Simulation device, program for simulation device, simulation system, and program for simulation system

Abstract

Provided is a simulation device capable of presenting, to a user, an item of a parameter that may contribute to improving a simulation result. The simulation device causes a virtual system in a virtual space, the virtual system having virtual components corresponding to components included in a system in a real space, to reproduce an operation of the system in the real space by simulation using real data acquired from the system in the real space. The simulation device comprises a parameter setting processing unit and a simulation unit. The parameter setting processing unit reads data item management information including a value of a parameter to be set for the virtual component, and outputs a parameter setting screen that allows the value of the parameter to be changed. The simulation unit simulates an operation of the virtual system according to content set on the parameter setting screen. The parameter setting screen includes a parameter value type corresponding to the parameter value.

Description

Simulation device, program for simulation device, simulation system, and program for simulation system

[0001] This disclosure relates to a simulation device for simulating the behavior of a simulation target in real space, a program for the simulation device, a simulation system, and a program for the simulation system.

[0002] In the simulation, the parameters set in the simulation are modified so that the simulation results, which simulate the operation of the actual equipment using a simulation device, approach the results in the actual equipment. Patent Document 1 discloses a formability analysis method that performs formability analysis using a formability analysis simulation program. In the formability analysis method described in Patent Document 1, each parameter of the material property data is set and a formability analysis simulation is performed, and actual molding is performed using an evaluation mold under the same conditions as the formability analysis simulation, and the evaluation target is determined from the results of the formability analysis simulation and the actual molding results. Furthermore, in the formability analysis method described in Patent Document 1, the difference between the results of the formability analysis simulation and the actual molding results for the evaluation target is calculated and compared with an evaluation standard value, and when the difference exceeds the evaluation standard value, each parameter of the material property data is changed and the formability analysis simulation is performed until the difference between the results of the formability analysis simulation and the actual molding results falls within the evaluation standard value.

[0003] Japanese Patent Application Publication No. 11-184906

[0004] In the above prior art, when the difference between the results of the molding analysis simulation and the actual molding results is outside the evaluation reference value, a skilled user can empirically know each parameter of the material property data to be changed in order to improve the simulation results. However, an unskilled user cannot know which parameter among the parameters of the material property data should be changed in order to improve the simulation results. For this reason, there has been a problem that an unskilled user has to change parameters by trial and error. Such a problem has also occurred not only in the simulation of the formability analysis but also in the simulation of the operation of the simulation target in the real space.

[0005] The present disclosure has been made in view of the above, and an object thereof is to obtain a simulation device that can present to a user items of parameters that may lead to improvement of simulation results.

[0006] In order to solve the above-described problems and achieve the object, the present disclosure is a simulation device that reproduces the operation of a real-space system by simulation using real data, which is information of the real-space system acquired from the real-space system, in a virtual system on a virtual space having the same virtual components as the real-space system including at least one component that performs an operation, and includes a parameter setting processing unit and a simulation unit. The parameter setting processing unit reads data item management information including values of parameters to be set for the virtual components, and outputs a parameter setting screen in which the set parameter values can be changed. The simulation unit simulates the operation of the virtual system according to the contents set on the parameter setting screen. The parameter setting processing unit generates a parameter setting screen that displays the type of the parameter value corresponding to the parameter value.

[0007] The simulation device according to the present disclosure has an effect that it can present to a user items of parameters that may lead to improvement of simulation results.

[0008] A diagram showing an example of the configuration of the simulation system according to Embodiment 1. A diagram showing another example of the configuration of the simulation system according to Embodiment 1. A block diagram showing an example of the functional configuration of the data item management device constituting the simulation system according to Embodiment 1. A diagram showing an example of data item management information. A block diagram showing an example of the functional configuration of the initial setting information management device constituting the simulation system according to Embodiment 1. A diagram showing an example of initial setting information. A block diagram showing an example of the functional configuration of the simulation device according to Embodiment 1. A diagram showing an example of the parameter setting screen. A flowchart showing an example of the procedure for the simulation method according to Embodiment 1. A flowchart showing an example of the procedure for the simulation method according to Embodiment 1. A diagram showing an example of the functional configuration of the simulation device according to Embodiment 2. A diagram showing an example of the difference between the simulation results and real data. A diagram schematically showing the difference between the results of work on the actual simulation target and the simulation results. A flowchart showing an example of the procedure for the simulation method according to Embodiment 2. A flowchart showing an example of the procedure for the simulation method according to Embodiment 2. A flowchart showing an example of the procedure for the simulation method according to Embodiment 2. A diagram showing an example of the parameter setting screen. A diagram showing an example of the functional configuration of the simulation device according to Embodiment 3. A diagram showing an example of the functional configuration of the simulation device according to Embodiment 4. A flowchart showing an example of the procedure for the additional item determination method. A diagram showing an example of the functional configuration of the simulation device according to Embodiment 5. A flowchart showing an example of the procedure for the additional item determination method according to Embodiment 5. Simulation devices according to Embodiments 1 to 5.A block diagram showing an example of the configuration of a computer system that implements a data item management device and an initial setting information management device. A diagram showing an example of applying a simulation system to a city to realize a digital twin of the city. A diagram showing an example of parameters used in urban design in a virtual city. A diagram showing an example of applying a simulation system to a building to realize a digital twin of the building. A diagram showing an example of parameters used in building simulation in a virtual space. A diagram showing an example of applying a simulation system to the construction of an elevator to realize a digital twin of an elevator. A diagram showing an example of applying a simulation system to the maintenance of an elevator to realize a digital twin of an elevator. A diagram showing an example of parameters used in an elevator in a virtual space. A diagram showing an example of applying a simulation system to a water treatment system to realize a digital twin of a water treatment system. A diagram showing an example of parameters used in a water treatment system in a virtual space.

[0009] The following describes in detail, with reference to the drawings, the simulation apparatus, the program for the simulation apparatus, the simulation system, and the program for the simulation system according to the embodiments of this disclosure.

[0010] Embodiment 1. Figure 1 is a diagram showing an example of the configuration of a simulation system according to Embodiment 1. The simulation system 1 is a system that acquires real data, which is information about the system of the simulation target 60 that exists in the real world, and realizes a digital twin that reproduces the operation of the system that exists in the real world using the acquired real data in a virtual space calculated on the simulation device 10. The simulation system 1 comprises a simulation device 10, a data item management device 30, an initial setting information management device 40, and a user terminal 50. In the example in Figure 1, the simulation device 10, the user terminal 50, and the simulation target 60 are installed on the factory side, and the data item management device 30 and the initial setting information management device 40 are installed on the cloud side.

[0011] The simulation device 10 is a device that performs simulations on the simulation target 60 according to instructions from the user terminal 50. The simulation target 60 is not particularly limited and can be anything that consists of multiple components working together to form a single system. Components may include not only devices but also people, objects, etc., placed in real space. Furthermore, the components may include non-moving items such as desks, as long as at least one component is operational. Examples of simulation targets 60 include manufacturing systems using FA (Factory Automation) equipment, water treatment systems, railway management systems, and power management systems. The simulation device 10 may also simulate design, construction, installation, maintenance, etc., as the simulation target 60. For example, the simulation device 10 may simulate urban design as design, simulate the construction of buildings as construction, or simulate the installation or maintenance of elevators as installation or maintenance. In the example in Figure 1, the simulation device 10 is configured using an on-premise server.

[0012] The data item management device 30 and the initial setting information management device 40 are comprised of one or more cloud servers. A cloud server is a server built in a cloud environment that includes computer resources provided on a cloud service platform.

[0013] The simulation device 10, the data item management device 30, the initial setting information management device 40, and the user terminal 50 are connected via a network 70. The network 70 is, in one example, a WAN (Wide Area Network) such as the Internet, but it may also be a LAN (Local Area Network).

[0014] The data item management device 30 is an information processing device that manages the parameters set in the simulation device 10, or more specifically, the simulation program, which is a computer program executed by the simulation device 10. In other words, the data item management device 30 is a device that manages data item management information, which is information about the parameters set in the simulation program, which is a computer program executed by the simulation device 10. In one example, the data item management device 30 is a database device.

[0015] The initial setting information management device 40 is an information processing device that manages initial setting information, which is the initial value of the parameters to be set in the virtual system of the simulation device 10. Specifically, the initial setting information management device 40 is a device that stores initial setting information, which is the initial value of the parameters to be set in the simulation program, and can be provided to a user who is using the simulation program of the simulation device 10 for the first time. In one example, the initial setting information management device 40 is a database device.

[0016] The user terminal 50 is connected to the simulation device 10 via a network 70 and is an information processing device that instructs the simulation device 10 to execute a simulation and receives and displays the simulation results from the simulation device 10. The network 70 between the user terminal 50 and the simulation device 10 is either a WAN or a LAN. The user terminal 50 has a display unit and an input unit and can perform tasks such as setting parameters for the simulation device 10 and displaying the simulation results from the simulation device 10.

[0017] Note that while Figure 1 shows an example where the simulation device 10 is an on-premise server, the system is not limited to this. Figure 2 shows another example of the configuration of the simulation system according to Embodiment 1. In Figure 2, the simulation device 10, data item management device 30, and initial setting information management device 40 are located on the cloud side and are shown as being configured by one or more cloud servers.

[0018] Figure 3 is a block diagram showing an example of the functional configuration of a data item management device 30 that constitutes the simulation system according to Embodiment 1. The data item management device 30 comprises a data receiving unit 31, a data item management unit 32, a data item management information storage unit 33, and a data transmission unit 34.

[0019] The data receiving unit 31 receives data item management information from the simulation device 10, which includes the name of the parameter, the value of the parameter, and the type of the parameter value. In other words, the data receiving unit 31 receives data item management information that includes the correspondence between the parameter value and the type of parameter value set on the parameter setting screen of the simulation device 10, which will be described later.

[0020] The data item management unit 32 stores the received data item management information in the data item management information storage unit 33.

[0021] The data item management information storage unit 33 stores data item management information that associates the set value and the type of set value for parameters set in the simulation device 10. Figure 4 shows an example of data item management information. The data item management information is managed on a per-user or per-simulation program basis for each component constituting the simulation target 60, associating the parameter name with the parameter value and the type of parameter value. The types of parameter values ​​include "initial values" that are pre-set in the simulation device 10 by the manufacturer of the simulation device 10 or the simulation program, "planned values" that are calculated in the design of the system in real space or that are provisionally set by the user, "actual values" that are actually measured in the system in real space and are based on actual results, and "excluded" values ​​that are not used as data. In the case of excluded values, the parameter value is not entered. In addition, the types of parameter values ​​may include other types.

[0022] Figure 4 shows an example of data management item information where the components are equipment A, equipment B, a desk, etc., which make up the simulation target 60, and the names of the parameters, the values ​​of the parameters, and the types of the parameter values ​​are associated with each component.

[0023] Returning to Figure 3, when the data transmission unit 34 receives a request from the simulation device 10 to acquire data item management information, it transmits the data item management information stored in the data item management information storage unit 33, corresponding to the simulation device 10, to the simulation device 10.

[0024] Figure 5 is a block diagram showing an example of the functional configuration of an initial setting information management device that constitutes the simulation system according to Embodiment 1. The initial setting information management device 40 comprises an initial setting information storage unit 41, a data transmission unit 42, a data reception unit 43, and a management processing unit 44.

[0025] The initial setting information storage unit 41 stores initial setting information, which is the initial value of the parameters of the simulation device 10. In one example, the initial setting information is set for each user of the simulation device 10. Figure 6 shows an example of initial setting information. The initial setting information is managed on a per-user basis or per-simulation program basis, for each component that makes up the simulation target 60, by associating the initial value of the parameter with the parameter name. Since the simulation device 10 performs simulations by executing simulation programs, the parameters set in the simulation device 10 can also be said to be the parameters set in the simulation program.

[0026] Returning to Figure 5, when the data transmission unit 42 receives a request from the simulation device 10 to acquire initial setting information for parameters, it acquires the initial setting information corresponding to the simulation device 10 from the initial setting information storage unit 41 and transmits it to the simulation device 10.

[0027] The data receiving unit 43 receives data related to the initial values ​​of parameters from other devices such as the simulation device 10 and the data item management device 30.

[0028] The management processing unit 44 manages to store the initial parameter values ​​in the initial setting information storage unit 41 for each user who has installed the simulation device 10. In one example, the management processing unit 44 registers data related to the initial parameter values ​​received from other devices into the initial setting information.

[0029] Figure 7 is a block diagram showing an example of the functional configuration of a simulation device according to Embodiment 1. The simulation device 10 is a device that reproduces the operation of a system in a real space by simulation using real data, which is information about the system to be simulated 60 acquired from the system in the real space, on a virtual system in a virtual space that has the same virtual components as a system in the real space that includes at least one component that performs operation. The simulation device 10 comprises a data receiving unit 11, a parameter setting processing unit 12, a data transmission unit 13, a real data collection unit 14, a simulation unit 15, and a result display processing unit 16.

[0030] The data receiving unit 11 receives data item management information from the data item management device 30 and initial setting information from the initial setting information management device 40. For example, when a user uses the simulation device 10 for the first time, the data receiving unit 11 receives initial setting information corresponding to the simulation device 10 from the initial setting information management device 40. When a user uses the simulation device 10 for the second time or later, the data receiving unit 11 receives data item management information corresponding to the simulation device 10 from the data item management device 30.

[0031] The parameter setting processing unit 12 reads data item management information, including the values ​​of parameters to be set for virtual components that constitute a virtual simulation target, and outputs a parameter setting screen in which the set parameter values ​​can be changed. Specifically, when a user uses the simulation device 10 for the first time, the parameter setting processing unit 12 sends a request to the initial setting information management device 40 to acquire initial setting information, reads the initial setting information as data item management information, and outputs the parameter setting screen. When a user uses the simulation device 10 for the second time or later, the parameter setting processing unit 12 sends a request to the data item management device 30 to acquire data item management information, reads the data item management information, and outputs the parameter setting screen. In one example, the parameter setting processing unit 12 generates a parameter setting screen for the parameters of virtual components that need to be set in the simulation device 10 and outputs it to the user terminal 50. The parameter setting screen allows the user to set parameters for each component of the simulation target 60, in one example.

[0032] Figure 8 shows an example of a parameter setting screen. The parameter setting screen 100 includes a component selection area 101, a simulation target display area 102, and a parameter setting area 103.

[0033] The component selection area 101 is an area that displays the components of the simulation target 60. In one example, the components are displayed in a tree structure in the component selection area 101. In the component selection area 101, the user can select one component for which they want to set parameters.

[0034] The simulation target display area 102 is an area that displays the virtual appearance of the simulation target 60, including the components selected in the component selection area 101, in virtual space.

[0035] The parameter setting area 103 is an area for setting the parameters of the component selected in the component selection area 101. The parameter setting area 103 has a name display area 1031 where the name of the parameter is displayed, a parameter input area 1032 where the value of the parameter is entered, and a type input area 1033 where the type of the parameter value is entered. The parameter value is entered in the parameter input area 1032. The type input area 1033 is where the value entered in the parameter input area 1032 is entered as either an initial value, a design value, an actual value, or not applicable. In one example, the type input area 1033 consists of a pull-down menu with initial value, design value, actual value, and not applicable as a list. In this way, the parameter setting screen 100 is configured so that the type of the parameter value is displayed together with the parameter value. This makes it easier for users using the parameter setting screen 100 to recognize the type of the set parameter value. In this way, the parameter setting processing unit 12 generates the parameter setting screen 100 which displays the type of parameter value corresponding to the parameter value. The types of parameter values ​​shown here are merely examples; any type that allows the user to recognize whether the parameter values ​​can be changed is acceptable. For example, the types of parameter values ​​should include at least one of the following: a type indicating that the parameter value can be changed, and a type indicating that the parameter value cannot be changed based on the simulation results.

[0036] When a component is selected in the component selection area 101, the parameter setting processing unit 12 reads the parameter name and parameter value for the selected component from the initial setting information or data item management information and reflects them in the name display area 1031 and parameter input area 1032 of the parameter setting area 103. The parameter setting processing unit 12 may also set the parameter value type corresponding to the parameter on the parameter setting screen 100 according to the data item management information if it reads data item management information where the parameter value type is set along with the parameter value. For example, if the parameter setting processing unit 12 reads data item management information where the parameter value type is set as the actual value, it may set the parameter value type corresponding to the parameter on the parameter setting screen 100 to the actual value. In another example, if the parameter setting processing unit 12 reads data item management information where the parameter value type is set as the initial value or design value, it may set the parameter value type corresponding to the parameter on the parameter setting screen 100 to the initial value or design value. In this way, when reading data where the parameter value and type are associated with a parameter item, the parameter setting processing unit 12 can set the type along with the parameter value on the parameter setting screen. This eliminates the need for the user to check what the type of parameter value is and set the type of the parameter value, and also reduces the likelihood of the user making a mistake in setting the type of parameter value. Note that the parameter item is information that indicates what the parameter value is, and in one example, it is the name of the parameter.

[0037] The parameter setting processing unit 12 outputs a message prompting the user to update the type of the corresponding parameter value when the parameter value is changed. Then, when the parameter setting processing unit 12 has finished setting the parameters, it sets the contents of the parameter setting screen 100 to the simulation unit 15.

[0038] Returning to Figure 7, once the input of parameters to the parameter setting screen 100 is complete, the data transmission unit 13 transmits the input contents of the parameter setting screen 100 to the data item management device 30. As a result, the input contents of the parameter setting screen 100 are stored in the data item management information storage unit 33 of the data item management device 30. In other words, the contents of the parameters set in the simulation device 10 are managed by the data item management device 30.

[0039] The real data collection unit 14 collects real data, which is data showing the results of the operation of the system in the real space that is the simulation target 60.

[0040] The simulation unit 15 simulates the operation of a virtual system according to the settings on the parameter setting screen 100. Specifically, it simulates the operation of a virtual simulation target constructed in the virtual space based on the simulation target 60 in the real space, according to real data collected from the simulation target 60 in the real space and parameters set by the parameter setting processing unit 12. In other words, the simulation unit 15 reproduces the operation of the simulation target in the virtual space by setting parameters in the simulation program, which is a computer program that operates the simulation target 60 in the virtual space, and inputting data collected from the simulation target 60 in the real space.

[0041] The results display processing unit 16 generates a results display screen that displays the simulation results and real data on the user terminal 50. One example of data that shows the simulation results is time. In this case, a results display screen is generated that includes the time taken for processing in the real-world system and the time taken for processing obtained as a result of the simulation in the virtual-world system. Here, time is given as an example of the gap between real data and simulation results, but other data may also be used.

[0042] The user checks whether there is a gap between the simulation results displayed on the user terminal 50 (not shown) and the real data that exceeds a predetermined range; in other words, whether there is a significant difference between the value of the verification item arbitrarily set by the user and the value corresponding to the verification item obtained in the simulation. In one example, the predetermined range is the margin of error.

[0043] Next, the simulation method in the simulation system 1 will be described. Figures 9 and 10 are flowcharts showing an example of the procedure for the simulation method according to Embodiment 1. First, when the simulation device 10 receives a request to display the parameter setting screen 100 from the user terminal 50 (step S11), it determines whether it is the first time the simulation device 10 is being used (step S12). If it is the first time (if the answer is Yes in step S12), the simulation device 10 sends a request to the initial setting information management device 40 to acquire initial setting information (step S13). When the initial setting information management device 40 receives the request to acquire initial setting information (step S14), it acquires the initial setting information corresponding to the simulation device 10 that sent the acquisition request from the initial setting information storage unit 41 (step S15), and sends the initial setting information to the simulation device 10 (step S16). The processing in the initial setting information management device 40 ends in step S16. The simulation device 10 sets the acquired initial setting information on the parameter setting screen 100 (step S17).

[0044] If step S12 is not the first time using the system (i.e., the answer in step S12 is No), the simulation device 10 sends a request to the data item management device 30 to acquire data item management information (step S18). When the data item management device 30 receives the request to acquire data item management information (step S19), it acquires the data item management information corresponding to the simulation device 10 that sent the request from the data item management information storage unit 33 (step S20), and sends the data item management information to the simulation device 10 (step S21). The simulation device 10 sets the acquired data item management information on the parameter setting screen 100 (step S22).

[0045] After that or after step S17, the simulation device 10 transmits the parameter setting screen 100 to the user terminal 50 (step S23). The user terminal 50 displays the parameter setting screen 100 on the display unit. As shown in FIG. 8, the parameter setting screen 100 has a configuration in which a type input area 1033 for inputting the type of the parameter value is also described for a pair of a name display area 1031 where the name of the parameter is displayed and a parameter input area 1032 where the value of the parameter can be input. On such a parameter setting screen 100, the user sets parameters. In the case of the first use, the user may not input anything as it is with the parameter values set on the parameter setting screen 100, or may input the calculated values obtained in advance by calculation. When the calculated values are input, the type of the value of the corresponding parameter is changed to "calculated value" by the user. Also, in the case of the second and subsequent uses, the user changes the values of the parameters whose type of the parameter value is not "actual value", particularly the parameters whose type is "initial value". When changing the parameter values, the values obtained by actually measuring the values corresponding to the items of the parameters that the simulation target 60 in the real space actually operates may be set as the parameter values, or the calculated values obtained in advance by calculation may be set. When the actually measured values are set, the type of the value of the corresponding parameter is changed to "actual value" by the user, and when the calculated values are set, the type of the value of the corresponding parameter is changed to "calculated value" by the user. Note that the steps of S11 - S_{13}, S17, S18, S22, and S23 correspond to a parameter setting process step of reading data item management information including the parameter values to be set for the virtual components in the virtual system on the virtual space having the same virtual components as the system in the real space including at least one component that performs operations, and outputting a parameter setting screen 100 in which the set parameter values can be changed. Also, in this parameter setting process step, a parameter setting screen 100 for displaying the type of the parameter value corresponding to the parameter value is generated.

[0046] The simulation device 10 determines whether the user has changed the parameter value (step S24). If the parameter value has been changed (if the answer is Yes in step S24), the simulation device 10 determines whether the change in the type of parameter value has been confirmed (step S25). In one example, the simulation device 10 displays a message prompting confirmation of the change in the type of parameter value on the display unit of the user terminal 50, and determines whether the change in the type of parameter value has been confirmed based on the response to this message.

[0047] If the user has not confirmed the change in the type of parameter value (if the answer is No in step S25), the process returns to step S24. If the user has confirmed the change in the type of parameter value (if the answer is Yes in step S25), or if the parameter value has not been changed in step S24 (if the answer is No in step S24), the simulation device 10 reflects the contents of the parameter setting screen 100 in the simulation device 10, specifically the simulation unit 15 (step S26), and transmits the contents of the parameter setting screen 100 to the data item management device 30 (step S27). When the data item management device 30 receives the contents of the parameter setting screen 100 (step S28), it saves the received contents of the parameter setting screen 100 to the data item management information storage unit 33 (step S29). When the data item management device 30 saves the parameter values ​​and items to the data item management information, it may overwrite the existing data or save it in a way that retains a history of past data. Step S28 corresponds to a data reception step, which receives data item management information, including the correspondence between the parameter values ​​set on the parameter setting screen 100 and the types of parameter values. Step S29 corresponds to a data item management information storage step, which stores the data item management information. Processing in the data item management device 30 ends in step S29.

[0048] After step S27, the simulation device 10 executes a simulation and obtains the result of the simulation (step S30). The processes of steps S26 and S30 correspond to a simulation process of simulating the operation of a virtual system using real data, which is information on the system in the real space obtained from the system in the real space according to the content set on the parameter setting screen 100.

[0049] Also, the simulation device 10 obtains real data, which is data indicating the operating state, from the system in the real space that is the simulation target 60 (step S31). Thereafter, the simulation device 10 generates a result display screen including the result of the simulation and the real data (step S32), and transmits the result display screen to the user terminal 50 (step S33). The user terminal 50 displays the result display screen on the display unit. The user checks whether there is a gap greater than a determined range between the result of the simulation and the real data using the result display screen, that is, the difference between the value of the verification item arbitrarily set by the user and the value corresponding to the above verification item obtained by the simulation. Here, the value of the verification item arbitrarily set by the user may be obtained from the real data or may be a specification value arbitrarily set by the user. Also, the term "arbitrarily set by the user" refers to any one of (A) something set afterwards by the user after seeing the result of the simulation and determining that there is a gap in this result, (B) something preset by the user as a simulation error such as setting the difference in the operating time in the real data and the result of the simulation to 5 seconds, and (C) something automatically set as a gap after the user learns something set afterwards by seeing the result of the simulation with artificial intelligence (Artificial Intelligence: AI). Also, the determined range is, as an example, the error range.

[0050] If the user determines that there is a gap between the simulation results and the real data, they will recognize that the accuracy of the simulation by the simulation device 10 is not high, change the parameters, and run the simulation again. On the other hand, if the user determines that there is no gap between the simulation results and the real data, they will recognize that the accuracy of the simulation by the simulation device 10 is sufficient for practical use, and will terminate the simulation to match the real data.

[0051] In other words, if the user wants to run the simulation again, they send a request to the simulation device 10 from the user terminal 50 to display the parameter setting screen 100, and if they want to end the simulation, they do not send a request to display the parameter setting screen 100. The simulation device 10 then determines whether it has received a request to display the parameter setting screen 100 from the user terminal 50 (step S34). If it has received a request to display the parameter setting screen 100 from the user terminal 50 (if the answer is Yes in step S34), the process returns to step S18.

[0052] In this case, the display unit of the user terminal 50 will display the contents of the parameter setting screen 100 saved in the data item management device 30 in step S29. At this time, the user can identify the parameters that should be changed by checking the type of parameter value in the parameter setting area 103 of the parameter setting screen 100 as shown in Figure 8. For example, if the type of parameter value is "actual value," it is a parameter that was actually measured and obtained in a real-world system, so there is no room to change this parameter. In other words, parameters whose type of value is "actual value" can be excluded from the parameter changes. Also, if there are parameters whose type of value is "initial value," it is highly likely that the parameter value deviates from the actual value. Furthermore, if there are parameters whose type of value is "planned value," it is highly likely that the parameter value deviates from the actual value, although not as much as the initial value. Furthermore, if the type of parameter value is "not applicable," it is thought that parameter settings may be necessary. In this way, the user can guess that parameters whose type of value is anything other than "actual value" are the parameters that should be changed.

[0053] Furthermore, comparing parameter values ​​categorized as "initial value" and "not applicable," the "not applicable" category indicates that there are cases where it is not necessary to set the parameter. Therefore, it is generally considered that changing the parameter value should be prioritized for "initial value" rather than "not applicable." Also, when the parameter value is categorized as "planned value," it is a value that has been calculated in advance, so it is generally considered that changing the parameter value should be prioritized for "initial value" rather than "initial value" or "not applicable." In other words, changing the parameter values ​​of "initial value" and "not applicable" rather than "planned value," and changing the parameter values ​​of "initial value" rather than "not applicable," increases the likelihood of improving simulation accuracy.

[0054] By considering the general relationship between the types of parameter values ​​and actual values, users can realize that they can improve the accuracy of the simulation by primarily changing the parameters whose value type is "initial value". Then, the parameters changed in this way are set in the simulation device 10, and the parameter setting and simulation execution are repeated until the difference between the simulation result and the real data falls within a predetermined range, for example, within the margin of error.

[0055] For example, by changing parameters that are "excluded" and "planned values" after all parameters with the "initial value" type have been removed, it becomes possible to change parameters to improve simulation accuracy more efficiently compared to randomly changing parameter values.

[0056] If no request to display the parameter setting screen 100 is received from the user terminal 50 in step S34 (i.e., the response in step S34 is No), the process terminates.

[0057] Here, we will explain the effects compared to conventional technology. In the conventional parameter setting screen, the parameter setting area 103 in Figure 8 lacks an item for the type of parameter value; in other words, there is no type input area 1033. As a result, when an inexperienced user is operating the system, the user does not know which part of the parameters to change. Therefore, they end up changing parameter values ​​haphazardly or asking an experienced user to change the parameter values. In the former case, it is unclear whether the change will improve the accuracy of the simulation, resulting in very poor work efficiency. In the latter case, experienced users who should be performing other tasks are made to perform the task of setting simulation parameters, which reduces the overall productivity of the company that has introduced the simulation system 1.

[0058] In contrast, the simulation device 10 according to Embodiment 1 includes a parameter setting processing unit 12 that reads data item management information including parameter values ​​to be set for virtual components and outputs a parameter setting screen 100 in which the set parameter values ​​can be changed. The parameter setting processing unit 12 generates a parameter setting screen 100 that displays the type of parameter value corresponding to the parameter value. As a result, even users with little knowledge of simulation can notice which parameters should be changed when the simulation results deviate from real data by looking at the type of parameter value on the parameter setting screen 100. And since the values ​​are changed mainly for the parameters that should be changed, the time required to bring the simulation results closer to real data can be shortened compared to conventional methods, and it becomes possible to change parameters to improve the accuracy of the simulation without the help of an experienced user.

[0059] Embodiment 2. Figure 11 shows an example of the functional configuration of the simulation device according to Embodiment 2. In addition to the configuration of Figure 7, the simulation device 10a further includes a gap determination unit 17 and a gap reduction item identification unit 18.

[0060] The gap determination unit 17 compares the real data with the simulation results from the simulation unit 15 corresponding to the real data to determine if there is a gap, which is the difference between the value of a user-defined verification item and the value corresponding to the verification item obtained in the simulation. The gap determination unit 17 determines whether there is a gap between the real data and the simulation results by determining whether the difference between the two is outside a predetermined range. If the difference is outside the predetermined range, the gap determination unit 17 instructs the gap reduction item identification unit 18 to identify an item that will reduce the gap. The predetermined range can be the error range.

[0061] Figure 12 shows an example of the difference between the simulation results and real data. Here, image GR shows the real domain, which is the area of ​​the simulation target 60 in real space, and image GD shows the digital domain, which is the area of ​​the simulation target in virtual space corresponding to the real domain.

[0062] As shown in image GD, in the digital realm, actual values ​​can be achieved in line with the planned values ​​through appropriate placement of workers and equipment, proper supply and transport of parts, and ideal worker and robot work efficiency. In this example, a simulation is performed in which the planned number of products manufactured is 340, and the actual number manufactured is also 340.

[0063] However, as shown in image GR, in the real world, the work efficiency of workers or robots differs from the ideal, becoming a bottleneck. This results in parts accumulating and people being idle, indicating that production is not proceeding as planned due to inadequate staffing. In this example, the planned number of products manufactured was 340, while the actual number was 240.

[0064] The gap determination unit 17 determines whether there is a gap between the digital domain and the real domain. If a gap exists, the gap determination unit 17 outputs a gap display screen showing the gap between the real data and the simulation results. In one example, the gap determination unit 17 outputs the gap display screen to the user terminal 50. The gap determination unit 17 may output a gap display screen in the format shown in Figure 12, or it may output a gap display screen in another format.

[0065] Returning to Figure 11, the gap reduction item identification unit 18 identifies candidate parameters that cause a gap based on the real data and the simulation results, when there is a gap between the real data and the simulation results.

[0066] The parameter setting processing unit 12 displays at least one of the candidate parameter names, parameter values, and parameter value types identified by the gap reduction item identification unit 18 in the parameter setting area 103 of the displayed parameter setting screen 100 in a different format from others. Examples of display in a different format include highlighting, blinking, and marker display.

[0067] Here, we will explain an example of how to change parameters when there is a gap between real data and simulation results. Figure 13 schematically shows the difference between the results of work performed on the actual simulation target and the simulation results. In Figure 13, the processing performed on the simulation target 60 is broken down into multiple work processes, and the work time for each work process is aggregated using data collected from sensors or equipment installed on the simulation target 60. In other words, in Figure 13, the processing performed on the system in real space and the processing performed on the simulation target 60 are broken down into four work processes: "Work A," "Work B," "Work C," and "Work D." The length of each work process represents the work time. In Figure 13, the upper part schematically shows the results of the processing performed on the simulation target 60, i.e., the measured values ​​of the work time, and the lower part schematically shows the values ​​obtained from the simulation, i.e., the simulated values ​​of the work time. The data is collected from sensors or equipment by the real data collection unit 14.

[0068] Figures 14 to 16 are flowcharts illustrating an example of the procedure for the simulation method according to Embodiment 2. Here, we will describe the processing after the simulation has been executed once by the simulation unit 15.

[0069] First, the gap determination unit 17 acquires result information including real data and simulation results for the simulation target 60 (step S51). The result information is in the format shown in Figure 13, for example. Next, the gap determination unit 17 refers to the result information to confirm whether there is a gap between the real data and the simulation results in the entire process of the simulation target 60 (step S52).

[0070] Subsequently, the gap determination unit 17 refers to the result information and checks whether there is a gap between the real data and the simulation results for each work process in the simulation target 60 (step S53). In one example, it checks for each process whether there is a difference between the actual values ​​obtained from the actual simulation target 60 and the simulation results.

[0071] The gap determination unit 17 determines whether there is a gap between the real data and the simulation results in each work process (step S54). In other words, in the process of step S53, it determines whether there is a work process in which the difference between the real data and the simulation results is not within a predetermined range. If there is no gap in each work process (if the result is No in step S54), the simulation results are considered to accurately represent the real data, so no further parameter changes are necessary, and the process ends.

[0072] If there is a gap in at least one of the work processes (if the answer is Yes in step S54), the gap determination unit 17 identifies the work process with the gap as the work process that causes the difference (step S55). In the example in Figure 13, "task C" is identified as the work process that causes the difference. Note that in the example in Figure 13, "task C" is identified as the work process that causes the difference, but differences may occur in multiple work processes, so if there are multiple work processes that cause differences, multiple work processes will be identified.

[0073] Next, the gap reduction item identification unit 18 identifies the portion of the simulation program corresponding to the extracted work process and extracts the arguments present in the identified portion of the simulation program (step S56). Since the arguments of the simulation program usually use parameters, the parameters being used can be identified by looking at the arguments. In other words, the gap reduction item identification unit 18 identifies the parameters and components corresponding to the arguments from the extracted arguments (step S57). The gap reduction item identification unit 18 outputs the identified components and parameters to the parameter setting processing unit 12. In this way, the gap reduction item identification unit 18 decomposes the processing in the real-world system into multiple work processes and identifies the parameters used as arguments in the portion of the simulation program corresponding to the work process causing the gap as candidates for parameters causing the gap.

[0074] When the parameter setting processing unit 12 receives the components and parameters identified from the gap reduction item identification unit 18, it displays the display items for the identified components and parameters on the parameter setting screen 100 displayed on the user terminal 50 in a different format (step S58). Examples of display in a different format include highlighting, blinking, and marker display. The display items for a parameter are at least one of the parameter name, parameter value, and type of parameter value.

[0075] Figure 17 shows an example of a parameter setting screen. Components identical to those in Figure 8 are denoted by the same reference numerals, and their descriptions are omitted. In Figure 17, the display items of the components and parameters identified by the gap reduction item identification unit 18 in the parameter setting screen 100 of Figure 8 are shaded. Specifically, the names of the identified components displayed in the component selection area 101 are shaded, and the values ​​of the identified parameters in the parameter setting area 103, i.e., the parameter input area 1032, are shaded. However, this is just an example, and the names of the parameters in the parameter setting area 103, i.e., the name display area 1031, and the types of parameter values, i.e., the type input area 1033, may also be displayed in a different format.

[0076] In step S58, the parameter setting processing unit 12 determines whether the value in the type input area 1033 of the identified parameter is an "actual value". If it is not an "actual value", it displays the display items for this parameter in a different format than the others. If the value in the type input area 1033 of the identified parameter is an "actual value", the parameter setting processing unit 12 may display the display items for this parameter in the same format as the others. This is because if it is an "actual value", there is no room to change the parameter value. This prevents the user from perceiving that a parameter that is an "actual value" is subject to change.

[0077] The user modifies the parameter values ​​of components displayed in a different format on the parameter setting screen 100, where the parameter value type is not "actual value". At this time, the user may use actual values ​​collected by the real data collection unit 14 from the actual simulation target 60 of the result information acquired in step S51 as the parameter values. After the user has finished modifying the parameter values ​​of the components displayed in a different format, the user selects other components displayed in a different format whose parameter values ​​have not yet been modified and proceeds to modify their parameter values ​​in the same way.

[0078] Returning to Figure 15, the parameter setting processing unit 12 accepts the user's parameter modification on the parameter setting screen 100 (step S59). Subsequently, the parameter setting processing unit 12 reflects the modified contents of the parameter setting screen 100 in the simulation unit 15 (step S60), and saves the modified contents of the parameter setting screen 100 in the data item management information storage unit 33 of the data item management device 30 (step S61).

[0079] The simulation unit 15 performs a simulation according to the set parameters (step S62). After the simulation is performed, the real data collection unit 14 collects real data. Then, the gap determination unit 17 obtains result information including the real data and the simulation results for the simulation target 60 (step S63), and determines whether there is still a gap between the real data and the simulation results (step S64). In one example, the gap determination unit 17 determines whether there is a gap between the real data and the simulation results for the work process identified in step S55.

[0080] If there is a gap between the real data and the simulation results (if the answer is Yes in step S64), the parameter setting processing unit 12 detects the parts of the parameters and components identified in step S57 that were not changed (step S65). Based on the detection results, the parameter setting processing unit 12 determines whether there are any parts that were not changed (step S66). For example, if the parameter setting processing unit 12 finds that there are parameter values ​​other than "actual values" in areas that are displayed differently from others on the parameter setting screen 100 received in step S59, it can determine that there are parts of the parameters and components identified in step S57 that were not changed. Alternatively, if there are no parameter values ​​other than "actual values" in areas that are displayed differently from others, the parameter setting processing unit 12 can determine that there are no parts of the parameters and components identified in step S57 that were not changed.

[0081] If there are any parts that were not changed (if the answer is Yes in step S66), the parameter setting processing unit 12 sends the detected parameters and components back to the parameter setting processing unit 12. When the parameter setting processing unit 12 receives the parameters and components that were not changed, it displays the display items for the unchanged components and parameters in a different format than the others (step S67). The parameter setting processing unit 12 also displays to the user terminal 50 that there are parameters that can be modified (step S68). Then, the process returns to step S59.

[0082] If there is no gap between the real data and the simulation results in step S64 (i.e., the result is No in step S64), the parameter setting processing unit 12 transmits the contents of the parameter setting screen 100 to the data item management device 30 via the data transmission unit 13 (step S69). Upon receiving the contents of the parameter setting screen 100, the data item management device 30 stores the received contents of the parameter setting screen 100 in the data item management information storage unit 33. This completes the process.

[0083] At this time, the contents of the parameter setting screen 100 that the data item management device 30 receives from the simulation device 10a are considered to be the result of the user optimizing the parameter values ​​so that the gap between the real data and the simulation results falls within a predetermined range. For this reason, the data item management unit 32 may generate an initial value setting request to set these parameter values ​​as initial values, and the data transmission unit 34 may send the initial value setting request to the initial setting information management device 40. The initial value setting request is information that includes a pair of parameter items and parameter values ​​for the simulation device 10a. When the management processing unit 44 of the initial setting information management device 40 receives the initial value setting request, it reflects the contents of the received initial value setting request in the initial setting information storage unit 41.

[0084] Furthermore, if there are no parts that were not changed in step S66 (i.e., the result is No in step S66), it indicates that even if all the parameters and components identified in step S57 are corrected, the gap between the real data and the simulation results will not be resolved. In such cases, it is considered that the problem lies in the accuracy of the simulation program used in the simulation unit 15, and it cannot be resolved without adding new parameters to the simulation program. In Embodiment 2, the process terminates in such cases. Embodiment 4 describes a method for improving the accuracy of the simulation program.

[0085] In Embodiment 2, the simulation device 10a further includes a real data collection unit 14 that collects real data, which is data showing the results of the operation of a system in real space, and a gap determination unit 17 that compares the real data with the simulation results from the simulation unit 15 corresponding to the real data and determines whether there is a gap between the two. If a gap exists, the gap determination unit 17 outputs a gap display screen that shows the gap between the real data and the simulation results. This makes it possible to visually display the difference between the real data and the simulation results to the user. Furthermore, while conventionally users had to rely on their skills to find gaps, the simulation device 10a determines and displays whether or not there is a gap, so it does not depend on the user's skill, and the simulation device 10a can be used by a wide range of general users.

[0086] Furthermore, the simulation device 10a is further equipped with a gap reduction item identification unit 18 that identifies the parameter causing the gap based on the real data and the simulation results when there is a gap between the real data and the simulation results. Specifically, the gap reduction item identification unit 18 decomposes the processing in the real-world system into multiple work processes and identifies the parameter used as an argument in the part of the simulation program corresponding to the work process causing the gap as a candidate for the parameter causing the gap. The parameter setting processing unit 12 then displays the identified candidate parameter items in a different display format on the parameter setting screen 100. This makes it possible for the user to recognize the candidate parameters to be changed on the parameter setting screen 100. In other words, even a user who is not proficient in simulations can change the parameters to reduce the gap between the real data and the simulation results, that is, to obtain more accurate simulation results.

[0087] Embodiment 3. Figure 18 is a diagram showing an example of the functional configuration of the simulation device according to Embodiment 3. In addition to the configuration in Figure 7, the simulation device 10b further includes a data type rate management unit 20. The data type rate management unit 20 sets a value in the simulation unit 15 obtained by multiplying the parameter value set on the parameter setting screen 100 by a coefficient set according to the type of parameter value. In one example, the coefficient according to the type of parameter value is stored as coefficient setting information. An example of the coefficient is "0.1" for "initial value", "0.5" for "planned value", "1" for "actual value", and "0" for "not applicable".

[0088] In this way, the coefficients are set lower for parameter values ​​that are generally considered to be far removed from "actual values," allowing simulations to be performed based on data that accurately reflects reality. In this case, the accuracy of the simulation results obtained using parameters whose values ​​are "initial values," "planned values," and "not applicable" will be lower than the accuracy of the simulation results obtained using parameters whose values ​​are "actual values." By intentionally making the parameter values ​​incorrect, it becomes easier to identify the parameters that cause gaps when there are discrepancies between real data and simulation results.

[0089] Furthermore, the data type ratio management unit 20 calculates and outputs the accuracy of the simulation according to the setting status of the types of parameter values ​​set on the parameter setting screen 100 executed by the simulation unit 15. In other words, the data type ratio management unit 20 calculates an index indicating how reliable the parameter values ​​were used to perform the simulation, based on the ratio of the types of parameter values ​​set in the simulation device 10b.

[0090] For example, if the parameter setting screen 100 has a parameters set to "initial value," b parameters set to "planned value," c parameters set to "actual value," and d parameters set to "not applicable," the data type rate management unit 20 calculates the index as shown in the following equation (1).

[0091] Index=0.1×a+0.5×b+1×c+0×d...(1)

[0092] The data type rate management unit 20 displays the calculated indicator along with the simulation results, for example. The closer the indicator is to "a + b + c + d", the higher the accuracy of the simulation, and the closer it is to 0, the lower the accuracy of the simulation.

[0093] Conventionally, there was no function to manage the types of parameter values, and simulations were performed assuming all numerical values ​​set for parameters were positive, which meant that the simulation results could differ from the behavior in real space. However, in Embodiment 3, it is assumed that the type of parameter value corresponds to the accuracy of the simulation results, and the parameter value is multiplied by a coefficient corresponding to the type of parameter value and used in the simulation. As a result, the simulation unit 15 can perform simulations based on data that matches reality.

[0094] Furthermore, by presenting indicators showing the reliability of the simulation results along with the simulation results themselves, it is possible to visualize how accurately the data used in the simulation is input. It also allows for understanding the accuracy of the simulation based on the data being used.

[0095] Embodiment 4. Figure 19 shows an example of the functional configuration of the simulation device according to Embodiment 4. Note that the same reference numerals are used for components identical to those described in Embodiments 1 and 2, and their descriptions are omitted.

[0096] The simulation device 10c according to Embodiment 4 further includes a user input item reflection unit 21 in addition to the configuration of the simulation device 10a of Embodiment 2. The user input item reflection unit 21 adds parameters to bridge the gap between the real data and the simulation results when there is a gap between the real data and the simulation results, and all the parameters identified by the gap reduction item identification unit 18 are values ​​that cannot be changed, i.e., the type of parameter value is an actual value. The user input item reflection unit 21 adds parameters on the simulation device 10c and reflects the added content in the data item management device 30 and the initial setting information management device 40.

[0097] Specifically, the user input item reflection unit 21 aggregates the parameter items, targeting all parameter items managed by the data item management device 30 or the initial setting information management device 40. The user input item reflection unit 21 also obtains the distribution of the level of detail of the parameter items in each group, obtained by classifying the parameter items according to the attributes of the simulation target 60. The attributes are the function of the simulation target 60, the area to be simulated, etc. The level of detail of the parameter items is, for example, the number of parameter items included in the group. If the number of parameter items included in the attribute group is large, it means that detailed settings have been made for that attribute, and if the number of parameter items included in the group is small, it means that coarse settings have been made for that attribute. In other words, the coarser the level of detail of the parameter items, the more room there is to add parameter items.

[0098] The user input item reflection unit 21 extracts items with coarse detail from multiple groups classified by attribute to be designated as the item addition target group, and extracts items with fine detail to be designated as the reference group. The user input item reflection unit 21 may also designate a group containing the candidate parameters identified by the gap reduction item identification unit 18 as the item addition target group. The user input item reflection unit 21 compares the parameter items of the item addition target group and the reference group and determines the additional items that are missing from the item addition target group. The user input item reflection unit 21 also determines the parameter values ​​to be set for the determined additional items. When searching for missing parameter items, the numerical values ​​used for verification can be reused as the parameter values ​​to be set for the additional items. Here, the numerical values ​​used for verification will be explained. After the simulation results are output, if the output is different from the desired result, the simulation movement may be manually modified to obtain the ideal simulation result. For example, in a real-world system where a workpiece is transported and processed, if the route showing the movement of the workpiece is rough, the movement of the workpiece may be manually modified. When the movement of a workpiece is manually modified or specified, numerical values ​​such as the workpiece's position are generated as a result of this movement. These numerical values ​​are used for verification, and the user input item reflection unit 21 may reuse these values ​​as parameters. Alternatively, numerical values ​​used in the reference group used when determining additional items can be reused. Or, as the parameter value to be set for an additional item, a value obtained by statistical processing, such as averaging the numerical values ​​used in other groups including the reference group that has the same item as the additional item, can be used.

[0099] Furthermore, the user input item reflection unit 21 reflects the determined additional items in the data item management device 30 and the initial setting information management device 40.

[0100] Next, the method for determining additional items in the user input item reflection unit 21 will be explained. Figure 20 is a flowchart showing an example of the procedure for determining additional items. In one example, this method for determining additional items is executed after it is determined that there are no unchanged parts (if the result is No in step S66) for the parameters and components identified in step S66 of Figure 16 as corresponding to work processes that create a gap between real data and simulation results.

[0101] First, the user input item reflection unit 21 aggregates the parameter items for all parameters managed by the data item management device 30 or the initial setting information management device 40 (step S91). In other words, the user input item reflection unit 21 aggregates the parameters used in Figures 14 to 16.

[0102] Next, the user input item reflection unit 21 classifies the parameter items according to the attributes of the simulation target 60, and the classified items are grouped (step S92). The user input item reflection unit 21 also examines the level of detail, which is the distribution of parameter items in each classified group (step S93). Some groups, or attributes, have many parameter items, while others have few. Groups with many parameter items are finely configured and can be said to have a high level of detail. On the other hand, groups with few parameter items are coarsely configured and can be said to have a low level of detail. Therefore, for groups with a low level of detail, it is possible to add more parameter items to increase the level of detail.

[0103] Subsequently, the user input item reflection unit 21 extracts the group with the lowest level of detail for the parameter items from among the classified groups and designates it as the group to which items will be added (step S94). In one example, the group with the fewest number of parameter items among the classified groups can be designated as the group to which items will be added. In another example, one of the groups among the classified groups that has fewer parameter items than a predetermined number can be designated as the group to which items will be added. In yet another example, a group containing candidate parameters that cause a gap between real data and simulation results can be designated as the group to which items will be added.

[0104] Furthermore, the user input item reflection unit 21 extracts a group from the classified multiple groups that has a high level of detail in the parameter items as a reference group (step S95). The user input item reflection unit 21 then compares the parameter items of the item addition target group and the reference group (step S96) and determines an additional item which is the parameter item that is missing in the item addition target group (step S97). The user input item reflection unit 21 also determines the parameter value to be set for the determined additional item (step S98). The numerical value used in the reference group used when determining the additional item can be reused as the parameter value to be set for the additional item. Alternatively, the value to be set for the additional item can be a value obtained by statistical processing, such as averaging the numerical values ​​used in other groups that include the reference group having the same item as the additional item.

[0105] Subsequently, the user input item reflection unit 21 sends an item addition request to the data item management device 30 and the initial setting information management device 40 to add the additional items and the parameter values ​​of the additional items (step S99). The data item management unit 32 of the data item management device 30 adds the additional items and parameter values ​​included in the item addition request to the data item management information in the data item management information storage unit 33 corresponding to the simulation device 10c. The management processing unit 44 of the initial setting information management device 40 adds the additional items and parameter values ​​included in the item addition request to the initial setting information in the initial setting information storage unit 41. With this, the process is completed.

[0106] The simulation apparatus 10c of Embodiment 4 further includes a user input item reflection unit 21 that, when all of the parameter value types of the identified candidate parameters are of a type where the parameter values ​​cannot be changed, classifies all parameters based on their attributes, compares the distribution of parameter items in the classified groups into coarse and fine distributions, and adds the missing parameter items in the coarse group to the coarse group. The user input item reflection unit 21 also reflects the added content in the data item management device 30 and the initial setting information management device 40. This has the effect of appropriately managing items that affect the accuracy of the simulation.

[0107] Embodiment 5. Embodiment 4 showed an example of adding parameter items from a group with low detail when the accuracy of the simulation results does not improve. However, parameter items that improve the accuracy of the simulation results may be added in other ways.

[0108] Figure 21 is a diagram showing an example of the functional configuration of a simulation device according to Embodiment 5. In addition to the configuration of the simulation device 10a of Embodiment 2, the simulation device 10d further includes an artificial intelligence (AI) unit 22 and an additional item setting unit 23.

[0109] The AI ​​unit 22 includes a learning model. One example of a learning model provided in the AI ​​unit 22 is a language model such as GPT (Generative Pretrained Transformer) or BERT (Bidirectional Encoder Representations from Transformers). Another example of a learning model provided in the AI ​​unit 22 is an image recognition model that learns after extracting feature parameters from image data, such as a Convolutional Neural Network (CNN). The learning model may be composed of a combination of multiple algorithms including these.

[0110] In one example, the learning model provided in the AI ​​unit 22 is a learning model generated by prior machine learning. Prior machine learning may be performed in the AI ​​unit 22 or outside the simulation device 10d. The AI ​​unit 22 may update the learning model as needed by additional machine learning. The AI ​​unit 22 may generate or update the learning model by machine learning using training data.

[0111] Here, a learning model is constructed with a relationship between the combination of parameter items and values ​​stored in the data item management information of the data item management information storage unit 33 of the data item management device 30, and the simulation results generated based on the combination of parameter items and values, as input and output. This learning model learns how the parameter items affect the location and movement of the simulation target 60, and how this effect changes depending on the parameter values, based on the simulation results. In other words, it is a learning model for generative AI that generates the necessary combination of parameter items and values ​​for the desired simulation results. In one example, the AI ​​unit 22 generates or updates the learning model by supervised learning. In this case, the combination of parameter items and values ​​corresponds to the input, and the simulation results correspond to labels or ground truth data.

[0112] The additional item setting unit 23 receives a request from the parameter setting processing unit 12 to add a parameter item and uses the AI ​​unit 22 to generate additional item candidates, which are combinations of parameter items and values ​​that can fill the gap. Here, the parameter setting processing unit 12 outputs an item addition request to the additional item setting unit 23 if it determines that there are no parts that have not been changed for the parameters and components identified as corresponding to work processes that cause a gap between real data and simulation results. The item addition request includes the location of the simulation defect.

[0113] Since the item addition request from the parameter setting processing unit 12 clearly indicates a faulty area in the simulation, the additional item setting unit 23 outputs an instruction to the AI ​​unit 22 to generate a combination of parameter items and values ​​to resolve the faulty area. The additional item setting unit 23 acquires the combination of parameter items and values ​​generated by the AI ​​unit 22 in response to the instruction and temporarily stores them as additional item candidates. The additional item setting unit 23 outputs an instruction to the AI ​​unit 22 to generate additional item candidates until the number of stored additional item candidates exceeds a predetermined number, and stores the resulting additional item candidates. At this time, the additional item setting unit 23 stores additional item candidates for each faulty area case.

[0114] When the number of candidate additional items exceeds a predetermined number, the additional item setting unit 23 determines a parameter item as the missing parameter item, which is a combination of a parameter value that has been stably generated from the stock of candidate additional items and the parameter item that corresponds to this value. Here, a combination of a parameter item and a value that has been stably generated includes combinations of parameter values ​​that are exactly the same and the parameter item that corresponds to this value, and combinations of parameter values ​​that are not exactly the same but can be considered the same and the parameter item that corresponds to this value. For example, in the case of parameter values, if the values ​​of multiple parameters match within the margin of error, these parameter values ​​can be considered the same. The additional item setting unit 23 also determines a recommended value for the parameter value corresponding to the parameter item to be added. When searching for a missing parameter item as the parameter value to be set for an additional item, the numerical values ​​used for verification as described in Embodiment 4 can be reused. Alternatively, the additional item setting unit 23 can determine the parameter value based on information showing the relationship between the magnitude of the gap in the simulation results and the setting position of the parameter value within the setting range of the parameter item value. In other words, the additional item setting unit 23 can modify or set the parameter value in proportion to the gap. Since the parameter value of the parameter item simulates physical phenomena, there are upper and lower limits to the parameter values ​​that can be set. This becomes the setting range for the parameter item's value. By pre-determining information showing the relationship between the magnitude of the gap in the simulation result and the setting position of the parameter value within the setting range for the parameter item's value, it is possible to determine the setting position of the parameter value such that the magnitude of the gap is no longer within the margin of error. Conventionally, users basically modify or determine the parameter value of additional parameter items based on their experience after looking at the simulation results, but the additional item setting unit 23 can determine the parameter value in a method similar to such experience-based user modification or determination.Alternatively, the additional item setting unit 23 may, in one example, use a value obtained by performing statistical processing, such as averaging the values ​​of the stored parameters, as the parameter value to be set for the additional item.

[0115] Furthermore, the additional item setting unit 23 reflects the determined additional items in the data item management device 30 and the initial setting information management device 40.

[0116] Next, the method for determining additional items will be explained. Figure 22 is a flowchart showing an example of the procedure for determining additional items according to Embodiment 5. First, the AI ​​unit 22 constructs a learning model as an input-output relationship between the combination of parameter items and values ​​stored in the data item management information of the data item management information storage unit 33 of the data item management device 30, and the simulation results simulated based on the combination of parameter items and values ​​(step S111). As described above, this learning model is a learning model for generative AI that generates the necessary combination of parameter items and values ​​for the desired simulation result.

[0117] In step S66 of Figure 16, if the parameter setting processing unit 12 determines that there are no unchanged parts in the parameters and components it has identified as corresponding to work processes that cause a gap between real data and simulation results, the parameter setting processing unit 12 outputs an item addition request to the additional item setting unit 23 that includes the defective parts that cause the gap between real data and simulation results.

[0118] The additional item setting unit 23 determines whether an item addition request has been received (step S112). If no item addition request has been received (if the result is No in step S112), the process returns to step S111. In one example, the process in step S111 can be performed each time the parameter value is changed to improve the accuracy of the learning model.

[0119] If an item addition request is received (if the answer is Yes in step S112), the item addition setting unit 23 generates an instruction statement instructing the generation of parameter items to be added in order to resolve the problematic area in the item addition request, and outputs it to the AI ​​unit 22 (step S113). The instruction statement includes the content of the simulation, the parameters to be used, and the desired simulation result. In one example, the content of the simulation is the simulation program used by the simulation unit 15. In one example, the parameters to be used are the parameter items and values ​​included in the data item management information of the data item management information storage unit 33 of the data item management device 30 that are associated with the problematic area in the item addition request. The desired simulation result is the problematic area in the item addition request, specifically the part where there is a gap between the real data and the simulation result. In one example, the desired simulation result is to make the gap between the real data and the simulation result, which is the problematic area, zero. The instruction statement may also be created by manual input by the user using the simulation device 10d.

[0120] When the AI ​​unit 22 receives an instruction, it uses a learning model to generate additional item candidates, which are the items and values ​​of the parameters to be added, as a response to the instruction, and outputs them to the additional item setting unit 23 (step S114). Since this learning model is a model that learns how the parameter items affect the simulation results, the AI ​​unit 22 can generate parameter items from a new perspective by working backward from the desired simulation result, for example, eliminating the gap between real data and the simulation results.

[0121] The additional item setting unit 23 temporarily stores the acquired additional item candidates (step S115). Additional item candidates are stored for each case of the simulation result in which a malfunction occurred. The additional item setting unit 23 determines whether the number of additional item candidates temporarily stored exceeds a predetermined number (step S116). If the number of additional item candidates is less than or equal to the predetermined number (if the result is No in step S116), the process returns to step S113. Then, the process of acquiring additional item candidates generated by the AI ​​unit 22 is executed until the number of additional item candidates exceeds the predetermined number. At this time, the gist of the instruction statement generated in step S113 is the same, but the expression may be changed or the instruction content may be made more detailed.

[0122] If the number of candidate additional items exceeds a predetermined number (if the answer is Yes in step S116), the additional item setting unit 23 determines a parameter item that has been stably generated from the temporarily stored combinations of parameter items and values ​​as the parameter item missing in the existing simulation program (step S117). The additional item setting unit 23 also calculates the parameter value corresponding to the determined parameter item (step S118). Since the simulator usage environment differs for each user, the additional item setting unit 23 calculates the parameter value recommended for the user's simulation device 10d.

[0123] Subsequently, the additional item setting unit 23 sends an item addition request to the data item management device 30 and the initial setting information management device 40 to add the additional item and the parameter values ​​for the additional item (step S119). The data item management unit 32 of the data item management device 30 adds the additional item and parameter values ​​included in the item addition request to the data item management information storage unit 33 corresponding to the simulation device 10d. The management processing unit 44 of the initial setting information management device 40 adds the additional item and parameter values ​​included in the item addition request to the initial setting information storage unit 41 corresponding to the simulation device 10d. With this, the process is completed.

[0124] As described above, in the simulation apparatus 10d of Embodiment 5, if all of the parameter values ​​identified as the cause of the difference between real data and simulation results are of a type where the parameter values ​​cannot be changed, the additional item setting unit 23 causes the AI ​​unit 22 to generate candidate parameters to be added based on the simulation content, the parameters used, and the simulation results to be obtained. The additional item setting unit 23 then determines the additional items from the candidate parameters to be added, and further reflects the determined additional items in the data item management device 30 and the initial setting information management device 40. This has the effect of appropriately managing items that affect the accuracy of the simulation.

[0125] Next, the hardware configuration of the simulation devices 10, 10a-10d, data item management device 30, and initial setting information management device 40 used in Embodiments 1 to 5 will be described. In Embodiments 1 to 5, the simulation devices 10, 10a-10d, data item management device 30, and initial setting information management device 40 function as the simulation devices 10, 10a-10d, data item management device 30, and initial setting information management device 40 by executing a computer program on the computer system that describes the processing in the simulation devices 10, 10a-10d, data item management device 30, and initial setting information management device 40, respectively.

[0126] Figure 23 is a block diagram showing an example of the configuration of a computer system that implements a simulation device, a data item management device, and an initial setting information management device according to Embodiments 1 to 5. As shown in Figure 23, this computer system 90 includes a control unit 901, an input unit 902, a storage unit 903, a display unit 904, a communication unit 905, and an output unit 906, which are connected via a system bus 907.

[0127] In Figure 23, the control unit 901 is, in one example, a processor such as a CPU (Central Processing Unit), and executes a program that describes the processing in the simulation devices 10, 10a-10d, the data item management device 30, and the initial setting information management device 40 of Embodiments 1 to 5. The input unit 902 is, in one example, composed of a keyboard, mouse, etc., and is used by the user of the computer system 90 to input various information. The storage unit 903 includes various types of memory such as RAM (Random Access Memory) and ROM (Read Only Memory), and storage devices such as a hard disk, and stores the program that the control unit 901 should execute, necessary data obtained in the process of processing, etc. The storage unit 903 is also used as a temporary storage area for the program. The display unit 904 is composed of a display, liquid crystal display panel, etc., and displays various screens to the user of the computer system 90. In one example, the input unit 902 and the display unit 904 may be configured as a touch panel in which the input unit 902 and the display unit 904 are integrally formed. The communication unit 905 consists of a receiver and transmitter that perform communication processing. The output unit 906 consists of a printer, speaker, etc. Note that Figure 23 is an example, and the configuration of the computer system 90 is not limited to the example in Figure 23.

[0128] Here, we will describe an example of the operation of the computer system 90 until the program becomes executable. In the computer system 90 with the above configuration, for example, the program is installed in the storage unit 903 from a CD-ROM or DVD-ROM set in a CD (Compact Disc)-ROM drive or DVD (Digital Versatile Disc)-ROM drive (not shown). When the program is executed, the program read from the storage unit 903 is stored in the main memory area of ​​the storage unit 903. In this state, the control unit 901 performs processing as the simulation devices 10, 10a-10d, data item management device 30, and initial setting information management device 40 of Embodiments 1 to 5 according to the program stored in the storage unit 903.

[0129] In the above description, a program describing the processing in the simulation devices 10, 10a-10d, the data item management device 30, and the initial setting information management device 40 is provided using a CD-ROM or DVD-ROM as the recording medium. However, the system is not limited to this, and depending on the configuration of the computer system 90, the capacity of the program to be provided, for example, a program provided via a transmission medium such as the Internet through the communication unit 905 may be used.

[0130] The simulation system 1 described in Embodiments 1 to 5 is applicable to various uses. Below, we will describe an overview of how the simulation system 1 can be applied to urban design, buildings, elevator construction and maintenance, and water treatment systems.

[0131] <When Simulation System 1 is applied to urban design> Figure 24 shows an example of applying a simulation system to a city to realize a digital twin of the city. Figure 24 shows the city that is the simulation target 60 in the real world and the city in the virtual world.

[0132] This simulation can be used, in one example, for urban design. Figure 25 shows an example of parameters used in urban design in a virtual city. In this urban design example, it is possible to verify changes in people's movement patterns, changes in the placement of buildings or facilities, and changes in the layout within buildings based on (1) the congestion of the city, (2) the congestion of buildings, (3) the congestion of each floor of a building, and (4) the air quality of the building. In addition, in this urban design example, it is possible to verify the reduction of the heat island effect by changing the height of a building or surrounding facilities based on (2) the congestion of buildings and (5) the environment around the building. Through such verification, it is possible to make people's living spaces more comfortable.

[0133] The table shown in Figure 25 contains the following items: the object to which the parameters for urban design described in (1) to (5) above are set, the parameter values ​​set for the object, and the type of parameter value. In this figure, the parameter value is shown as an example of the content entered as the parameter value, i.e., the parameter item. Also, the object corresponds to a component. The same applies to the following examples.

[0134] In this example, the objects are people, cars, air, sunlight, weather, and wind conditions, and parameters are set for these objects. As shown in Figure 24, Simulation System 1 acquires real data in real time from the system of a real-world city, analyzes and simulates the acquired real data in the system of a virtual city, and feeds the results back into the system of a real-world city.

[0135] However, some parameters, such as the number of people and traffic volume, are difficult to set appropriately because real-time data collection is challenging, resulting in parameter values ​​that do not reflect reality. In the example in Figure 25, this applies to parameters whose value type is set to "XX year statistics." By checking the year of the statistics for parameters whose value type is "XX year statistics," users can estimate which parameter items are causing a decrease in simulation accuracy. Then, users can obtain statistics from various years as needed and update the parameter values. In other words, by allowing users to select parameter values ​​from various years, simulation accuracy can be improved.

[0136] Thus, when performing a simulation, the user checks the type of parameter values ​​and modifies them so that the simulation results from the virtual city system match the real data of the real city system.

[0137] <When simulation system 1 is applied to a building> Figure 26 shows an example of how a simulation system can be applied to a building to realize a digital twin of the building. Figure 26 shows the building, which is the simulation target 60 in the virtual space.

[0138] In this simulation, for example, the use of materials and the progress of construction can be estimated based on the position of the crane and the positions of the personnel, allowing for verification of the progress of construction. Here, the position of the crane and the positions of the personnel include their movement history. The movement history includes information such as the movement path of the crane and personnel, the time and location of stops, and details of the operation. In addition, in this simulation, for example, the use of materials and the construction status, indicating what kind of assembly is being carried out, can be estimated based on the position of the crane and the positions of the personnel, allowing for verification of safety, such as the collapse of the building during construction due to errors in the assembly procedure.

[0139] Figure 27 shows an example of parameters used in the simulation of a building in a virtual space. In this example, the objects are the building, crane, people, and materials, and parameters are set for these objects. Simulation system 1 acquires real data in real time from the building system in the real space, analyzes and simulates the building system in the virtual space based on the acquired real data, and feeds the results back to the building system in the real space.

[0140] However, some parameters may have values ​​that do not reflect the current situation. For example, for parameters whose value type is "planned value," it is difficult to set appropriate parameters because it is difficult to execute according to the planned value, or because it is difficult to obtain real data in real time. In the example in Figure 27, the parameter value type for the object "person" and "material" is set to "planned value." Therefore, it can be assumed that the user confirming that the parameter value type is "planned value" is a cause of decreased simulation accuracy. By updating the parameter values ​​whose value type is set to "planned value" and correcting the parameter value type from "planned value" to match the current situation, the simulation accuracy can be improved.

[0141] Thus, when performing a simulation, the user checks the type of parameter values ​​and changes the parameter values ​​so that the simulation results from the virtual building system match the real data of the real building system.

[0142] <When Simulation System 1 is applied to the construction and maintenance of elevators> Figure 28 shows an example of applying the simulation system to the construction of elevators to realize a digital twin of an elevator. Figure 29 shows an example of applying the simulation system to the maintenance of elevators to realize a digital twin of an elevator. Figures 28 and 29 show the elevator, which is the simulation target 60 in the real world, and the elevator in the virtual world.

[0143] This simulation can be used, for example, for the construction and maintenance verification of elevators. Figure 30 shows an example of parameters used for an elevator in a virtual space. Construction verification of elevators is performed, for example, when installing or renovating an elevator. Construction verification of elevators allows for (6) progress verification and (7) safety verification. (6) Progress verification verifies the progress of the elevator construction. (7) Safety verification verifies the safety of the construction, such as verifying assembly procedure errors and verifying elevator collapse. In addition, (8) elevator maintenance verification is performed on elevators that are in operation.

[0144] The table shown in Figure 30 has the following items: the object to which the parameters for the construction and maintenance of the elevator described in (6) to (8) above are set, the parameter value to be set for the object, and the type of parameter value. In this figure, the parameter value is shown as an example of the content to be entered as the parameter value, i.e., the parameter item.

[0145] In this example, the objects are the entire elevator, elevator components, crane, people, and materials, and parameters will be set for these objects. Simulation system 1 acquires real data in real time from the elevator system in the real space, analyzes and simulates the acquired real data in the elevator system in the virtual space, and feeds the results back into the elevator system in the real space.

[0146] However, some parameters are difficult to set appropriately, meaning that their values ​​may not reflect the current situation. For example, in the elevator construction verification shown in Figure 30, the "people" and "materials" objects, whose parameter value type is set to "planned value," are difficult to execute according to the planned value or to obtain real-time data for. Therefore, the user can deduce that parameters whose value type is "planned value" are causing a decrease in simulation accuracy. Simulation accuracy can be improved by updating the values ​​of parameters whose value type is set to "planned value" and correcting the parameter value type from "planned value" to match the current situation.

[0147] Furthermore, in the elevator maintenance verification shown in Figure 30, it is difficult to perform operations according to planned values ​​or obtain real-time data for parameters such as "heat," "life," and "torque / force / load," where the parameter value type is set to "estimated value." Therefore, users can deduce that parameters with a parameter value type set to "estimated value" are causing a decrease in simulation accuracy. Simulation accuracy can be improved by updating the values ​​of parameters with a parameter value type set to "estimated value" and correcting the parameter value type from "estimated value" to match the current situation.

[0148] In this way, when performing a simulation, the user checks the attribute, which is the type of parameter value, and modifies the parameter value so that the simulation results from the virtual elevator system match the real data of the elevator system in the real world.

[0149] <When Simulation System 1 is applied to a water treatment system> Figure 31 shows an example of how a simulation system can be applied to a water treatment system to realize a digital twin of the water treatment system. Figure 31 shows a sewage treatment plant, which is an example of a water treatment system that is the simulation target 60 in the real world, and a sewage treatment plant in the virtual world.

[0150] This simulation allows for the calculation of water treatment capacity based on factors such as the water treatment plant's capacity and the temperature that affects bacterial activity, thereby enabling verification of the water treatment situation. Water treatment capacity includes factors such as potential hydrogen (pH), water clarity (an indicator of water treatment capacity), filter contamination, and bacterial density.

[0151] Figure 32 shows an example of parameters used in a water treatment system in a virtual space. In this example, the objects are a water treatment plant and weather, and parameters are set for these objects. Simulation system 1 acquires real data in real time from the water treatment system in the real space, analyzes and simulates the virtual water treatment system based on the acquired real data, and feeds the results back to the water treatment system in the real space.

[0152] However, some parameters, such as those for "filter" and "bacteria," require actual measurements of filter contamination and bacterial density, making it difficult to set appropriate parameters, resulting in parameter values ​​that do not reflect the current situation. In the example in Figure 32, the parameter values ​​for "filter" and "bacteria" are set to either "estimated value" or "measured value." Here, the parameter value type is set to include "estimated or measured time" along with "estimated value" or "measured value." Therefore, by confirming that the parameter value type at a certain point in time is either "estimated value" or "measured value," that is, by confirming that the parameter value type is either "estimated value" or "measured value" and this "estimated or measured time," the user can infer that this is the cause of the decrease in simulation accuracy. By updating the parameter values ​​where the parameter value type is set to either "estimated value" or "measured value" along with "estimated or measured time," and by correcting the parameter value type from "estimated value" or "measured value" to match the current situation, the simulation accuracy can be improved.

[0153] Furthermore, water treatment process simulations can be used not only for the water treatment capacity mentioned above, but also for the water quality of the treated water, the amount of sludge generated in the water treatment process, the power consumption in the water treatment process, and so on. In these cases, the types of parameter values ​​set in the water treatment process simulation can be classified into, for example, state values, set values, and variable factors.

[0154] Status values ​​are status data that indicate the automatic control status of the water treatment process in the water treatment equipment of a water treatment plant. Status values ​​are detected by various sensors installed in the water treatment equipment of the water treatment plant. Examples of status values ​​include the water quality of the treated water in the water treatment process of the water treatment equipment of the water treatment plant, the amount of sludge generated in the water treatment process, the amount of water flowing into the water treatment process, the ammonia concentration in the water treatment process, the dissolved oxygen concentration in the reaction tank of the water treatment equipment, the activated sludge suspended solids (Mixed Liquor Suspended Solids: MLSS) in the treated water in the water treatment process, and the residual chlorine concentration in the treated water in the water treatment process.

[0155] The set values ​​are the operating conditions for the water treatment equipment in the water treatment plant. Examples of set values ​​include the aeration airflow rate, which is the amount of air supplied to the reaction tank of the water treatment equipment; the amount of coagulant injected into the downstream stage of the reaction tank of the water treatment equipment for the purpose of phosphorus removal; and the amount of hypochlorous acid injected into the chlorine mixing tank of the water treatment equipment.

[0156] Variables include, for example, weather, temperature, and season.

[0157] Users can easily identify which parameters need to be changed by checking the type of parameter value. For example, if the status value is real-time information detected by a sensor, and the setting value is information transmitted at a predetermined interval, for example, one day, then the accuracy of the simulation can be improved by mainly changing the values ​​of parameters whose parameter value type is "setting value".

[0158] Furthermore, correlated setpoints and state values ​​may be managed by the type of parameter value. For example, a setpoint correlated with the dissolved oxygen concentration in the reaction tank of a water treatment facility, which is a state value, is the operating conditions of the blower that supplies air to the reaction tank, i.e., the setpoint of the aeration airflow rate. In this case, the dissolved oxygen concentration, which is the "state value," and the aeration airflow rate, which is the "setpoint," are set to the same type, in this case, "setpoint." This allows the user to easily understand that, in one example, if there is a difference between the dissolved oxygen concentration obtained from the simulation and the dissolved oxygen concentration of the real data, the aeration airflow rate is likely the parameter that should be changed by checking the type of parameter value.

[0159] Thus, when performing a simulation, the user checks the type of parameter values ​​and modifies them so that the simulation results from the virtual water treatment system match the real data of the real-world water treatment system.

[0160] These are just examples, and the simulation system 1 according to Embodiments 1 to 5 can be applied to systems such as power systems and railway systems.

[0161] The configurations shown in the above embodiments are merely examples, and it is possible to combine them with other known technologies, combine different embodiments, and omit or modify parts of the configuration without departing from the gist of the invention.

[0162] 1 Simulation system, 10, 10a, 10b, 10c, 10d Simulation device, 11, 31, 43 Data receiving unit, 12 Parameter setting processing unit, 13, 34, 42 Data transmission unit, 14 Real data collection unit, 15 Simulation unit, 16 Result display processing unit, 17 Gap judgment unit, 18 Gap reduction item identification unit, 20 Data type rate management unit, 21 User input item reflection unit, 22 AI unit, 23 Additional item setting unit, 30 Data item management device, 32 Data item management unit, 33 Data item management information storage unit, 40 Initial setting information management device, 41 Initial setting information storage unit, 44 Management processing unit, 50 User terminal, 60 Simulation target, 70 Network, 90 Computer system, 100 Parameter setting screen, 101 Component selection area, 102 Simulation target display area, 103 Parameter setting area, 901 Control unit, 902 Input unit, 903 Memory unit, 904 Display unit, 905 Communication unit, 906 Output unit, 907 System bus, 1031 Name display area, 1032 Parameter input area, 1033 Type input area.

Claims

1. A simulation device that reproduces the operation of a real-world system by simulation using real data, which is information about the real-world system obtained from the real-world system, on a virtual system in a virtual space having the same virtual components as a real-world system that includes at least one component that performs an operation, the simulation device comprising: a parameter setting processing unit that reads data item management information including the values ​​of parameters to be set for the virtual components and outputs a parameter setting screen on which the set parameter values ​​can be changed; and a simulation unit that simulates the operation of the virtual system according to the contents set on the parameter setting screen, wherein the parameter setting processing unit generates the parameter setting screen that displays the type of parameter value corresponding to the parameter value.

2. The simulation apparatus according to claim 1, characterized in that the type of parameter value includes at least one of a type indicating that the parameter value can be changed and a type indicating that the parameter value cannot be changed based on the results of the simulation.

3. The simulation apparatus according to claim 1 or 2, characterized in that the parameter setting processing unit outputs a message prompting the user to update the type of value of the parameter when the value of the parameter is changed.

4. The simulation device according to any one of claims 1 to 3, further comprising: a real data collection unit that collects real data which is data indicating the results of the operation of the system in the real space; and a gap determination unit that compares the real data with the results of the simulation performed by the simulation unit corresponding to the real data and determines whether there is a gap which is the difference between the value of a verification item arbitrarily set by the user and the value corresponding to the verification item obtained in the simulation, wherein the gap determination unit outputs a gap display screen indicating the gap between the real data and the results of the simulation when there is a gap.

5. The simulation apparatus according to claim 4, further comprising a gap reduction item identification unit that identifies candidate parameters causing a gap based on the real data and the simulation results when there is a gap between the real data and the simulation results.

6. The simulation apparatus according to claim 5, characterized in that the gap reduction item identification unit decomposes the processing in the real-world system into a plurality of work processes, and identifies the parameter used as an argument in the part of the simulation program corresponding to the work process that causes the gap as a candidate for the parameter that causes the gap.

7. The simulation apparatus according to claim 6, further comprising a user input item reflection unit that, when all of the types of parameter values ​​of the identified candidate parameters are of a type where the parameter values ​​cannot be changed, classifies all parameters based on their attributes, compares the distribution of parameter items in the classified groups to be coarse and fine, and adds the missing parameter items in the coarse group to the coarse group.

8. The simulation apparatus according to claim 6, further comprising: an artificial intelligence unit having a learning model for generating combinations of items and values ​​of the necessary parameters for the desired simulation result; and an additional item setting unit that, when all of the identified types of parameter values ​​are of a type in which the parameter values ​​cannot be changed, uses the artificial intelligence unit to generate additional item candidates, which are combinations of items and values ​​of the parameters that can fill the gap.

9. The simulation apparatus according to claim 2, characterized in that when the parameter setting processing unit reads the data item management information in which the type of the parameter is set along with the value of the parameter, it sets the type of the value of the parameter corresponding to the parameter on the parameter setting screen according to the data item management information.

10. The simulation apparatus according to any one of 1 to 9, further comprising a data type rate management unit that calculates and outputs the accuracy of the simulation according to the setting status of the types of parameter values ​​set on the parameter setting screen executed by the simulation unit.

11. The simulation apparatus according to claim 10, characterized in that the data type rate management unit sets a value in the simulation unit obtained by multiplying the value of the parameter set on the parameter setting screen by a coefficient set according to the type of the value of the parameter.

12. A simulation system comprising: a simulation device according to any one of claims 1 to 11; and a data item management device for managing the data item management information, wherein the data item management device includes: a data receiving unit for receiving the data item management information, which includes the correspondence between the values ​​of the parameters set on the parameter setting screen of the simulation device and the types of values ​​of the parameters; and a data item management information storage unit for storing the data item management information.

13. The simulation system according to 12, further comprising an initial setting information management device for managing initial setting information which is the initial value of the parameters to be set in the virtual system of the simulation device, wherein the initial setting information management device comprises an initial setting information storage unit for storing the initial setting information of the simulation device, and a data transmission unit that, upon receiving a request from the simulation device to acquire the initial setting information of the parameters, acquires the initial setting information from the initial setting information storage unit and transmits it to the simulation device, wherein the parameter setting processing unit of the simulation device transmits a request to acquire the initial setting information to the initial setting information management device when the simulation device is used for the first time.

14. The simulation system according to claim 12 or 13, characterized in that when the simulation device is used for the second time or later, the parameter setting processing unit of the simulation device transmits a request to the data item management device to acquire the data item management information.

15. The simulation system according to 13, wherein the data item management device further comprises: a data management unit that generates an initial value setting request to set the optimized parameter value as an initial value when the parameter value of the data item management information is optimized for the simulation device; and a data transmission unit that transmits the initial value setting request to the initial setting information management device, wherein the initial setting information management device further comprises a management processing unit that, upon receiving the initial value setting request, reflects the contents of the initial value setting request in the initial setting information storage unit.

16. A program for a simulation device, characterized in that it causes a computer to execute: a parameter setting process step, which reads data item management information including parameter values ​​to be set for a virtual component in a virtual system in a virtual space having the same virtual component as a system in the real space that includes at least one component that performs an operation, and outputs a parameter setting screen on which the set parameter values ​​can be changed; and a simulation process step, which simulates the operation of the virtual system using real data, which is information of the system in the real space obtained from the system in the real space, according to the contents set on the parameter setting screen, wherein the parameter setting process step generates the parameter setting screen that displays the type of parameter value corresponding to the parameter value.

17. A simulation system program that causes a computer to execute: a parameter setting processing step which reads data item management information including parameter values ​​to be set for a virtual component in a virtual system in a virtual space that has the same virtual component as a system in the real space that includes at least one component that performs an operation, and outputs a parameter setting screen in which the set parameter values ​​can be changed; a simulation step which simulates the operation of the virtual system using real data, which is information of the system in the real space obtained from the system in the real space, according to the contents set on the parameter setting screen; a data receiving step which receives the data item management information including the correspondence between the parameter values ​​set on the parameter setting screen and the types of the parameter values; and a data item management information storage step which stores the data item management information, wherein the parameter setting processing step generates the parameter setting screen which displays the types of the parameter values ​​corresponding to the parameter values.

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