 831, and again obtains the error between the gas flow rate predicted by the prediction model 831 and the target value. The optimization unit 833 repeats these processes to minimize the error, and derives the optimal control information 322.

[0095] Moreover, the optimization unit 833 transmits the optimal control information 322 as an instruction to the substrate processing apparatus (specifically, to the actuator 332 in the physical space 330).

[0096] The verification unit 834 acquires the optimal control information 322 from the optimization unit 833. Furthermore, the verification unit 834 acquires gas flow rate information provided from the physical space 330 in response to the optimal control information 322 being transmitted as an instruction to the substrate processing apparatus (specifically, the actuator 332 in the physical space 330).

[0097] Furthermore, the verification unit 834 judges the suitability of the control information 322 based on the optimal control information 322 and the acquired gas flow rate information, verifies the prediction accuracy of the prediction model 831, and adjusts the model parameters of the prediction model 831 as necessary. This allows the verification unit 834 to match the prediction model 831 with the behavior of the gas flow rate control system in the physical space 330.

[0098] <Gas flow control process flow> Next, a description will be given of the flow of gas flow rate control processing by the gas-related digital twin 316. Fig. 9A is a flowchart showing the flow of the gas flow rate control processing.

[0099] In step S901, the model predictive control unit 730 acquires a target value, and derives control information according to the acquired target value. The model predictive control unit 730 also transmits the derived control information as an instruction to the substrate processing apparatus in the physical space 330.

[0100] In step S902, the state estimation unit 720 acquires gas flow rate information, temperature information, pressure information, etc. 321 from the physical space 330 as data in the physical space.

[0101] In step S903, the state estimation unit 720 estimates state information indicating the state of the gas flow rate control system of the substrate processing apparatus based on the acquired data in the physical space.

[0102] In step S904, the agent unit 710 monitors, based on the state information estimated by the state estimation unit 720, whether or not an event that requires a change of the target value has occurred.

[0103] In step S905, agent unit 710 determines whether or not an event that requires a change in the target value in the gas flow rate control process has occurred and the type of the event. If it is determined in step S905 that no event has occurred (NO in step S905), the process proceeds to step S912.

[0104] On the other hand, if it is determined in step S905 that an event has occurred (YES in step S905), the process proceeds to step S906.

[0105] In step S906, the agent unit 710 calculates a target value according to the type of the event that has occurred.

[0106] In step S907, the model predictive control unit 730 executes an optimization process to derive control information that minimizes the error from the calculated target value.

[0107] In step S908, the agent unit 710 determines whether or not control is possible based on the error from the target value when the optimization process is executed by the model prediction control unit 730 in step S907.

[0108] Specifically, if the error between the output of the prediction model 831 and the target value when the control information is derived in step S907 is equal to or greater than a threshold value, and control information that minimizes the error is not derived, the agent unit 710 determines that control is not possible. In other words, if the target value cannot be approached even by executing the optimization process, the agent unit 710 determines that control is not possible. On the other hand, if the error between the output of the prediction model 831 and the target value when the control information is derived in step S907 is less than the threshold value, and control information that minimizes the error is derived, the agent unit 710 determines that control is possible. In other words, if the target value is approached by executing the optimization process, the agent unit 710 determines that control is possible.

[0109] In step S909, the agent unit 710 determines whether or not it is necessary to send and receive information to and from other digital twins, based on the result of the controllability determination.

[0110] Specifically, if it is determined in step S908 that control is possible, the agent unit 710 determines that it can approach the target value by itself. For this reason, in step S909, the agent unit 710 determines that it is not necessary to transmit and receive information to and from other digital twins (determines NO in step S909), and proceeds to step S910.

[0111] In step S910, the model predictive control unit 730 transmits the derived new control information to the substrate processing apparatus in the physical space 330 as an instruction.

[0112] On the other hand, if it is determined in step S908 that control is not possible, the agent unit 710 determines that it is not possible to approach the target value by itself. For this reason, in step S909, the agent unit 710 determines that it is necessary to transmit and receive information to and from other digital twins (determines YES in step S909), and proceeds to step S911.

[0113] In step S911, the agent unit 710 performs an adjustment process, transmits and receives information to and from other digital twins, and then derives new control information. Details of the adjustment process are as shown in Fig. 9B. Fig. 9B is a flowchart showing the flow of the adjustment process.

[0114] In step S921, the agent unit 710 transmits the conversation content, including the target value calculated in step S906 of FIG. 9A, to the other digital twin, and receives the conversation content (response) transmitted from the other digital twin.

[0115] In step S922, the agent unit 710 calculates a new target value in the gas flow rate control process by transmitting and receiving conversation content with other digital twins.

[0116] In step S923, the model predictive control unit 730 executes an optimization process to derive control information that minimizes the error with respect to the calculated new target value.

[0117] In step S924, the model prediction control unit 730 transmits the derived new control information as an instruction to the substrate processing apparatus in the physical space 330. Then, the process returns to step S912 in FIG. 9A.

[0118] In step S912, the model prediction control unit 730 acquires, from the physical space 330, data in the physical space 330 required for verifying the prediction model.

[0119] In step S913, the model prediction control unit 730 verifies the prediction accuracy of the prediction model 831 based on the control information transmitted to the physical space 330 and the data acquired from the physical space 330.

[0120] In step S914, the model prediction control unit 730 adjusts the model parameters of the prediction model 831 based on the prediction accuracy of the verified prediction model 831.

[0121] In step S915, agent section 710 determines whether or not to end the gas flow rate control process, and if it determines to continue the gas flow rate control process (NO in step S915), the process returns to step S902.

[0122] On the other hand, if it is determined in step S915 that the gas flow rate control process is to be ended (YES in step S918), the gas flow rate control process is ended.

[0123] <Summary> As is clear from the above description, in the cyber-physical system 100, the management system that forms the cyberspace and manages the substrate manufacturing process in the physical space is as follows: The system has a plurality of digital twins. Each of the digital twins has a plurality of agent units that monitor the status of each substrate processing apparatus and detect the occurrence of a predetermined event. A transmission path that connects multiple digital twins, which, when a specified event is detected in the agent part of one of the digital twins, transmits and receives information between the agent parts of the other digital twins based on the detected event. When a predetermined event is detected, the agent unit derives an instruction for the substrate processing apparatus based on the information transmitted and received via the transmission path so that the index value of the substrate manufacturing process is optimized.

[0124] In this way, the management system according to the first embodiment places an agent unit and a transmission path in cyberspace, and links multiple digital twins to appropriately handle events that occur in the physical space and derive instructions for the substrate processing apparatus. As a result, the management system according to the first embodiment can make each substrate processing apparatus autonomous.

[0125] That is, according to the first embodiment, it is possible to provide a management system that makes the substrate processing apparatus autonomous.

[0126] [Second embodiment] In the above first embodiment, a case has been described in which one cyberspace 310 is formed in a cyber-physical system. However, the number of cyberspaces formed in a cyber-physical system is not limited to one, and multiple cyberspaces may be formed. In addition, digital twins (specifically, agents) included in each of the multiple cyberspaces formed may be connected via a transmission path, and information may be transmitted and received between digital twins in different cyberspaces. The following describes the second embodiment, focusing on the differences from the above first embodiment.

[0127] <Functional configuration of cyber-physical systems> First, a description will be given of the functional configuration of a cyber-physical system according to the second embodiment. Fig. 10 is a diagram illustrating an example of the functional configuration of the cyber-physical system according to the second embodiment.

[0128] As shown in Fig. 10, cyber-physical system 1000 has multiple cyberspaces (cyberspace 310 and cyberspace 1010). Note that in Fig. 10, due to space limitations, the physical spaces corresponding to each of the multiple cyberspaces are omitted, but for example, cyberspace 310 is assumed to be a cyberspace corresponding to physical space 330 in Fig. 3. Also, cyberspace 1010 is assumed to be a cyberspace corresponding to a physical space having a similar configuration to physical space 330 in Fig. 3, which is located in a factory (Fab: Fabrication) different from the physical space 330 in Fig. 3.

[0129] Therefore, the cyberspace 1010 shown in FIG. 10 includes digital twins similar to those of the cyberspace 310 (see the entire process-related digital twin 1011 to the operation-related digital twin 1019).

[0130] In addition, the transmission paths connecting each digital twin in cyberspace 1010 shown in FIG. 10 are assumed to have the same connection configuration as the transmission paths connecting each digital twin in cyberspace 310.

[0131] However, in the case of Fig. 10, the entire process-related digital twin 311 in cyberspace 310 and the entire process-related digital twin 1011 in cyberspace 1010 are connected via a transmission path (see thick dotted line). Also, in the case of Fig. 10, the gas-related digital twin 316 in cyberspace 310 and the gas-related digital twin 1016 in cyberspace 1010 are connected via a transmission path (see thick dotted line).

[0132] In this way, by connecting digital twins contained in different cyberspaces via a transmission path and configuring them to send and receive information between digital twins in other cyberspaces, it becomes possible, for example, to achieve optimization across multiple physical spaces.

[0133] <Various processes executed in cyber-physical systems> Next, various processes executed in the cyber-physical system 1000 according to the second embodiment will be described. Fig. 11 is a diagram showing an example of various processes executed in the cyber-physical system according to the second embodiment. Note that the example of Fig. 11 shows only the processes executed in digital twins (entire process-related digital twin, gas-related digital twin) connected via a transmission path in different cyberspaces.

[0134] 11 , in the cyberspace 310, an entire process related digital twin 311 executes an index value management process. Similarly, in the cyberspace 1010, an entire process related digital twin 1011 executes an index value management process.

[0135] The index value management processing executed in each of the entire-process related digital twins 311 and 1011 has already been explained in the first embodiment above, so explanation thereof will be omitted here.

[0136] However, while sending and receiving information with the entire process related digital twin 311, the entire process related digital twin 311 sends various instructions to other digital twins in cyberspace 310 so as to optimize the index values ​​of the entire substrate manufacturing process.

[0137] Similarly, the entire process-related digital twin 1011 sends various instructions to other digital twins in cyberspace 1010 so as to optimize index values ​​for the entire substrate manufacturing process, while transmitting and receiving information between the entire process-related digital twin 311.

[0138] As shown in FIG. 11, the entire process related digital twin 311 and the entire process related digital twin 1011 may be connected to the entire Fab related digital twin 1101 that governs them via a transmission path.

[0139] The entire Fab related digital twin 1101 manages the entire process related digital twins contained in each of the multiple cyberspaces. Specifically, the entire Fab related digital twin 1101 transmits and receives information to the entire process related digital twins 311, 1011, and transmits various instructions to each digital twin so as to optimize index values ​​for the entire Fab (i.e., across the multiple physical spaces).

[0140] The Fab-wide related digital twin 1101 may be included in either the cyberspace 310 or 1010, or may be included in a cyberspace formed by other devices (for example, server devices 110_1 to 110_3).

[0141] 11, in cyberspace 310, gas-related digital twin 316 performs a gas flow control process. Similarly, in cyberspace 1010, gas-related digital twin 1016 performs a gas flow control process.

[0142] The gas flow rate control processing executed in the gas-related digital twins 316 and 1016, respectively, has already been described in the first embodiment, and therefore will not be described here.

[0143] However, the gas-related digital twin 316 calculates processable target values ​​while sending and receiving information to and from the gas-related digital twin 1016 in addition to the process recipe-related digital twin 313 and the temperature-related digital twin 317.

[0144] Similarly, the gas-related digital twin 1016 calculates processable target values ​​while sending and receiving information to and from the gas-related digital twin 316, in addition to the process recipe-related digital twin 1013 and the temperature-related digital twin 1017.

[0145] As shown in FIG. 11, the gas-related digital twin 316 and the gas-related digital twin 1016 may be connected via a transmission path to an overall gas-related digital twin 1102 that oversees them.

[0146] The gas-related overall digital twin 1102 manages the gas-related digital twins contained in each of the multiple cyberspaces. Specifically, the gas-related overall digital twin 1102 transmits and receives information to the gas-related digital twins 316, 1016, and transmits various instructions to each gas-related digital twin so as to optimize target values ​​for the entire Fab (i.e., across the multiple physical spaces).

[0147] The gas-related overall digital twin 1102 may be included in either the cyberspace 310 or 1010, or may be included in a cyberspace formed by other devices (e.g., server devices 110_1 to 110_3).

[0148] <Summary> As is clear from the above description, in the cyber-physical system 1000, a management system that forms multiple cyberspaces and manages the substrate manufacturing processes in multiple physical spaces is as follows: Each cyberspace has multiple digital twins. Each digital twin has multiple agent units that monitor the status of each substrate processing apparatus and detect the occurrence of a specific event. -Has a transmission path that connects digital twins contained in different cyberspaces. Specifically, when a specific event is detected in the agent part of a digital twin contained in one cyberspace, a transmission path is provided for sending and receiving information between the agent part of a digital twin contained in another cyberspace based on the detected event. When a predetermined event is detected, the agent unit derives an instruction for the substrate processing apparatus based on the information transmitted and received via the transmission path so that the index value of the substrate manufacturing process is optimized. In this case, a digital twin may be further placed that oversees the digital twins contained in each of the multiple cyberspaces, and instructions may be derived to optimize the multiple physical spaces as a whole.

[0149] Thus, the management system according to the second embodiment has a configuration for linking digital twins in different cyberspaces in addition to the configuration of the management system according to the first embodiment, so that the management system according to the second embodiment can automate each substrate processing apparatus so that the entirety of multiple physical spaces is optimized.

[0150] [Third embodiment] In the above first and second embodiments, a digital twin corresponding to each function of the substrate processing apparatus is formed in cyberspace, that is, a digital twin is formed in functional units in cyberspace.

[0151] In contrast, in a third embodiment, a digital twin is formed for each operation unit of hardware that realizes a function in a substrate processing apparatus. The third embodiment will be described below, focusing on the differences from the first and second embodiments.

[0152] <Functional configuration of cyber-physical systems> First, a functional configuration of a cyber-physical system according to the third embodiment will be described. Fig. 12 is a diagram illustrating an example of the functional configuration of the cyber-physical system according to the third embodiment.

[0153] As shown in FIG. 12, in a cyber-physical system 1200, a cyberspace 1210 formed by management devices 120_1 to 120_n includes a plurality of digital twins formed in association with operation units of hardware that realize the functions of the substrate processing apparatus.

[0154] The example of FIG. 12 shows that it includes a Fab layer digital twin 1211 formed on a Fab basis, and equipment layer digital twins 1212_1 and 1212_2 formed on an equipment basis of the substrate processing apparatus.

[0155] The example in Figure 12 also shows that it includes an MC layer digital twin 1213_1 formed in an MC unit, an EC layer digital twin 1213_2 formed in an EC unit, and an external measurement machine layer digital twin 1213_3 formed in an external measurement machine unit.

[0156] Also, the example of Fig. 12 shows that sensor layer digital twins 1214_1 and 1214_4 corresponding to the sensor unit are included. Furthermore, the example of Fig. 12 shows that a transport selection layer digital twin 1214_2 formed in a transport selection unit and a CJ / PJ management layer digital twin 1214_3 formed in a CJ / PJ management unit are included.

[0157] Furthermore, as shown in Fig. 12, each digital twin included in cyberspace 1210 has a hierarchical structure according to the hierarchical relationship of each operation unit. For example, in the case of Fig. 12, in cyberspace 1210, Fab layer digital twin 1211 corresponding to Fab is placed in the highest hierarchy.

[0158] In addition, the substrate processing apparatuses 130_1 and 130_2 arranged in the Fab are Equipment layer digital twin 1212_1, · Equipment Layer Digital Twin 1212_2, are placed at the second hierarchical level in the cyberspace 1210.

[0159] In addition, the MC layer 1240, the EC layer 1250, and the external measurement device layer 1260 arranged in the substrate processing apparatus 130_1 are ·MC Layer Digital Twin 1213_1, ·EC Layer Digital Twin 1213_2, ·External measurement device layer digital twin 1213_3, are placed at the third hierarchical level in the cyberspace 1210.

[0160] Furthermore, a sensor layer digital twin 1214_1 corresponding to the sensor layer 1241 arranged in the MC layer 1240 is arranged in the fourth hierarchical layer in the cyberspace 1210. Further, a transport selection layer digital twin 1214_2 and a CJ / PJ management layer digital twin 1214_3 corresponding to the transport selection layer 1251 and the CJ / PJ management layer 1252 arranged in the EC layer 1250 are each arranged in the fourth hierarchical layer in the cyberspace 1210. Furthermore, a sensor layer digital twin 1214_4 corresponding to the sensor layer 1261 arranged in the external measuring device layer 1260 is arranged in the fourth hierarchical layer in the cyberspace 1210.

[0161] As shown in FIG. 12, information about the behavior unit arranged at the lowest hierarchical level in the physical space is input to the lowest hierarchical level in the cyberspace 1210 (the fourth hierarchical level in the example of FIG. 12).

[0162] Specifically, sensor layer information 1221 is input to the sensor layer digital twin 1214_1 as information regarding the sensor layer 1241 arranged in the MC layer 1240 of the substrate processing apparatus 130_1.

[0163] Moreover, as information regarding the transport selection layer 1251 arranged in the EC layer 1250 of the substrate processing apparatus 130_1, transport selection layer information 1222 is input to the transport selection layer digital twin 1214_2. Moreover, as information regarding the CJ / PJ management layer 1252 arranged in the EC layer 1250 of the substrate processing apparatus 130_1, CJ / PJ management layer information 1223 is input to the CJ / PJ management layer digital twin 1214_3.

[0164] Furthermore, sensor layer information 1224 is input to the sensor layer digital twin 1214_4 as information regarding the sensor layer 1261 arranged in the external measurement device layer 1260 of the substrate processing apparatus 130_1.

[0165] Furthermore, as shown in FIG. 12, digital twins located at hierarchies other than the lowest hierarchical level in cyberspace 1210 (in the example of FIG. 12, the highest hierarchical level, the second hierarchical level, and the third hierarchical level) each have operation information of the corresponding action unit input thereto.

[0166] For example, Fab operation information 1231 is input into the Fab layer digital twin 1211, equipment operation information 1232 is input into the equipment layer digital twin 1212_1, and equipment operation information 1233 is input into the equipment layer digital twin 1212_2. In addition, MC operation information 1234 is input into the MC layer digital twin 1213_1, EC operation information 1235 is input into the EC layer digital twin 1213_2, and measuring instrument operation information 1236 is input into the external measuring instrument layer digital twin 1213_3.

[0167] Also, as shown in FIG. 12, in cyberspace 1210, a digital twin located at each layer is connected via a transmission path to the digital twin located at the next higher layer and the digital twin located at the next lower layer.

[0168] For example, the equipment layer digital twin 1212_1 located at the second hierarchical level is connected to the Fab layer digital twin 1211, which is a digital twin located at the next higher hierarchical level, via a transmission path. Also, the equipment layer digital twin 1212_1 located at the second hierarchical level is connected to the MC layer digital twin 1213_1 to the external measurement device layer digital twin 1213_3, which are digital twins located at the next lower hierarchical level, via transmission paths. The following connections are made in the same manner, so a description thereof will be omitted here.

[0169] <Various processes executed in cyber-physical systems> Next, a description will be given of various processes executed in the cyber-physical system 1200. Fig. 13 is a diagram showing an example of various processes executed in the cyber-physical system according to the third embodiment.

[0170] As in the above embodiments, the processes enclosed in thick black frames in Fig. 13 are examples of processes that are executed mainly by the corresponding digital twins. As shown in Fig. 13, for example, the Fab layer digital twin 1211 executes production management processing.

[0171] The production management process is a process for managing the throughput of the entire Fab and for managing the throughput allocated to each substrate processing apparatus.

[0172] Fab layer digital twin 1211, for example, calculates the next processing volume to be processed by the entire Fab based on the current operation information (Fab operation information 1231) of the corresponding operation unit (entire Fab), and determines the processing volume to be allocated to each of substrate processing equipment 130_1, 130_2. In addition, Fab layer digital twin 1211 transmits the conversation contents including the determined processing volumes via the transmission path to equipment layer digital twins 1212_1, 1212_2, which are located one hierarchical level lower.

[0173] In addition, in response to sending the conversation content including the determined processing volume, conversation content (response) may be sent from the equipment layer digital twin 1212_1 or 1212_2, which is one hierarchical level lower, to the effect that it is unable to process the determined processing volume.

[0174] In this case, the Fab layer digital twin 1211 changes the processing amount allocated to each of the substrate processing apparatuses 130_1, 130_2. Also, the Fab layer digital twin 1211 transmits the conversation content including the changed processing amount to each of the equipment layer digital twins 1212_1, 1212_2 located one hierarchical level lower.

[0175] In this way, Fab layer digital twin 1211 calculates the next processing volume to be processed by the entire Fab based on the current operation information of the entire Fab, and determines the processing volume to be allocated to each substrate processing apparatus. Also, Fab layer digital twin 1211 changes the allocated processing volume by sending and receiving information to and from the equipment layer digital twin.

[0176] Note that the production management process shown in FIG. 13 is an example of a process executed in the cyber-physical system 1200, and the Fab layer digital twin 1211 may execute processes other than the production management process. Also, the main digital twin is not limited to the Fab layer digital twin 1211, and other digital twins not illustrated in FIG. 13 may be the main body and execute any process.

[0177] However, hereinafter, the production management process executed by the Fab layer digital twin 1211 will be described in detail.

[0178] <Overview of the functional configuration of the Fab layer digital twin> First, an overview of the functional configuration of the Fab layer digital twin that executes the production management process will be described. FIG. 14 is a diagram showing an overview of the functional configuration of the Fab layer digital twin.

[0179] As shown in FIG. 14, the Fab layer digital twin 1211 has an agent unit 1410 and a state estimation unit 1420 as functional blocks for executing the production management process. Note that the models of each unit are stored in the model storage unit 1430 and are read from the model storage unit 1430 when the production management process is executed.

[0180] The agent unit 1410 manages the state estimation unit 1420. Specifically, the agent unit 1410 grasps in real time the state information indicating the state of the corresponding operation unit (the entire Fab) estimated by the state estimation unit 1420, and calculates the processing amount that the entire Fab should process next. Also, the agent unit 1410 determines the processing amount to be assigned to each substrate processing apparatus.

[0181] In addition, the agent unit 1410 transmits the conversation content including the determined processing amount to the device layer digital twins 1212_1 and 1212_2 located one layer below. Furthermore, the agent unit 1410 repeats the transmission and reception of the conversation content with the device layer digital twins 1212_1 and 1212_2 located one layer below to derive an optimal allocation of the processing amount and transmits it to the device layer digital twins 1212_1 and 1212_2.

[0182] The state estimation unit 1420 acquires the current operation information (Fab operation information 1231) of the corresponding operation unit (the entire Fab), and uses the acquired Fab operation information 1231 as an input to estimate the state information indicating the state of the corresponding operation unit (the entire Fab). In addition, the state estimation unit 1420 transmits the estimated state information to the agent unit 1410.

[0183] Note that in FIG. 14, the functional configuration of the Fab layer digital twin is shown. When the production management process is executed, it is assumed that other digital twins also execute the same process under the same functional configuration.

[0184] <Details of the functional configuration of the Fab layer digital twin 1211> Next, the details of the functional configuration of the Fab layer digital twin 1211 that executes the production management process will be described. FIG. 15 is a diagram showing the details of the functional configuration of the Fab layer digital twin.

[0185] As shown in FIG. 15, the state estimation unit 1420 has a state estimation model 1521. The state estimation model 1521 uses the Fab operation information 1231 as an input to estimate the state information indicating the state of the entire Fab. The state information estimated by the state estimation model 1521 includes any information related to the state of the entire Fab.

[0186] The agent unit 1410 has an event detection model 1511, a determination unit 1512, a transmission / reception unit 1513, and an analysis model 1514.

[0187] Event detection model 1511 receives as input the state information estimated by state estimation model 1521 and estimates the occurrence of an event that requires a change in the processing volume that the entire Fab should process next and the type of event.

[0188] When event detection model 1511 estimates that no event has occurred, determination unit 1512 calculates the next processing volume to be processed by the entire Fab based on the current operation information, and also calculates the processing volume to be allocated to each substrate processing apparatus. In addition, determination unit 1512 notifies transmission / reception unit 1513 of the conversation content including the processing volume to be allocated to each substrate processing apparatus.

[0189] At this time, the judgment unit 1512 calculates the throughput to be processed next by the entire Fab and the throughput to be allocated to each substrate processing apparatus so as to optimize the index value of the entire substrate manufacturing process (here, the entire Fab). Note that the index value here is the same as in the first embodiment, and includes sub-index values ​​such as the yield of the entire substrate manufacturing process, the throughput per unit time of the entire substrate manufacturing process, and the energy consumption of the entire substrate manufacturing process.

[0190] Furthermore, when event detection model 1511 estimates that an event has occurred, determination unit 1512 acquires the type of event from event detection model 1511. Furthermore, determination unit 1512 changes the next processing amount to be processed by the entire Fab based on the acquired type of event, and also changes the processing amount to be allocated to each substrate processing apparatus. Furthermore, determination unit 1512 notifies transmission / reception unit 1513 of the conversation contents including the processing amount to be allocated to each substrate processing apparatus.

[0191] The transmitter / receiver 1513 transmits the conversation content notified by the determination unit 1512 to the equipment layer digital twin located one layer lower. The transmitter / receiver 1513 also receives the conversation content (response) transmitted from the equipment layer digital twin located one layer lower, and inputs it to the analysis model 1514. The transmitter / receiver 1513 also transmits the conversation content output from the analysis model 1514 to the equipment layer digital twin located one layer lower.

[0192] In addition, when the transmitter / receiver 1513 transmits and receives conversation content between an equipment layer digital twin located one hierarchical level lower, the transmission and reception is performed in accordance with the inter-hierarchical rules stored in the inter-hierarchical rule memory unit 1515.

[0193] In addition, the contents of the conversation that the transmitter / receiver 1513 transmits and receives between the device layer digital twin, which is located one hierarchical level lower, are stored in the information storage unit 1516.

[0194] The analysis model 1514 takes the conversation content (response) notified by the transmitter / receiver 1513 as input, and outputs the conversation content to be sent to the equipment layer digital twin located one hierarchical level lower. In the case of production management processing, in response to the allocation of processing volume sent to the equipment layer digital twin located one hierarchical level lower, information regarding whether or not it can be executed is sent from one of the equipment layer digital twins located one hierarchical level lower. Therefore, the analysis model 1514 calculates a new allocation of processing volume using the information regarding whether or not it can be executed sent from the equipment layer digital twin located one hierarchical level lower as input.

[0195] In the analysis model 1514, by repeatedly sending and receiving conversation content with the equipment layer digital twin, which is located one hierarchical level lower, the optimal allocation of processing load is derived and transmitted to the equipment layer digital twin, which is located one hierarchical level lower.

[0196] Note that, since the example in Fig. 15 describes the functional configuration of the Fab layer digital twin 1211 located at the highest hierarchical level, the transmitter / receiver 1513 transmits the conversation content only to the digital twin located one hierarchical level lower. However, in the case of a digital twin located at another hierarchical level, the conversation content is transmitted to both the digital twin located one hierarchical level lower and the digital twin located one hierarchical level higher. However, which conversation content is transmitted to which digital twin located at which hierarchical level is determined in accordance with the inter-hierarchical rules stored in the inter-hierarchical rule storage unit 1515.

[0197] <Example of conversations between layers in production management processing> Next, a specific example of the content of conversation transmitted and received between hierarchical layers during production management processing by the Fab layer digital twin 1211 will be described. Fig. 16 is a diagram showing an example of the content of conversation transmitted and received between hierarchical layers during production management processing.

[0198] In step S1601, the Fab layer digital twin 1211 determines the presence or absence of an event from state information estimated based on the Fab operation information 1231, and then calculates the next processing volume to be processed by the entire Fab. The Fab layer digital twin 1211 also calculates the processing volumes to be allocated to the substrate processing apparatuses 130_1 and 130_2. Of these, the Fab layer digital twin 1211 transmits to the equipment layer digital twin 1212_1 the conversation content including the processing volume allocated to the substrate processing apparatus 130_1, "By XX month YY day, equipment 1 should process α units of A."

[0199] In step S1602, in response to sending the conversation content, the Fab layer digital twin 1211 receives "Completed" as the conversation content (response) from the equipment layer digital twin 1212_1.

[0200] Next, in step S1611, the Fab layer digital twin 1211 sends the conversation content including the processing amount allocated to the substrate processing apparatus 130_2, "Equipment 2 should process β units of B by XX month YY date," to the equipment layer digital twin 1212_2.

[0201] In step S1612, the equipment layer digital twin 1212_2 outputs the conversation content to be sent to the MC layer digital twin 1213_1 based on the conversation content sent from the Fab layer digital twin 1211. Specifically, the equipment layer digital twin 1212_2 outputs "Process under condition b" as the conversation content and sends it to the MC layer digital twin 1213_1. It is assumed that at this timing, a problem occurs in the MC layer 1240 (an event that requires a change in the processing amount that the substrate processing apparatus 130_2 should process next).

[0202] In step S1613, the MC layer digital twin 1213_1 detects that an event has occurred that requires a change in the processing volume to be processed next, and sends the conversation content “A problem has occurred” to the equipment layer digital twin 1212_2.

[0203] In step S1614, the equipment layer digital twin 1212_2 derives the amount of processing that the substrate processing apparatus 130_2 can perform based on the conversation content (response) transmitted from the MC layer digital twin 1213_1. As a result, the equipment layer digital twin 1212_2 transmits "Apparatus 2 can only process (β-n) pieces of B" to the Fab layer digital twin 1211 as the conversation content including the derived amount of processing.

[0204] In step S1615, the equipment layer digital twin 1212_2 derives an optimal solution to the trouble based on the conversation content (response) sent from the MC layer digital twin 1213_1. In addition, the equipment layer digital twin 1212_2 sends "Please restore using stock part Z" to the MC layer digital twin 1213_1 as the conversation content including the derived solution.

[0205] Meanwhile, in step S1616, the Fab layer digital twin 1211 changes the processing amounts allocated to the substrate processing apparatuses 130_1 and 130_2 based on the conversation content (response) sent from the equipment layer digital twin 1212_2. Among these, the Fab layer digital twin 1211 sends the following conversation content including the processing amount of the substrate processing apparatus 130_2 after the allocation change to the equipment layer digital twin 1212_2: "By XX month YY day, equipment 2 should process (β-n) units of B."

[0206] In step S1617, the equipment layer digital twin 1212_2 outputs the conversation content to be sent to the MC layer digital twin 1213_1 based on the conversation content sent from the Fab layer digital twin 1211. Specifically, it outputs "Process under condition b'" as the conversation content and sends it to the MC layer digital twin 1213_1.

[0207] In step S1618, in response to sending the conversation content including the processing volume after the allocation change, the Fab layer digital twin 1211 receives the conversation content (response) “Completed” from the equipment layer digital twin 1212_2.

[0208] In step S1621, the Fab layer digital twin 1211 sends the conversation content, including the processing volume after the allocation change, “Device 1, process an additional γ units of A” to the equipment layer digital twin 1212_1.

[0209] In step S1622, in response to sending the conversation content including the processing volume after the allocation change, the Fab layer digital twin 1211 receives the conversation content (response) "Completed" from the equipment layer digital twin 1212_1.

[0210] <Production management process flow> Next, the flow of the production management process will be described. Fig. 17 is a flowchart showing the flow of the production management process. Note that Fig. 17 describes the operation during the production management process by a digital twin located at a predetermined layer other than the highest layer.

[0211] In step S1701, a digital twin located at a specified hierarchical level receives conversation content, including an allocated amount of processing, from a digital twin located at the hierarchical level one level higher.

[0212] In step S1702, a digital twin located at a predetermined hierarchy obtains current operating information of a corresponding operation unit.

[0213] In step S1703, the digital twin located at a predetermined level estimates status information indicating the status of the corresponding action unit based on the acquired operation information.

[0214] In step S1704, the digital twin located at a predetermined hierarchical level monitors, based on the estimated state information, whether or not an event has occurred that requires a change in the processing volume that the corresponding operation unit should process next.

[0215] In step S1705, the digital twin located at a predetermined hierarchical level determines whether or not an event that requires a change in the processing amount has occurred and the type of the event. If it is determined in step S1705 that no event has occurred (NO in step S1705), the process proceeds to step S1708.

[0216] On the other hand, if it is determined in step S1705 that an event has occurred (YES in step S1705), the process proceeds to step S1706.

[0217] In step S1706, the digital twin located at a specified hierarchical level transmits the conversation content, including the event that has occurred and the amount of processing that can be performed, to the digital twin located at the hierarchical level one level higher.

[0218] In step S1707, the digital twin located at a specified hierarchical level receives the processing volume after the allocation has been changed from the digital twin located at the hierarchical level one level higher.

[0219] In step S1708, the digital twin located at a given hierarchical level derives the processing amount to be allocated to the digital twin located at the hierarchical level one level lower based on the received processing amount.

[0220] In step S1709, a digital twin located at a specified hierarchical level transmits the conversation content, including the allocated processing amount, to a digital twin located at the hierarchical level one level lower.

[0221] In step S1710, a digital twin located at a predetermined hierarchical level determines whether or not it has received conversation content (response) including an event from a digital twin located at a hierarchical level one level lower. If it is determined in step S1710 that conversation content (response) including an event has been received (YES in step S1710), the process returns to step S1706.

[0222] On the other hand, if it is determined in step S1710 that the conversation content (response) including the event has not been received (NO in step S1710), the process proceeds to step S1711.

[0223] In step S1711, the digital twin located at a predetermined level determines whether or not to end the production management process. If it is determined in step S1711 that the production management process is not to end (NO in step S1711), the process returns to step S1702.

[0224] On the other hand, if it is determined in step S1711 that the production management process is to be ended (YES in step S1711), the production management process is ended.

[0225] <Summary> As is clear from the above description, in the cyber-physical system 1200, the management system that forms the cyberspace and manages the substrate manufacturing process in the physical space is as follows: -Has multiple digital twins. Furthermore, the multiple digital twins correspond to the operation units of the hardware that realize the functions of each substrate processing apparatus, and have a hierarchical structure according to the hierarchical relationship of the operation units. - It has a transmission path connecting multiple digital twins so that information based on an event detected in any one of the digital twins (e.g., a changed allocation of processing volume) can be sent and received between digital twins located at different hierarchical levels.

[0226] In this way, by forming a digital twin corresponding to an operation unit and transmitting and receiving information via a transmission path according to a hierarchical structure, the management system according to the third embodiment can provide the same effects as the first and second embodiments. In addition, the management system according to the third embodiment can efficiently execute specific processes such as production management processes.

[0227] [Other embodiments] In the above first to fourth embodiments, the management devices 120_1 to 120_n are configured as separate management devices, but the management devices 120_1 to 120_n may be configured as an integrated device. In this case, the n management devices may be configured to operate virtually (i.e., as virtual machines) on the integrated device.

[0228] In the above first to fourth embodiments, the management devices 120_1 to 120_n corresponding to the substrate processing apparatuses 130_1 to 130_n have been described as executing the management program by themselves. However, a management device (e.g., the management device 120_1) corresponding to one substrate processing apparatus (e.g., the substrate processing apparatus 130_1) may be configured by, for example, a plurality of computers. The management program may be installed in each of the plurality of computers, so that the management program is executed in a distributed computing format.

[0229] In the above first to fourth embodiments, a method of downloading and installing the management program to the auxiliary storage device 203 of the management devices 120_1 to 120_n via a network has been mentioned as an example of a method of installing the management program to the auxiliary storage device 203 of the management devices 120_1 to 120_n. At this time, no particular reference was made to the download source, but when installing by such a method, the download source may be, for example, a server device that stores the management program in an accessible manner. Furthermore, the server device may be a device on a cloud that accepts access from each of the management devices 120_1 to 120_n via a network and downloads the management program on the condition of payment. In other words, the server device may be a device on a cloud that provides a service of providing the management program.

[0230] In the above first to fourth embodiments, the cyberspace is formed in the management system including the multiple management devices 120_1 to 120_n, but the cyberspace may be formed outside the management system. For example, the cyberspace may be formed in the server devices 110_1 to 110_3.

[0231] In addition, in the first to fourth embodiments, details of the model are not mentioned. However, the model used in the first to fourth embodiments may be, for example, a machine learning model including deep learning. For example, ·RNN (Recurrent Neural Network), ·LSTM (Long Short-Term Memory), ·CNN(Convolutional Neural Network), ·R-CNN (Region based Convolutional Neural Network), ·YOLO (You Only Look Once), ·SSD (Single Shot MultiBox Detector), ·GAN (Generative Adversarial Network), ·SVM(Support Vector Machine), Decision trees, Random Forest It may be any of the above.

[0232] Alternatively, the model may be a model using a genetic algorithm such as GA (Genetic Algorism) or GP (Genetic Programming), or a model trained by reinforcement learning.

[0233] Alternatively, the models used in the first to fourth embodiments may be models obtained by general statistical analysis other than deep learning, such as Principal Component Regression (PCR), Partial Least Square (PLS), LASSO, ridge regression, linear polynomial, autoregressive model, moving average model, autoregressive moving average model, ARX model, etc. Alternatively, the above models may be used in combination.

[0234] In addition, when training a machine learning model, for example, the data used as "input" in the explanation of Figure 8 and the data to be "estimated" may be obtained in advance, and the respective data may be used as training data, which are "input data" and "correct answer data."

[0235] In addition, although three connection modes have been described in the first embodiment, the connection modes of digital twins are not limited to these. In addition, the connection mode may be changed depending on the processing that each digital twin mainly executes.

[0236] The present invention is not limited to the configurations shown in the above embodiments, combinations with other elements, etc. These points can be changed without departing from the spirit of the present invention, and can be appropriately determined according to the application form.

[0237] This application claims priority based on Japanese Patent Application No. 2020-217779, filed on December 25, 2020, the entire contents of which are incorporated herein by reference. [Explanation of symbols]

[0238] 100: Cyber-Physical Systems 120_1~120_n: Management device 130_1 to 130_n: Substrate processing equipment 310: Cyberspace 330: Physical Space 710: Agent Department 720: State estimation unit 730: Model prediction control unit 811: Event detection model 812: Judgment Department 813: Transmitter / Receiver 814:Analysis model 821: State estimation model 831: Predictive Model 832: Objective function part 833: Optimization Department 834: Verification Department 1000: Cyber-Physical Systems 1010: Cyberspace 1200: Cyber-Physical Systems 1210: Cyberspace 1410: Agent Department 1420: State estimation unit 1511: Event detection model 1512:Judgment Department 1513: Transmitter / Receiver 1514:Analysis model 1521: State estimation model

Claims

1. A management system for managing a substrate manufacturing process, a plurality of agents that monitor a state of a substrate processing apparatus that executes the substrate manufacturing process and detect a predetermined event; a transmission path for transmitting and receiving information between the agents based on a predetermined event detected by any of the agents; The agent derives an instruction for the substrate processing apparatus based on information transmitted and received via the transmission path so that an index value of the substrate manufacturing process is optimized.

2. a model storage unit configured to store a state estimation model for estimating a state of the substrate processing apparatus based on information acquired from the substrate manufacturing process; an acquisition unit that acquires a state of the substrate processing apparatus estimated by inputting information acquired from the substrate manufacturing process into the state estimation model; a detection unit that detects a predetermined event in the substrate processing apparatus from the acquired state of the substrate processing apparatus; The management system according to claim 1 , further comprising:

3. the model storage unit further stores a prediction model that reproduces a control system of the substrate processing apparatus; The management system further comprises: a determination unit that determines whether or not it is necessary to transmit and receive information between the agent and another agent based on the type of the detected event; a transmitting unit that transmits information based on the detected event to another agent connected via the transmission path when it is determined that transmission / reception of information with another agent is necessary; a receiving unit for receiving a response from the other agent in response to the transmission of the information based on the detected event; an information storage unit for storing information transmitted and received between the other agent and the other agent; an optimization unit that optimizes a control value so that the prediction model outputs a target value calculated based on responses from the other agents; a control unit that controls the control system using the optimized control value; The management system according to claim 2 , further comprising:

4. The determination unit is 4. The management system described in claim 3, which determines whether or not control is possible based on the error between the output of the predictive model when the optimization unit optimizes a control value so that the predictive model outputs a target value corresponding to the type of the detected event and the target value corresponding to the type of the detected event, thereby determining whether or not information needs to be sent and received between other agents.

5. The acquisition unit is The management system according to claim 3 , further comprising: a control unit for controlling a substrate processing apparatus by inputting newly acquired information from the substrate manufacturing process into the state estimation model in response to control using the optimized control value, thereby newly acquiring a state of the substrate processing apparatus.

6. The agent further comprises: A verification unit that verifies the prediction accuracy of the prediction model based on the newly acquired information, The verification unit is The management system according to claim 5 , further comprising: a management unit configured to adjust model parameters of the prediction model based on the prediction accuracy.

7. 2. The management system according to claim 1, wherein each of the plurality of agents is connected to all other agents or to a portion of other agents via the transmission path.

8. 2. The management system according to claim 1, wherein a direction of transmission / reception when transmitting / receiving information between each of the plurality of agents and other agents connected by the transmission path is predefined for each connection destination.

9. the plurality of agents are arranged in correspondence with each hierarchical level in a hierarchical structure based on an operation unit of the substrate manufacturing process; 4. The management system according to claim 3, wherein the transmission path connects the plurality of agents such that information based on the detected event is transmitted and received between agents associated with different hierarchical levels.

10. 10. The management system according to claim 9, wherein the plurality of agents further comprises a rule storage unit that stores, for each associated hierarchical level, rules between hierarchical levels when transmitting and receiving information based on the detected event between agents associated with different hierarchical levels.

11. The transmission unit is 11. The management system according to claim 10, further comprising: transmitting information calculated based on information received from an agent associated with another hierarchical level to the agent associated with the other hierarchical level in accordance with the rule between the hierarchical levels.

12. The management system according to claim 3 , wherein the transmission path connects agents contained in different cyberspaces so that information can be transmitted and received between corresponding agents among a plurality of agents contained in different cyberspaces.

13. A method for managing a substrate manufacturing process, comprising: a detection step in which a plurality of agents monitor a state of a substrate processing apparatus that executes the substrate manufacturing process and detect a predetermined event; a transmitting / receiving step of transmitting / receiving information between the agents via a transmission path based on a predetermined event detected in any of the agents, The agent derives an instruction for the substrate processing apparatus based on information transmitted and received via the transmission path so that an index value of the substrate manufacturing process is optimized.

14. The computer of the management system that manages the substrate manufacturing process, a plurality of agents that monitor a state of a substrate processing apparatus that executes the substrate manufacturing process and detect a predetermined event; A program that, when a predetermined event is detected in any of the agents, functions as a transmission path for transmitting and receiving information between the agents based on the detected event, The agent derives an instruction to the substrate processing apparatus based on information transmitted and received via the transmission path so that an index value of the substrate manufacturing process is optimized.

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