Simulation system, simulation method, and simulation program

Abstract

A model generation unit (220) uses log data, which indicates information for each of a plurality of types of control signals input in the past from a control device (310) into a mechanism (320) and a plurality of types of response signals output in the past from the mechanism (320) to the control device (310), to generate a mechanism model (281) having, for each combination of the control signals and the response signals having a causal relationship with one another, time interval information related to a time interval from the time when a change in the value of the control signal occurred to the time when a change in the value of the response signal occurred.

Description

Simulation System, Simulation Method, and Simulation Program

[0001] The present disclosure relates to a technique for simulating the operation timing of equipment.

[0002] Generally, a manufacturing facility is composed of a control device responsible for control and a mechanism responsible for physical processing. Examples of control devices include PLCs, industrial personal computers (IPCs), or general-purpose PCs. PLC is an abbreviation for Programmable Logic Controller. PC is an abbreviation for Personal Computer.

[0003] The control device sends a control signal to the mechanism. Then, when the mechanism completes a predetermined operation, the control device receives a response signal from the mechanism and performs the next control.

[0004] Those who develop or operate such manufacturing equipment may have the following two desires. The first desire is to verify whether the control program is appropriate. The second desire is to verify whether the operation of the mechanism is appropriate.

[0005] For example, there are those who want to complete production within a predetermined time. Such a person may want to confirm whether production can be completed within the predetermined time with the current content of the control program, or whether production can be completed within the predetermined time with the current operation content and settings (such as operation speed) of the mechanism.

[0006] Such verification can be carried out by operating the actual machine of the manufacturing equipment. However, if the actual machine of the manufacturing equipment is in operation, the manufacturing equipment cannot be used. Also, it is desired to suppress the consumption of the manufacturing equipment and resources. Therefore, it may be implemented as an alternative by simulation on a computer.

[0007] To achieve such verification, conventional simulation devices constructed a pseudo-mechanism that received control instructions from control equipment and returned response signals to the control equipment. For example, conventional simulation devices simulated the electrical circuit of the mechanism. By simulating the signal exchange between the control equipment and the mechanism using a pseudo-mechanism, it was possible to verify the operation of the manufacturing equipment. Furthermore, by incorporating a mechanism to change the response time into the pseudo-mechanism, it became possible to verify the operation while taking into account the diversity of the mechanism's operation.

[0008] However, conventional simulation devices required manual configuration of electrical circuits and other components to build a simulated mechanism, which was time-consuming. Furthermore, appropriate settings could not be provided without knowledge of the mechanism's operation. In addition, when changing the response time of a simulated mechanism, it was necessary to manually investigate and condition what response times the actual mechanism could take. For example, it was necessary to manually measure the response time (average, maximum, or minimum values, etc.) using a timer and then determine the conditions that should be applied to the response of the simulated mechanism.

[0009] Japanese Patent Application Publication No. 09-230923

[0010] This disclosure aims to reduce manual labor and enable the simulation of equipment operation timing.

[0011] The simulation system of this disclosure includes a model generation unit that generates a mechanism model having time interval information relating to the time interval from when a change in the value of the control signal occurs until a change in the value of the response signal occurs, for each combination of control signals and response signals that have a causal relationship with each other, using log data that shows information on multiple types of control signals that have been input from a control device to a mechanism in the past and multiple types of response signals that have been output from the mechanism to the control device in the past.

[0012] According to this disclosure, it becomes possible to simulate the timing of equipment operation while reducing the amount of manual work required.

[0013] Configuration diagram of the simulation system 100 in Embodiment 1. Configuration diagram of the simulation device 200 in Embodiment 1. Flowchart showing the operation of the log acquisition unit 210 and the model generation unit 220 in Embodiment 1. Diagram showing an example of log data 291 in Embodiment 1. Diagram showing an example of the configuration of the mechanism model 281 in Embodiment 1. Configuration diagram of the simulation system 100 in Embodiment 2. Flowchart showing the operation of the model setting unit 221 in Embodiment 2. Configuration diagram of the simulation system 100 in Embodiment 3. Configuration diagram of the simulation system 100 in Embodiment 4. Diagram showing an example of the configuration of the simulation system 100 in an embodiment. Hardware configuration diagram of the simulation device 200 in an embodiment.

[0014] In the embodiments and drawings, the same or corresponding elements are denoted by the same reference numeral. The descriptions of elements denoted by the same reference numeral as the described elements are omitted or simplified as appropriate. The arrows in the figures mainly indicate the flow of data or processing.

[0015] Embodiment 1. The simulation system 100 will be described based on Figures 1 to 5.

[0016] ***Configuration Description*** The configuration of the simulation system 100 will be described based on Figure 1. The simulation system 100 is a system for simulating the operation of equipment based on log data of equipment signals.

[0017] The manufacturing equipment 300 is an example of equipment to be simulated (target equipment). The manufacturing equipment 300 comprises a control device 310 and a mechanism 320. In Figure 1, the manufacturing equipment 300 comprises a control device 310 and a plurality of mechanisms 320. The control device 310 is a device that controls the mechanisms 320. For example, a PLC, IPC, or general-purpose PC can be used as the control device 310. The control device 310 controls the operation of the mechanisms 320 according to a control program. The control program describes how to calculate the control signals given from the control device 310 to the mechanisms 320. The control program is prepared in advance by the developer. The mechanism 320 is a device controlled by the control device 310 and performs predetermined physical processing (such as machining or assembly). Examples of mechanisms 320 include various devices, robots, or conveyors. The control device 310 inputs control signals to the mechanisms 320, and the mechanisms 320 operate according to the control signals and output response signals to the control device 310. A series of manufacturing processes are realized through the repeated exchange of control signals from the control device 310 to the mechanism 320 and response signals from the mechanism 320 to the control device 310.

[0018] The simulation system 100 includes a simulation device 200.

[0019] The configuration of the simulation device 200 will be explained based on Figure 2. The simulation device 200 is a computer equipped with hardware such as a processor 201, memory 202, auxiliary storage device 203, communication device 204, and input / output interface 205. These hardware components are connected to each other via signal lines.

[0020] The processor 201 is an integrated circuit (IC) that performs arithmetic operations and controls other hardware. For example, the processor 201 is a CPU, DSP, GPU, or a combination of these. IC stands for Integrated Circuit. CPU stands for Central Processing Unit. DSP stands for Digital Signal Processor. GPU stands for Graphics Processing Unit.

[0021] Memory 202 is a volatile or non-volatile storage device. Memory 202 is also called main memory. For example, memory 202 is RAM. Data stored in memory 202 is saved to auxiliary storage device 203 as needed. RAM is an abbreviation for Random Access Memory.

[0022] The auxiliary storage device 203 is a non-volatile storage device. For example, the auxiliary storage device 203 is a ROM, HDD, flash memory, or a combination thereof. Data stored in the auxiliary storage device 203 is loaded into memory 202 as needed. ROM is an abbreviation for Read Only Memory. HDD is an abbreviation for Hard Disk Drive.

[0023] The communication device 204 is a receiver and transmitter. For example, the communication device 204 is a communication chip or NIC. Communication of the simulation device 200 is performed using the communication device 204. NIC is an abbreviation for Network Interface Card.

[0024] The input / output interface 205 is a port to which input and output devices are connected. For example, the input / output interface 205 is a USB terminal, the input devices are a keyboard and mouse, and the output device is a display. Input and output of the simulation device 200 are performed via the input / output interface 205. USB is an abbreviation for Universal Serial Bus.

[0025] The simulation device 200 includes elements such as a log acquisition unit 210, a model generation unit 220, and a simulation unit 230. These elements are implemented using software.

[0026] The auxiliary storage device 203 stores a simulation program that allows the computer to function as a log acquisition unit 210, a model generation unit 220, and a simulation unit 230. The simulation program is loaded into memory 202 and executed by the processor 201. The auxiliary storage device 203 also stores the operating system (OS). At least a portion of the OS is loaded into memory 202 and executed by the processor 201. The processor 201 executes the simulation program while executing the OS. OS is an abbreviation for Operating System.

[0027] The simulation program data (input data, output data, etc.) is stored in the storage unit 290. Memory 202 functions as the storage unit 290. However, storage devices such as auxiliary storage device 203, registers in the processor 201, and cache memory in the processor 201 may function as the storage unit 290 instead of, or together with, memory 202.

[0028] The simulation program can be recorded (stored) in a computer-readable format on a non-volatile recording medium such as an optical disc or flash memory.

[0029] ***Explanation of Operation*** The procedure for operating the simulation system 100 corresponds to the simulation method. Also, the procedure for operating the simulation system 100 corresponds to the procedure for processing by the simulation program.

[0030] The operation of the log acquisition unit 210 and the model generation unit 220 will be explained based on Figure 3. In step S110, the log acquisition unit 210 acquires log data 291.

[0031] For example, the control device 310 records log data 291, and the log acquisition unit 210 acquires the log data 291 from the control device 310.

[0032] Log data 291 shows information on multiple types of control signals that were previously input from the control device 310 to the mechanism 320, and multiple types of response signals that were previously output from the mechanism 320 to the control device 310. Control signals are signals used to control the mechanism 320. The mechanism 320 operates in accordance with the control signals. Response signals are signals used to respond to the control signals.

[0033] For example, log data 291 shows the values ​​of each control signal and the values ​​of each response signal for each past time point.

[0034] Figure 4 shows an example of log data 291. Log data 291 shows the values ​​of each control signal (Y1, Y2, ...) and each response signal (X1, X2, ...) for each past time point. A value of "0" means "ON" and a value of "1" means "OFF".

[0035] Returning to Figure 3, we will continue the explanation from step S120. In step S120, the model generation unit 220 generates a mechanism model 281 using the log data 291.

[0036] The mechanism model 281 is a model that holds time interval information for each combination of control signals and response signals that have a causal relationship with each other. The model is a type of data.

[0037] Time interval information refers to the time interval (change time interval) between a change in the value of a control signal and a change in the value of a response signal. For example, time interval information shows statistical values ​​of the change time interval (mean, standard deviation, maximum, minimum, etc.).

[0038] Figure 5 shows an example of the configuration of mechanism model 281. The control device 310 uses a memory area to treat signals exchanged between the control device 310 and mechanism 320 as electrical signals. The control device 310 changes the value of the control signal Y1 from "OFF" to "ON". The control signal Y1 is input from the control device 310 to mechanism 320. Mechanism 320 is a conveyor that performs workpiece transport as a predetermined physical process. When the control signal Y1 of "ON" is input to mechanism 320, it drives and transports the workpiece. When the workpiece reaches a predetermined position, the optical sensor of mechanism 320 detects the arrival of the workpiece, and transport is completed. Then, the optical sensor of mechanism 320 changes the value of the response signal X2 from "OFF" to "ON". The response signal X2 is output from the optical sensor of mechanism 320 to the control device 310. The control device 310 records the changes in the value of the control signal Y1 and the value of the response signal X2 as log data 291, along with the time.

[0039] Mechanism model 281 shows the average, standard deviation, maximum, and minimum values ​​of the time interval from when the control signal Y1 changes to "ON" until the response signal X2 changes to "ON". The time interval from when the control signal Y1 changes to "ON" until the response signal X2 changes to "ON" corresponds to the time during which the workpiece is transported.

[0040] Returning to Figure 3, let's continue the explanation. The mechanism model 281 is generated, for example, as follows. First, the model generation unit 220 analyzes the log data 291. For example, the model generation unit 220 analyzes the changes in control signals and response signals that occur repeatedly during the periodic manufacturing process. Next, the mechanism 320 extracts combinations of control signals and response signals that have a causal relationship with each other from the log data 291 based on the analysis results. Next, for each extracted combination, the model generation unit 220 learns the time interval (change time interval) from when a change in the value of the control signal occurs until a change in the value of the response signal occurs. Then, for each extracted combination, the model generation unit 220 generates a model that has the information obtained through learning as time interval information. The generated model is the mechanism model 281.

[0041] In step S130, the model generation unit 220 outputs a mechanism model 281.

[0042] The operation of the simulation unit 230 will be described. The simulation unit 230 uses the mechanism model 281 to simulate the operation of the mechanism 320 and reproduce the timing of signal transmission and reception that occurs between the control device 310 and the mechanism 320.

[0043] The simulation unit 230 outputs a simulation result. For example, the simulation unit 230 displays the simulation result on a display to provide the simulation result to the user. For example, the simulation unit 230 transmits the simulation result to an external system to provide the simulation result to the external system.

[0044] ***Effects of Embodiment 1*** Embodiment 1 aims to reduce the labor of manually constructing a model by learning the operation timing of the mechanism 320 from the log data 291 of the control device 310 and mechanically modeling it. Even when reproducing the operation of the mechanism 320 by changing the response time of the mechanism 320, by using the information related to the response time of the mechanism 320 obtained through learning, the labor of conditioning in the reproduction of the operation of the mechanism 320 is reduced.

[0045] The simulation system 100 learns the operation timing of the mechanism 320 from the log data 291 of the control device 310 and mechanically generates a mechanism model 281. As a result, the user can perform simulation verification that reproduces the operation timing of the mechanism 320 without having to spend the labor of constructing the mechanism model 281 and without having knowledge of the mechanism 320.

[0046] ***Supplementary Explanation of Embodiment 1*** The time interval of signal change can also be represented by a regression model for the change over time. For example, if it is learned from the log data 291 that the time interval of signal change gradually becomes longer, it is also possible to make the mechanism model 281 a model that similarly makes the time interval of signal change longer over time. Specifically, if it is learned from the log data 291 that it extends by 1 second per day, it is also possible to make the mechanism model 281 a model in which the time interval of signal change extends by 1 second during the simulation when one day has passed. Such a regression model is for simulation including the case where the time required for physical processing extends as the actual mechanism 320 deteriorates in performance over time.

[0047] When extracting combinations of control signals and response signals having a causal relationship with each other from the log data 291, depending on the learning method, it is not always possible to narrow down to combinations of control signals and response signals exactly the same as those in the actual machine of the manufacturing facility 300. For example, assume that in addition to the response signal X2 associated with the control signal Y1 in FIG. 5, the response signal X3 from another sensor repeatedly changes from “OFF” to “ON” at a timing close to that of the response signal X2. In this case, depending on the learning method, there is a possibility that it cannot be determined which of the combinations of the control signal Y1 and the response signal X2 and the combination of the control signal Y1 and the response signal X3 has an appropriate causal relationship. In such a case, candidates for combinations of signals having a causal relationship may be presented to the user of the simulation system 100, and the user may be allowed to select an appropriate combination from the combination candidates, and the selected combination may be applied to the mechanism model 281.

[0048] Embodiment 2. Regarding the form of setting the operating conditions of the mechanism 320 during simulation execution, the main differences from Embodiment 1 will be described based on FIGS. 6 and 7.

[0049] ***Configuration Description*** The configuration of the simulation device 200 will be described based on Figure 6. The simulation device 200 further includes an element called a model setting unit 221. The simulation program further causes the computer to function as the model setting unit 221.

[0050] ***Explanation of Operation*** The operation of the model setting unit 221 will be explained based on Figure 7. In step S210, the model setting unit 221 acquires time interval information from the mechanism model 281.

[0051] In step S220, the model setting unit 221 presents the acquired time interval information.

[0052] For example, the model setting unit 221 presents time interval information to the user by displaying it on a screen. In this case, the user refers to the time interval information, decides on the setting for the change time interval when simulating the operation of the mechanism 320, and inputs the decided setting into the simulation system 100.

[0053] For example, the model setting unit 221 presents time interval information to an external system by transmitting the time interval information to the external system. In this case, the external system receives the time interval information and executes a software program using the time interval information as input. This determines the setting of the change time interval when simulating the operation of the mechanism 320. The external system then transmits data (setting data) including the determined setting to the simulation system 100.

[0054] In step S230, the model setting unit 221 receives the setting for the change time interval when simulating the operation of the mechanism 320.

[0055] For example, the model setting unit 221 receives the settings input to the simulation system 100.

[0056] For example, the model setting unit 221 receives the setting data transmitted to the simulation system 100.

[0057] In step S240, the model setting unit 221 stores the received settings. For example, the model setting unit 221 stores the received settings in the mechanism model 281.

[0058] The operation of the simulation unit 230 will now be explained. The simulation unit 230 uses the stored settings as the operating conditions for the mechanism 320 and simulates the operation of the mechanism 320 using the mechanism model 281. This reproduces the timing of signal exchange between the control device 310 and the mechanism 320 when the settings based on the presented time interval information are used as the operating conditions for the mechanism 320 during simulation execution.

[0059] ***Effects of Embodiment 2*** Embodiment 2 makes it possible to provide conditions when simulating the operation timing of mechanism 320.

[0060] The simulation system 100 allows users or external systems to provide operating conditions for the mechanism model 281. This enables simulation verification that considers a variety of operating timings for the mechanism 320.

[0061] For example, the following simulation verifications become possible: (Example 1) If multiple mechanisms 320 have varying operating times, and the time interval between signal changes is at its maximum for all mechanisms 320, will manufacturing be completed within the desired time? (Example 2) If a specific mechanism 320 has its maximum time interval between signal changes for 10 consecutive cycles, will this cause any inconsistencies in the overall operating timing of the manufacturing equipment 300? (Example 3) If the manufacturing equipment 300 stops up during operation due to the slow operation of a mechanism 320, how much faster will the operation of that mechanism 320 need to be sped up to prevent the manufacturing equipment 300 from stopping? (Example 4) If the operation of a certain mechanism 320 is sped up, how much will the overall manufacturing time for the manufacturing equipment 300 be reduced?

[0062] The simulation system 100 presents information on the time intervals of signal changes learned from the log data 291 of the control device 310. Therefore, users and external systems do not need to obtain information on the operating timing of the mechanism 320 by other means. Other methods include observing the actual mechanism 320 in operation and taking measurements with a timer, or searching for the design information of the mechanism 320. However, these methods are time-consuming. Furthermore, manual measurements are prone to errors. Also, even if design information is searched, the actual mechanism 320 may not operate at the timing specified in the design. Therefore, these methods are inferior in terms of accuracy.

[0063] ***Supplement to Embodiment 2*** When simulating using the mechanism model 281, the model setting unit 221 sets the operating timing of the mechanism 320, that is, the time interval of signal change from when the mechanism 320 receives a control signal until it returns a response signal. For this setting, for example, the user of the simulation can provide arbitrary values. In this case, the model setting unit 221 is equipped with a user interface (UI) that accepts input from the user of the simulation. For this setting, for example, an external system can provide arbitrary values. In this case, the model setting unit 221 is equipped with an application programming interface (API) that accepts input from a software program of the external system.

[0064] Users or external systems can provide any value to set the time interval for signal changes. Alternatively, users or external systems can select a value from the mean, maximum, or minimum values ​​shown in the time interval information. Furthermore, users or external systems can select a value using a regression model.

[0065] The mechanism model 281 can be given common settings for multiple manufacturing cycles. For example, it is possible to give the mechanism model 281 a setting such as "in the simulation execution of 10 manufacturing cycles, operate the mechanism 320 with the signal change time interval set to the maximum value in all cycles." In addition, it is possible to give the mechanism model 281 different settings for each cycle for multiple manufacturing cycles.

[0066] Embodiment 3. The mode for simulating the operation of the control device 310 will be explained, mainly based on Figure 8, with respect to the differences from Embodiment 1.

[0067] ***Configuration Description*** The configuration of the simulation device 200 will be described based on Figure 8. The simulation device 200 also stores a control device model 282. The control device model 282 is a model used to simulate the operation of the control device 310. For example, the control device model 282 is provided to the simulation device 200 by a user or an external system.

[0068] ***Explanation of Operation*** The simulation unit 230 simulates the operation of the mechanism 320 using the mechanism model 281, and also simulates the operation of the control device 310 using the control device model 282. This reproduces the timing of signal exchange that occurs between the control device 310 and the mechanism 320.

[0069] The simulation is performed as follows: The simulation unit 230 manages the start of the simulation, the end of the simulation, and the simulation conditions (such as the duration for which the simulation is performed). The simulation unit 230 executes the simulation by coordinating the operation of both the control equipment model 282 and the mechanism model 281.

[0070] The simulation is performed in the following steps. First, the user or an external system provides the simulation device 200 with instructions to start the simulation and the simulation conditions. The simulation conditions include the period for which the simulation will be performed. Next, the simulation unit 230 receives the instructions to start the simulation and the simulation conditions. Then, under the simulation conditions, the simulation unit 230 performs signal exchange between the control device model 282 and the mechanism model 281. Signal exchange means the exchange of control signals and response signals. The control signals are generated by the control device model 282. The response signals are generated by the mechanism model 281, which simulates the timing of operation in response to the control signals. When the simulation for the period given as the simulation conditions is completed, the simulation unit 230 presents the simulation results (such as the time required for simulated manufacturing) to the user or external system. This completes the simulation.

[0071] ***Effects of Embodiment 3*** Embodiment 3 is a configuration in which the mechanism model 281 is linked with the model of the control device 310 to perform a simulation. This makes it possible to simulate the overall operating timing of the manufacturing equipment 300, which combines the control device 310 and the mechanism 320. By providing the control device model 282 to the simulation device 200, the user can use the simulation device 200 to verify the operating timing. In other words, the user can verify whether the control program installed in the control device 310 achieves the appropriate operating timing of the manufacturing equipment 300 without handling the actual control device 310.

[0072] ***Supplement to Embodiment 3*** The control device model 282 is a model that simulates the operating timing of the control device 310. The operating timing of the control device 310 is determined by the control program given to the control device 310. Therefore, a typical example of the control device model 282 is one that executes the control program of the control device 310 itself. However, the control device model 282 may also read and execute a timing chart or the like that describes the operating timing of the control device 310. Alternatively, the control device model 282 may be a model generated by the model generation unit 220 learning log data 291, similar to the mechanism model 281.

[0073] Embodiment 3 may be implemented in combination with Embodiment 2. That is, the simulation device 200 may include a model setting unit 221 and be given the operating conditions for the mechanism 320. Similarly, the operating conditions for the control device 310 may be given via the model setting unit 221.

[0074] Embodiment 4. A method for simulating external factors that affect the operation of at least one of the control device 310 and the mechanism 320 will be explained, mainly based on Figure 9, with respect to differences from Embodiment 3.

[0075] ***Configuration Description*** The configuration of the simulation device 200 will be described based on Figure 9. The simulation device 200 also stores an external model 283. The external model 283 is a model relating to external factors and is used to simulate the behavior of external factors. External factors affect the behavior of at least one of the control equipment 310 and the mechanism 320. Examples of external factors for the manufacturing equipment 300 are people and workpieces. A workpiece is an object (object) that is processed or assembled. For example, the external model 283 is provided to the simulation device 200 by a user or an external system.

[0076] ***Explanation of Operation*** The simulation unit 230 simulates the operation of the control device 310 and the mechanism 320 using the control device model 282 and the mechanism model 281, and also simulates the operation of external factors using the external model 283.

[0077] For example, the simulation unit 230 provides an external factor detection signal to the control device model 282 at a timing determined by the external model 283. The external factor detection signal corresponds to a sensor signal output from a sensor that detects human movement or the loading of a workpiece.

[0078] ***Effects of Embodiment 4*** Embodiment 4 is a configuration in which an external model 283 is linked to the mechanism model 281 and the control equipment model 282 to perform a simulation. The external model 283 represents the timing of operations related to external factors (e.g., people or workpieces) of the manufacturing equipment 300.

[0079] The simulation device 200 is designed to perform simulations that include the timing of operations related to external factors (e.g., people or workpieces) of the manufacturing equipment 300. This makes it possible to verify the timing of operations that may occur on the manufacturing site due to factors other than the manufacturing equipment 300.

[0080] ***Supplement to Embodiment 4*** The external model 283 is a model that simulates the operating timing of the manufacturing equipment 300 related to external factors.

[0081] (First example) External model 283 simulates the timing of the generation of a sensor signal that detects human movement (input timing). When human movement periodically interacts with the sensor, a sensor signal separate from the control signal and response signal exchanged between the control device 310 and the mechanism 320 is provided to the control device 310 as input. Such sensor signal inputs cannot be learned as part of the relationship between control signals and response signals. External model 283 is defined as a method for simulating the timing of the generation of such sensor signals (input timing). External model 283 provides the sensor signal when human movement is detected as input to the control device model 282 at a specific timing in the manufacturing cycle.

[0082] (Second example) External model 283 simulates the timing of loading a workpiece into the manufacturing equipment 300. At the start of the physical process, a workpiece is loaded into the control device 310 from the outside. The workpiece may be loaded manually or by equipment or transport equipment in the preceding process. This loading of workpieces is detected by sensors (such as optical sensors) provided in the manufacturing equipment 300. The timing of workpiece loading occurs independently of the signal exchange between the control device 310 and the mechanism 320. External model 283 is defined as a method for simulating this timing of workpiece loading. External model 283 provides the sensor signal when workpiece loading is detected as input to the control device model 282 at a specific timing in the manufacturing cycle.

[0083] Embodiment 4 may be implemented in combination with Embodiment 2, similar to Embodiment 3. That is, the simulation device 200 may include a model setting unit 221 and be given the operating conditions for the mechanism 320. Similarly, the operating conditions for the control device 310 may be given via the model setting unit 221. Furthermore, the operating conditions for external factors may be given via the model setting unit 221.

[0084] Embodiment 4 may be implemented in combination with Embodiment 1 or Embodiment 2 instead of Embodiment 3. In other words, the operation of the control device 310 does not need to be simulated using the control device model 282.

[0085] ***Supplement to the Embodiment*** In the simulation system 100, the functions of the simulation device 200 may be implemented by multiple devices arranged in a distributed manner. For example, the simulation device 200 may be replaced by a device for managing models and a device for executing simulations. Figure 10 shows an example of the configuration of the simulation system 100. The simulation system 100 includes a model management device 411, a model management device 412, and a simulation execution device 420 instead of the simulation device 200. Each device has a hardware configuration similar to that of the simulation device 200. The model management device 411 is a device for managing the mechanism model 281 and includes a log acquisition unit 210, a model generation unit 220, and a model management unit (not shown). The model management unit transfers the mechanism model 281 to the simulation execution device 420 via a network. The model management device 412 is a device for managing the control equipment model 282 and includes a model management unit (not shown). The model management unit transfers the control equipment model 282 to the simulation execution device 420 via a network. The simulation execution device 420 is a device that executes simulations and includes a simulation unit 230. The simulation unit 230 receives models (281, 282) from model management devices (411, 412) via a network and executes simulations using the received models. Executing simulations requires greater computing power. On the other hand, model generation and model management (editing, etc.) require less computing power than simulation. By distributing the functions, it becomes possible to execute simulations on high-performance machines (e.g., the cloud) and perform model generation and model management on moderately rated machines (e.g., local terminals).

[0086] Based on Figure 11, the hardware configuration of the simulation device 200 will be described. The simulation device 200 includes a processing circuit 209. The processing circuit 209 is hardware that implements a log acquisition unit 210, a model generation unit 220, a model setting unit 221, and a simulation unit 230. The processing circuit 209 may be dedicated hardware, or it may be a processor 201 that executes a program stored in memory 202.

[0087] If the processing circuit 209 is dedicated hardware, the processing circuit 209 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field Programmable Gate Array.

[0088] The simulation device 200 may include multiple processing circuits that replace the processing circuit 209.

[0089] In the processing circuit 209, some functions may be implemented by dedicated hardware, while the remaining functions may be implemented by software or firmware.

[0090] Thus, the functions of the simulation device 200 can be realized through hardware, software, firmware, or a combination thereof.

[0091] Each embodiment is an example of a preferred form and is not intended to limit the technical scope of this disclosure. Each embodiment may be implemented in part or in combination with other embodiments. Procedures described using flowcharts, etc., may be modified as appropriate.

[0092] The "part" of each element of the simulation device 200 may be read as "process," "step," "circuit," or "circuit."

[0093] 100 Simulation system, 200 Simulation device, 201 Processor, 202 Memory, 203 Auxiliary storage device, 204 Communication device, 205 Input / Output interface, 209 Processing circuit, 210 Log acquisition unit, 220 Model generation unit, 221 Model setting unit, 230 Simulation unit, 281 Mechanism model, 282 Control device model, 283 External model, 290 Storage unit, 291 Log data, 300 Manufacturing equipment, 310 Control device, 320 Mechanism, 411 Model management device, 412 Model management device, 420 Simulation execution device.

Claims

1. A simulation system comprising a model generation unit that generates a mechanism model having time interval information relating to the time interval between a change in the value of a control signal and a change in the value of a response signal for each combination of control signals and response signals that have a causal relationship with each other, using log data that shows information on multiple types of control signals that have been input from a control device to a mechanism in the past and multiple types of response signals that have been output from the mechanism to the control device in the past.

2. The simulation system according to claim 1, wherein the model generation unit extracts combinations of control signals and response signals that have a causal relationship with each other from the log data, learns the time interval from when a change in the value of the control signal occurs until a change in the value of the response signal occurs for each extracted combination, and generates a model as the mechanism model that has the information obtained by learning as the time interval information for each extracted combination.

3. The simulation system according to claim 1 or 2, further comprising a model setting unit that presents the time interval information of the mechanism model, receives the time interval setting when simulating the operation of the mechanism, and stores the received setting as the operating conditions of the mechanism when the simulation is executed.

4. The simulation system according to any one of claims 1 to 3, further comprising a simulation unit that simulates the operation of the mechanism using the mechanism model to reproduce the timing of signal exchange between the control device and the mechanism.

5. The simulation system according to claim 4, wherein the simulation unit simulates the operation of the mechanism using the mechanism model and simulates the operation of the control equipment using the control equipment model.

6. The simulation system according to claim 5, wherein the simulation unit simulates the operation of the control device and the mechanism using the control device model and the mechanism model, and simulates the operation of the external factors using an external factors model relating to external factors that affect the operation of at least one of the control device and the mechanism.

7. The simulation system according to claim 4, wherein the simulation unit simulates the operation of the mechanism using the mechanism model and simulates the operation of the external factors using an external factors model relating to external factors that affect the operation of at least one of the control equipment and the mechanism.

8. A simulation method for generating a mechanism model that has time interval information relating to the time interval between a change in the value of a control signal and a change in the value of a response signal for each combination of control signals and response signals that have a causal relationship with each other, using log data that shows information on multiple types of control signals that have been input from a control device to a mechanism in the past and multiple types of response signals that have been output from the mechanism to the control device in the past.

9. A simulation program for causing a computer to execute a model generation process that generates a mechanism model having time interval information relating to the time interval between a change in the value of a control signal and a change in the value of a response signal for each combination of control signals and response signals that have a causal relationship with each other, using log data that shows information on multiple types of control signals that have been input from a control device to a mechanism in the past and multiple types of response signals that have been output from the mechanism to the control device in the past.

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