Simulation system, simulation method, and simulation program

Abstract

The model generation unit (220) uses log data that shows information on multiple types of control signals previously input from the control device (310) to the mechanism (320) and multiple types of response signals previously output from the mechanism (320) to the control device (310) to generate a mechanism model (281) that has time interval information relating to the time interval from when a change in the value of the control signal occurs until when 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.

Description

Technical Field

[0001] This disclosure relates to a technology for simulating the operation timing of equipment.

Background Art

[0002] Generally, manufacturing equipment is composed of a control device responsible for control and a mechanism responsible for physical processing. Examples of control devices include PLCs, industrial PCs (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 may be someone who wants 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 manufacturing equipment. However, if the actual manufacturing equipment is in operation, the manufacturing equipment cannot be used. Also, it is desired to suppress the consumption of manufacturing equipment and resources. Therefore, it may be alternatively implemented by simulation on a computer.

[0007] To achieve such verification, conventional simulation devices constructed a pseudo-mechanism that received control instructions from control devices and returned response signals to those devices. For example, conventional simulation devices simulated the electrical circuits of the mechanism. By simulating the signal exchange between control equipment and mechanisms using a simulated mechanism, it was possible to verify the operation of the manufacturing equipment. Furthermore, by incorporating a mechanism to change the response time into the simulated mechanism, it was 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, it was impossible to provide appropriate settings without knowledge of how the mechanism operated. Furthermore, when varying the response time for a simulated mechanism, it was necessary to manually investigate and condition what response times the actual mechanism could take. For example, it was time-consuming to 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. [Prior art documents] [Patent Documents]

[0009] [Patent Document 1] Japanese Patent Application Publication No. 09-230923 [Overview of the Initiative] [Problems that the invention aims to solve]

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

[0011] The simulation system disclosed herein is A model generation unit generates a mechanism model that uses log data showing information on multiple types of control signals previously input from a control device to the mechanism and multiple types of response signals previously output from the mechanism to the control device, to generate a mechanism model that has time interval information relating to the time interval between a change in the value of the control signal and a change in the value of the response signal for each combination of control signals and response signals that have a causal relationship with each other. It is equipped with. [Effects of the Invention]

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

[0013] [Figure 1] Configuration diagram of the simulation system 100 in Embodiment 1. [Figure 2] Configuration diagram of the simulation device 200 in Embodiment 1. [Figure 3] A flowchart illustrating the operation of the log acquisition unit 210 and the model generation unit 220 in Embodiment 1. [Figure 4] A figure showing an example of log data 291 in Embodiment 1. [Figure 5] A diagram showing an example of the configuration of the mechanism model 281 in Embodiment 1. [Figure 6] Configuration diagram of the simulation system 100 in Embodiment 2. [Figure 7] A flowchart illustrating the operation of the model setting unit 221 in Embodiment 2. [Figure 8] Configuration diagram of the simulation system 100 in Embodiment 3. [Figure 9] Configuration diagram of the simulation system 100 in Embodiment 4. [Figure 10] A diagram showing an example of the configuration of the simulation system 100 in the embodiment. [Figure 11]Hardware configuration diagram of the simulation device 200 in the embodiment.

Embodiment for Carrying Out the Invention

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

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

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

[0017] The manufacturing equipment 300 is an example of the equipment (target equipment) to be simulated. The manufacturing equipment 300 includes a control device 310 and a mechanism 320. In FIG. 1, the manufacturing equipment 300 includes a control device 310 and a plurality of mechanisms 320. The control device 310 is a device that controls the mechanism 320. For example, a PLC, an IPC, or a general-purpose PC is used as the control device 310. The control device 310 controls the operation of the mechanism 320 according to a control program. The control program describes the calculation method of the control signal given from the control device 310 to the mechanism 320. The control program is pre-produced by a developer. The mechanism 320 is a device controlled by the control device 310 and performs a predetermined physical process (such as processing or assembly). Examples of the mechanism 320 are various devices, robots, or conveyors. The control device 310 inputs a control signal to the mechanism 320, and the mechanism 320 operates according to the control signal and outputs a response signal 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] Processor 201 is an IC that performs arithmetic operations and controls other hardware. For example, processor 201 is a CPU, DSP, GPU, or a combination of these. IC is an abbreviation for Integrated Circuit. CPU is an abbreviation for Central Processing Unit. DSP is an abbreviation for Digital Signal Processor. GPU is an abbreviation 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 in software.

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

[0027] The simulation program data (input data, output data, etc.) is stored in the memory unit 290. Memory 202 functions as 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 storage unit 290 instead of memory 202, 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. Furthermore, the procedure for operating the simulation system 100 corresponds to the procedure for processing by the simulation program.

[0030] Based on Figure 3, the operation of the log acquisition unit 210 and the model generation unit 220 will be explained. 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. The control signal is a signal for controlling mechanism 320. Mechanism 320 operates according to the control signal. A response signal is a signal used to respond to a control signal.

[0033] For example, log data 291 shows the values ​​of each control signal and 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 the values ​​of 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] 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. A model is a type of data.

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

[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 the 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 the mechanism 320. Mechanism 320 is a conveyor that performs workpiece transport as a predetermined physical process. When an "ON" control signal Y1 is input to mechanism 320, it is driven to transport the workpiece. When the workpiece reaches a predetermined position, the optical sensor of mechanism 320 detects the workpiece's arrival, and transport is completed. The optical sensor of mechanism 320 then 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 mean, 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, we continue the explanation. 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, based on the analysis results, mechanism 320 extracts combinations of control signals and response signals that have a causal relationship with each other from the log data 291. Next, the model generation unit 220 learns the time interval (change time interval) between a change in the value of the control signal and a change in the value of the response signal for each extracted combination. The model generation unit 220 then generates a model for each extracted combination that contains 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 the mechanism model 281.

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

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

[0044] ***Effects of Embodiment 1*** Embodiment 1 aims to reduce the effort required for manual model construction by learning the operating 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 mechanism 320 by changing its response time, the effort required for conditioning in reproducing the operation of mechanism 320 is reduced by utilizing the information related to the response time of mechanism 320 obtained through learning.

[0045] The simulation system 100 learns the operating timing of the mechanism 320 from the log data 291 of the control device 310 and mechanically generates a mechanism model 281. This allows users to perform simulation verification that reproduces the operating timing of mechanism 320, without having to go through the trouble of constructing mechanism model 281 or having any prior knowledge of mechanism 320.

[0046] ***Supplement to Embodiment 1*** The time interval of signal changes can also be represented by a regression model to show how it changes over time. For example, if we learn from log data 291 that the time interval between signal changes gradually increases, we can modify mechanism model 281 to also modify it to increase the time interval between signal changes over time. Specifically, if we learn from log data 291 that the interval increases by 1 second per day, we can modify mechanism model 281 to modify it so that the time interval between signal changes increases by 1 second over the course of a day in a simulation. Such regression models are designed to simulate scenarios where the actual mechanism 320 degrades in performance over time, including the resulting increase in the time required for physical processing.

[0047] When extracting control signal and response signal combinations that have a causal relationship from log data 291, depending on the learning method, it is not always possible to narrow down the combinations to those that are exactly the same as those used in the actual manufacturing equipment 300. For example, in Figure 5, suppose that in addition to the response signal X2 that should be associated with the control signal Y1, a response signal X3 from another sensor repeatedly changes from "OFF" to "ON" at a timing close to that of response signal X2. In this case, depending on the learning method, it may not be possible to determine which combination of control signal Y1 and response signal X2, or control signal Y1 and response signal X3, has the appropriate causal relationship. In such cases, the simulation system 100 may present users with candidate combinations of causally related signals, allow users to select an appropriate combination from the candidates, and then apply the selected combination to the mechanism model 281.

[0048] Embodiment 2. The main differences between the configuration for setting the operating conditions of the mechanism 320 during simulation execution and Embodiment 1 will be explained based on Figures 6 and 7.

[0049] ***Explanation of the structure*** The configuration of the simulation device 200 will be explained based on Figure 6. The simulation device 200 further includes an element called a model setting unit 221. The simulation program further enables the computer to function as a 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 the time interval information on the display. In this case, the user refers to the time interval information, determines the setting for the change time interval when simulating the operation of mechanism 320, and inputs the determined 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 time interval information and executes a software program using this time interval information as input. This determines the setting for the change time interval when simulating the operation of mechanism 320. The external system then transmits data (setting data) containing 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 sent 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 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 operating timing of mechanism 320.

[0060] The simulation system 100 allows users or external systems to provide operating conditions for the mechanism model 281. This makes it possible to perform simulation verification by considering various operating timings for mechanism 320.

[0061] For example, the following simulation verification becomes possible. (Example 1) Multiple mechanisms 320 have varying operating times. If the time interval between signal changes is maximized for all mechanisms 320, will manufacturing be completed within the desired time? (Example 2) If a specific mechanism 320 reaches its maximum signal change time interval for 10 consecutive cycles, will this cause an inconsistency in the overall operating timing of the manufacturing equipment 300? (Example 3) If a manufacturing facility 300 in operation stops due to the slow operation of mechanism 320, to what extent must the operation of mechanism 320 be sped up to prevent the manufacturing facility 300 from stopping? (Example 4) If the operation of a certain mechanism 320 is sped up, how much will the total 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 regarding the operating timing of mechanism 320 by any other means. Other methods include observing the actual mechanism 320 in operation and taking measurements using 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 timings specified in the design. Therefore, these methods are inferior in terms of accuracy.

[0063] ***Supplement to Embodiment 2*** During simulation using mechanism model 281, the model setting unit 221 sets the operating timing of mechanism 320, that is, the time interval of signal change from when mechanism 320 receives a control signal until it returns a response signal. For this setting, for example, the simulation user can provide arbitrary values. In this case, the model setting unit 221 is equipped with a user interface (UI) that accepts input from the simulation user. For this setting, for example, an external system can provide arbitrary values. In this case, the model setting unit 221 includes 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 as the setting for the time interval of signal changes. Furthermore, users or external systems can select a value from the average, maximum, or minimum values ​​shown in the time interval information. Furthermore, users or external systems can select values ​​using regression models.

[0065] The mechanism model 281 allows for common settings to be applied to multiple manufacturing cycles. For example, it is possible to provide the mechanism model 281 with a setting such as, "In the simulation of manufacturing over 10 cycles, operate mechanism 320 by setting the time interval of signal changes to the maximum value in all cycles." Furthermore, the mechanism model 281 can be given different settings for each of the multiple manufacturing cycles.

[0066] Embodiment 3. The main differences between the simulation method for controlling the operation of the control device 310 and Embodiment 1 will be explained based on Figure 8.

[0067] ***Explanation of the structure*** The configuration of the simulation device 200 will be explained based on Figure 8. The simulation device 200 also stores the control equipment model 282. Control device model 282 is a model used to simulate the operation of control device 310. For example, control device model 282 is provided to the simulation device 200 by the 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 between the control device 310 and the mechanism 320.

[0069] The simulation will be executed as follows: The simulation unit 230 manages the start of the simulation, the end of the simulation, and the conditions of the simulation (such as the duration for which the simulation is run). The simulation unit 230 performs 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 duration for which the simulation will be run. Next, the simulation unit 230 receives an instruction to start the simulation and the simulation conditions. Next, the simulation unit 230 performs signal exchange between the control device model 282 and the mechanism model 281 under simulation conditions. Signal exchange refers to the exchange of control signals and response signals. The control signal is generated by the control device model 282. The response signal is generated by the mechanism model 281, which simulates the operating timing in response to the control signal. Then, 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 an 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 the 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 simulation device 200 with the control device model 282, users can use the simulation device 200 to verify the operating timing. In other words, users can verify whether the control program installed in the control device 310 achieves the appropriate operating timing for the manufacturing equipment 300 without having to handle the actual control device 310.

[0072] ***Supplement to Embodiment 3*** Control device model 282 is a model that simulates the operating timing of control device 310. The operating timing of the control device 310 is determined by the control program provided to the control device 310. Therefore, a typical example of control device model 282 is one that executes the control program of control device 310 itself. However, the control device model 282 may also read and execute a timing chart or similar document describing 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 by learning log data 291, similar to the mechanism model 281.

[0073] Embodiment 3 may be implemented in combination with Embodiment 2. In other words, the simulation device 200 may be equipped with a model setting unit 221, and the operating conditions of the mechanism 320 may be provided. Similarly, the operating conditions of the control device 310 may be provided via the model setting unit 221.

[0074] Embodiment 4. The main differences between this embodiment and Embodiment 3 will be explained with reference to Figure 9 regarding the simulation of external factors that affect the operation of at least one of the control device 310 and the mechanism 320.

[0075] ***Explanation of the structure*** The configuration of the simulation device 200 will be explained based on Figure 9. The simulation device 200 also stores the external model 283. External model 283 is a model relating to external factors and is used to simulate the behavior of those external factors. External factors affect the operation of at least one of the control device 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, an 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 the external model 283 is linked to the mechanism model 281 and the control equipment model 282 to perform the simulation. External model 283 represents the timing of operations of the manufacturing equipment 300 related to external factors (e.g., people or workpieces).

[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*** External model 283 is a model that simulates the timing of operations related to external factors of the manufacturing equipment 300.

[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 signals cannot be learned as a relationship between control signals and response signals. External model 283 is defined as a method to simulate the timing of the generation (input timing) of such sensor signals. External model 283 provides the sensor signal, when human movement is detected, as input to control device model 282 at a specific timing in the manufacturing cycle.

[0082] (Second example) External model 283 simulates the timing of loading workpieces into the manufacturing equipment 300. At the start of the physical processing, the workpiece is fed into the control device 310 from an external source. Workpieces may be loaded manually or by equipment or conveying devices from the preceding process. The loading of such workpieces is detected by sensors (such as optical sensors) installed in the manufacturing equipment 300. Furthermore, the timing of when the workpiece is loaded 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 the timing of workpiece loading. External model 283 provides a sensor signal, which is detected when workpiece loading is performed, as input to 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. In other words, the simulation device 200 may be equipped with a model setting unit 221, and the operating conditions of the mechanism 320 may be provided. Similarly, the operating conditions of the control equipment 310 may be provided via the model setting unit 221. Furthermore, the operating conditions of external factors may be provided 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] ***Supplementary Information on 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 with a device for managing the model and a device for executing the simulation. 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 of these devices 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 that manages the control equipment model 282 and includes a model management unit (not shown in the figure). The model management unit transfers the control equipment model 282 to the simulation execution device 420 via the network. The simulation execution device 420 is a device that performs simulations and includes a simulation unit 230. The simulation unit 230 receives models (281, 282) from the model management devices (411, 412) via a network and performs simulations using the received models. Running simulations requires greater computing power. On the other hand, model generation and model management (editing, etc.) can be done with less computing power than simulations. By distributing the functions, it becomes possible to run simulations on high-performance machines (e.g., the cloud) and 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 explained. The simulation device 200 includes a processing circuit 209. The processing circuit 209 is hardware that implements the log acquisition unit 210, the model generation unit 220, the model setting unit 221, and the 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," "process," "circuit," or "circuit." [Explanation of symbols]

[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 model generation unit generates a mechanism model that uses log data showing information on multiple types of control signals previously input from a control device to the mechanism and multiple types of response signals previously output from the mechanism to the control device, to generate a mechanism model that has time interval information relating to the time interval between a change in the value of the control signal and a change in the value of the response signal for each combination of control signals and response signals that have a causal relationship with each other. Equipped with, 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 between a change in the value of the control signal and a change in the value of the response signal for each extracted combination, and generates a model as the mechanism model that has the information obtained through learning as the time interval information for each extracted combination. Simulation system.

2. A model generation unit generates a mechanism model that uses log data showing information on multiple types of control signals previously input from a control device to a mechanism and multiple types of response signals previously output from the mechanism to the control device, and generates a mechanism model that has time interval information relating to the time interval from when a change in the value of the control signal occurs until when 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. A simulation unit reproduces the timing of signal exchange that occurs between the control device and the mechanism by simulating the operation of the mechanism using the mechanism model, simulating the operation of the control device using the control device model, and simulating the operation of 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. A simulation system equipped with the following features.

3. A model generation unit generates a mechanism model that uses log data showing information on multiple types of control signals previously input from a control device to a mechanism and multiple types of response signals previously output from the mechanism to the control device, and generates a mechanism model that has time interval information relating to the time interval from when a change in the value of the control signal occurs until when 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. A simulation system comprising: a simulation unit that simulates the operation of the mechanism using the mechanism model, and simulates the operation of 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, thereby reproducing the timing of signal exchange that occurs between the control device and the mechanism.

4. The model generation unit uses log data showing information on multiple types of control signals previously input from the control device to the mechanism and multiple types of response signals previously output from the mechanism to the control device to generate a mechanism model that has time interval information relating to the time interval between a change in the value of the control signal and a change in the value of the response signal for each combination of control signals and response signals that have a causal relationship with each other. A simulation method, 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 between a change in the value of the control signal and a change in the value of the response signal for each extracted combination, and generates a model as the mechanism model that has the information obtained through learning as the time interval information for each extracted combination. Simulation method.

5. Using log data that shows information on multiple types of control signals input from control equipment to the mechanism in the past and multiple types of response signals output from the mechanism to the control equipment in the past, a mechanism model is generated that has time interval information relating to the time interval from when a change in the value of the control signal occurs until when 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. The timing of signal exchange between the control device and the mechanism is reproduced by simulating the operation of the mechanism using the mechanism model, simulating the operation of the control device using the control device model, and simulating the operation of 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. Simulation method.

6. Using log data that shows information on multiple types of control signals input from control equipment to the mechanism in the past and multiple types of response signals output from the mechanism to the control equipment in the past, a mechanism model is generated that has time interval information relating to the time interval from when a change in the value of the control signal occurs until when 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. The operation of the mechanism is simulated using the mechanism model, and the operation of the external factors is simulated using an external factors model relating to external factors that affect the operation of at least one of the control device and the mechanism, thereby reproducing the timing of signal exchange that occurs between the control device and the mechanism. Simulation method.

7. Model generation process: Using log data that shows information on multiple types of control signals input from control equipment to the mechanism in the past and multiple types of response signals output from the mechanism to the control equipment in the past, a mechanism model is generated that has time interval information relating to the time interval between a change in the value of the control signal and a change in the value of the response signal for each combination of control signals and response signals that have a causal relationship with each other. A simulation program to run on a computer, The model generation process extracts combinations of control signals and response signals that have a causal relationship with each other from the log data, learns the time interval between a change in the value of the control signal and a change in the value of the response signal for each extracted combination, and generates a model as the mechanism model that has the information obtained through learning as the time interval information for each extracted combination. Simulation program.

8. A model generation process that uses log data showing information on multiple types of control signals input from a control device to a mechanism in the past and multiple types of response signals output from the mechanism to the control device in the past to generate a mechanism model that has time interval information relating to the time interval from when a change in the value of the control signal occurs until when 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. A simulation process that reproduces the timing of signal exchange between the control device and the mechanism by simulating the operation of the mechanism using the mechanism model, simulating the operation of the control device using the control device model, and simulating the operation of 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, A simulation program to run on a computer.

9. A model generation process that uses log data showing information on multiple types of control signals input from a control device to a mechanism in the past and multiple types of response signals output from the mechanism to the control device in the past to generate a mechanism model that has time interval information relating to the time interval from when a change in the value of the control signal occurs until when 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. A simulation process that simulates the operation of the mechanism using the mechanism model, and simulates the operation of 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, thereby reproducing the timing of signal exchange that occurs between the control device and the mechanism. A simulation program to run on a computer.

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