Support system and support method

Abstract

To provide a technique for supporting the achievement of a financial target and a non-financial target at a production site.SOLUTION: A support system is configured to: acquire a financial target and a non-financial target; generate a first measure for bringing a financial indicator value at a production site closer to the financial target based on information representative of an operating status of a production facility and the financial target; and generate a second measure for bringing a non-financial indicator value at the production site closer to the non-financial target based on information representative of the operation status of the production facility when the generated first measure is applied and the non-financial target.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a technique for supporting goal achievement in a production site. [Background technology]

[0002] In manufacturing sites, efforts to improve productivity and quality are underway on a daily basis. Recently, attempts have been made to utilize ICT and DX to analyze data collected from production sites and support problem-solving. For example, Patent Document 1 proposes a method for using computer simulations with 3D models of production lines to identify potential bottlenecks and improve production capacity in advance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2020-521251 Summary of the Invention [Problem to be solved by the invention]

[0004] In traditional manufacturing, the primary goal was to achieve targets related to production capacity and output, such as productivity and production volume (referred to as "financial targets"). However, in recent years, an increasing number of companies are striving to achieve not only financial targets but also social value-related targets, such as consideration for the global environment and improving work practices (referred to as "non-financial targets"). However, it is not easy to develop specific solutions (measures) that simultaneously satisfy both financial and non-financial targets, and it is difficult to say that methods for achieving this have been established. In the ideal future, it is desirable to realize a system in which production site systems automatically and autonomously change (improve) to achieve given financial and non-financial targets.

[0005] The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a technique for supporting the achievement of financial and non-financial goals at a production site. [Means for solving the problem]

[0006] The present disclosure includes a support system for supporting goal achievement at a production site, the support system having: a financial target acquisition unit that acquires financial targets, which are targets for financial indicators to be achieved at the production site; a non-financial target acquisition unit that acquires non-financial targets, which are targets for non-financial indicators to be achieved at the production site; a first measure generation unit that generates a first measure for bringing the value of a financial indicator at the production site closer to the financial target based on information representing the operating status of production equipment operating at the production site and the financial target; and a second measure generation unit that generates a second measure for bringing the value of a non-financial indicator at the production site closer to the non-financial target based on information representing the operating status of the production equipment when the first measure generated by the first measure generation unit is applied and the non-financial target.

[0007] The system may further include a financial indicator evaluation unit that acquires the change in financial indicators when the first measure is applied to the production site and evaluates whether the financial target has been achieved based on the change in financial indicators, and if the financial indicator evaluation unit evaluates that the financial target has not been achieved, the first measure generation unit may modify the first measure.

[0008] The method further includes a non-financial indicator evaluation unit that acquires a change in a non-financial indicator when the second measure is applied to the production site and evaluates whether or not the non-financial target has been achieved based on the change in the non-financial indicator, and the non-financial indicator evaluation unit evaluates that the non-financial target has not been achieved. In this case, the second measure generator may modify the second measure.

[0009] The production system may further include a non-financial indicator evaluation unit that acquires change values ​​of non-financial indicators when the second measure is applied to the production site and evaluates whether the non-financial target has been achieved based on the change values ​​of the non-financial indicators, and a third measure generation unit that generates a third measure different from the second measure as a measure to bring the values ​​of non-financial indicators at the production site closer to the non-financial target when the non-financial indicator evaluation unit evaluates that the non-financial target has not been achieved.

[0010] The third measure generation unit may generate a plurality of measure candidates as the third measure, and present the generated plurality of measure candidates to a user.

[0011] The system may further include a learning unit that performs machine learning on information about a measure selected by a user from the plurality of candidate measures and the change in the non-financial indicators when the selected measure is applied to the production site.

[0012] The first strategy may include a control parameter for changing control of the production equipment.

[0013] The first measure generation unit may be configured by a trained model that has been machine-learned to output measures for bringing the values ​​of financial indicators at the production site closer to the financial targets based on information representing the operating status of the production equipment and the financial targets.

[0014] The second measure generation unit may be configured by a trained model that has been machine-learned to output measures for bringing the values ​​of non-financial indicators at the production site closer to the non-financial targets based on information representing the operating status of the production equipment and the non-financial targets.

[0015] The system may further include a simulator that performs an operation simulation using virtual production equipment that reproduces the production equipment in a virtual space, and the simulator estimates the operating status of the production equipment when the first measure is applied by applying the first measure generated by the first measure generation unit to the virtual production equipment and performing an operation simulation, and the second measure generation unit may generate the second measure using the estimation result by the simulator as information representing the operating status of the production equipment when the first measure is applied.

[0016] The system may further include a simulator that performs an operation simulation using virtual production equipment that reproduces the production equipment in a virtual space, and the simulator estimates the operating status of the production equipment when the first measure is applied by applying the first measure generated by the first measure generation unit to the virtual production equipment and performing an operation simulation, and the financial indicator evaluation unit may estimate a change in the financial indicator when the first measure is applied to the production equipment based on the estimation result by the simulator.

[0017] The system may further include a simulator that performs an operation simulation using virtual production equipment that reproduces the production equipment in a virtual space, wherein the simulator applies the second measure generated by the second measure generation unit to the virtual production equipment and performs an operation simulation to estimate the operating status of the production equipment when the second measure is applied, and the non-financial indicator evaluation unit may estimate a change in the non-financial indicator when the second measure is applied to the production equipment based on the estimation result by the simulator.

[0018] The present disclosure provides a method for supporting goal achievement at a production site by a computer, the method comprising the steps of: acquiring financial targets, which are targets for financial indicators to be achieved at the production site; and acquiring targets for non-financial indicators, which are targets for non-financial indicators to be achieved at the production site. a step of generating a first measure for bringing the value of a financial indicator at the production site closer to the financial target based on information representing the operating status of production equipment operating at the production site and the financial target; and a step of generating a second measure for bringing the value of a non-financial indicator at the production site closer to the non-financial target based on information representing the operating status of the production equipment when the first measure is applied and the non-financial target.

[0019] The present disclosure includes a program for causing a computer to execute each step of the above-described support method.

[0020] The present invention may be understood as a support system, goal achievement support system, measure provision system, measure planning system, optimization system, improvement system, autonomous management system, etc., having at least some of the above means. Furthermore, the present invention can also be understood as a support method, a support system control method, a goal achievement support method, measure provision method, measure planning method, optimization method, improvement method, autonomous management method, or a program for realizing such a method or a recording medium on which such a program is recorded, including at least some of the above processing. The above means and processing can be combined with each other as much as possible to constitute the present invention. [Effects of the Invention]

[0021] According to the present invention, it is possible to support the achievement of financial and non-financial goals at the production site. [Brief explanation of the drawings]

[0022] [Figure 1] FIG. 1 is a diagram showing a conceptual model of a support system to which the present invention is applied. [Figure 2] FIG. 2 is a block diagram showing the functional configuration of the support system according to the first embodiment. [Figure 3] 3A, 3B, and 3C are diagrams showing configuration examples when a trained model is used. [Figure 4] FIG. 4 is a flowchart of the assistance process executed by the assistance system according to the first embodiment. [Figure 5] FIG. 5 shows an example of optimization using the support system. [Figure 6] FIG. 6 shows an example of optimization using the support system. [Figure 7] FIG. 7 is a block diagram showing the functional configuration of the support system according to the second embodiment. [Figure 8] FIG. 8 is a flowchart of the assistance process executed by the assistance system according to the second embodiment. [Figure 9] FIG. 9 is a flowchart of the assistance process executed by the assistance system according to the third embodiment. [Figure 10] FIG. 10 is a block diagram showing the functional configuration of the support system according to the fourth embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0023] <Application example> 1 shows a conceptual model of a support system to which the present invention is applied. With reference to FIG. 1, an overview of the support system 1 will be described.

[0024] The support system 1 connects data with the company's management system MS and various systems of the production site PL, and generates and provides solutions (measures for solving problems) to improve the production site PL so as to achieve the financial and non-financial targets set by the management system MS.

[0025] "Financial targets" are target values ​​for financial indicators, mainly set by management and executives. Here, "financial indicators" refer to indicators related to production and manufacturing capacity and output, such as productivity, production volume, production value (sales), operating hours, operating rate, yield, non-defective product rate, first-run rate, and delivery date. Financial target data is obtained from a production management system (MS), such as an MES (Manufacturing Execution System).

[0026] "Non-financial goals" are target values ​​for non-financial indicators, primarily set by management. Here, "non-financial indicators" refer to indicators other than financial indicators, such as indicators related to social value, such as consideration for the global environment, achievement of SDGs, and improvements in working styles. Specifically, non-financial indicators include energy consumption, CO2 emissions, job satisfaction, work engagement, and safety and health. Non-financial goals are obtained, for example, from core management systems (MS) such as ERP (Enterprise Resource Planning).

[0027] When financial and non-financial goals are given, it is not easy to devise optimal solutions (measures) to simultaneously achieve both. This is because the direction and content of financial and non-financial goals are completely different, which increases the complexity and ambiguity of the problem to be solved.

[0028] Therefore, rather than simultaneously achieving both goals, Support System 1 adopts a sequential approach: first, improve financial indicators, then improve non-financial indicators. Specifically, in the first step, Support System 1 generates and provides a solution (first measure) focused on achieving financial targets. By applying this first measure to the production site's P&L, financial indicators are improved. In the second step, a solution (second measure) focused on achieving non-financial targets is generated and applied to the production site's P&L, improving non-financial indicators. This procedure is based on the hypothesis that improving financial indicators creates surplus (room for manpower) in the operation of production equipment, and that effectively utilizing this surplus can improve non-financial indicators. To give a simple example, if productivity can be improved and production equipment operating hours can be reduced (improved financial indicators), idle time will be created (created surplus). Shutting down production equipment during this idle time can improve non-financial indicators, such as reducing energy consumption and CO2 emissions. In this way, by breaking down a given major proposition (achieving financial and non-financial goals) into two sub-propositions, "improving financial indicators" and "improving non-financial indicators (using the surplus created by improving financial indicators)," the problem is simplified and made easier, allowing support system 1 to automatically generate a solution.

[0029] The measures provided by the support system 1 may be, for example, information specifying the behavior of resources (people, equipment, procedures, materials, etc.) related to manufacturing at the production site PL. A so-called "recipe" is one example of a measure. Preferably, the first measure provided in the first step is a control parameter for changing the control of the production equipment operating at the production site PL. The second measure provided in the second step may also be a control parameter for changing the control of the production equipment operating at the production site PL. In the case of such a measure, the measures (control parameters) provided by the support system 1 can be immediately applied to the production equipment, allowing improvement actions in accordance with the measures to be implemented immediately and automatically. Furthermore, by monitoring on-site data acquired from the production equipment, the effectiveness of improvement actions in accordance with the measures can be confirmed. By utilizing these, a system in which production equipment autonomously and automatically changes (improves) to achieve given financial and non-financial goals—in other words, autonomous management—can be realized. The first and second measures may include measures other than control parameters, for example, instructions other than control of production equipment, such as personnel allocation and work instructions (measures requiring human response).

[0030] Before (or instead of) applying the generated first and second measures to actual production equipment (real machines) operating at the production site PL, the support system 1 may apply the measures to virtual production equipment, which is a virtual reproduction of the production equipment, and perform an operation simulation to estimate the operating status of the production equipment when the measures are applied. Using such a simulator allows the support system 1 to generate measures and verify their effectiveness within itself, thereby enabling the first to second steps to be performed without affecting the operation of the actual machines. Furthermore, unlike with real machines, simulations facilitate trial and error of measures, making it possible to compare and refine (optimize) measures. Furthermore, depending on the content of a measure, it may take time to verify its effectiveness after applying it to the actual machine. However, simulations can shorten the time required to verify its effectiveness. For example, a so-called digital twin, which reproduces the production equipment (or the entire production site PL) using a 3D model, is preferably used as the simulator. Advanced simulations using digital twins are expected to enable accurate prediction of changes in not only financial indicators but also non-financial indicators.

[0031] However, there are cases where the goal cannot be achieved even after the first and second steps. In the example above, this applies when there is no room for further reduction in operating hours and the improvement of financial indicators has plateaued, or when the surplus created alone is not enough to achieve non-financial goals. In such cases, achieving the goal through measures such as production equipment control alone is difficult. Instead, measures addressing aspects or resources other than production equipment control may be necessary, such as line reconfiguration or expansion, the introduction of new equipment (hardware and software), the addition or reduction of workers, or a review of raw materials and energy. Therefore, if the goal is not achieved even after the first and second steps, the support system 1 generates and provides an alternative solution (a third measure) different from the second measure in the third step. Alternative solutions may include measures that require human implementation, decision-making (approval) from management or executives, or measures that require time and cost for implementation, making them unsuitable for automatic application to the production floor P&L. Therefore, in the third step, multiple candidate measures may be generated as alternative solutions (third measures), and these may be presented to a user (for example, management or administrative personnel) to select the measure to adopt.

[0032] First Embodiment A first embodiment of the present invention will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the functional configuration of a support system according to the first embodiment.

[0033] The support system 1 of the first embodiment has, as its main functions, a database (DB) 10, a first measure generation unit 11, a second measure generation unit 12, a third measure generation unit 13, a financial target acquisition unit 14, a non-financial target acquisition unit 15, a measure output unit 16, an operation status acquisition unit 17, a non-financial indicator acquisition unit 18, and a non-financial indicator evaluation unit 19. The support system 1 is connected to a management system MS (ERP, MES, etc.) and a production site PL (production equipment, management equipment, etc.) via a network, and data is shared between them. The production equipment includes, for example, manufacturing equipment, conveyance equipment, inspection equipment, PLC, robots, sensors, etc.

[0034] The financial target acquisition unit 14 is a function that acquires financial targets to be achieved in the production site PL. The non-financial target acquisition unit 15 is a function that acquires non-financial targets to be achieved in the production site PL. Note that while FIG. 2 shows an example in which financial targets and non-financial targets are provided from the management system MS, each target may be provided from a separate system, or may be directly input by a person to the support system 1.

[0035] The operation status acquisition unit 17 acquires information representing the operation status from the production equipment operating at the production site PL. This is a function to acquire operational status data (operational status data). Since operational status data is used to generate measures and understand changes in financial indicators, the type of operational status data to be acquired varies depending on the types of financial and non-financial targets that have been set. In other words, any type of information may be collected as operational status data as long as it can be used to support the achievement of financial and non-financial targets. For example, log data from various devices, programs executed by various devices and their parameters, and sensor detection results are examples of operational status data. The operational status data acquired by the operational status acquisition unit 17 is stored in the DB 10 together with information on the time of acquisition.

[0036] The first policy generation unit 11 is a function that executes the first step shown in FIG. 1 and generates a first policy based on current operation status data (i.e., before the first policy is applied) and financial targets. The first policy is a solution focused on achieving the financial target, i.e., a policy for bringing the values ​​of financial indicators in the production site PL closer to the financial targets. The policy generation algorithm by the first policy generation unit 11 may be designed in any way. For example, a rule-based table or function may be used, or a trained model created by machine learning may be used. FIGS. 3A and 3B schematically show an example configuration using a trained model. The trained model 30 in FIG. 3A is trained by machine learning so that, when operation status data and financial targets are given as input, it outputs a policy for bringing the values ​​of financial indicators closer to the financial targets. In this configuration, the trained model 30 infers the current values ​​of the financial indicators from the operation status data. The trained model 30 in FIG. 3B is configured to explicitly give the current values ​​of the financial indicators as input.

[0037] The second policy generation unit 12 is a function that executes the second step shown in FIG. 1 and generates a second policy based on the operation status data collected after applying the first policy to the production site PL and the non-financial goals. The second policy is a solution focused on achieving the non-financial goals, i.e., a policy for bringing the values ​​of non-financial indicators in the production site PL closer to the non-financial goals. The policy generation algorithm by the second policy generation unit 12 may be designed in any way. For example, it may use tables and functions created based on rules, or it may use a trained model created by machine learning. For example, it may use a configuration similar to that shown in FIGS. 3A and 3B (but with "financial" replaced with "non-financial").

[0038] The third measure generation unit 13 is a function that executes the third step shown in FIG. 1. If the non-financial target is not achieved even when the second measure is applied to the production site PL, the third measure generation unit 13 generates a third measure different from the second measure. The third measure is also a solution focused on achieving the non-financial target, i.e., a measure for bringing the values ​​of non-financial indicators in the production site PL closer to the non-financial target. The third measure generation unit 13 may present multiple candidate measures to the user as the third measure and allow the user to select the measure to adopt. Note that the algorithm for generating the measure by the third measure generation unit 13 may be designed in any way. For example, a rule-based table or function may be used, or a trained model 31 created by machine learning as shown in FIG. 3C may be used. The trained model 31 is designed to output multiple candidate measures. Furthermore, the support system 1 may include a learning unit 32 that performs machine learning based on information about the selected measure and the effect of applying the measure (changes in non-financial indicators) after the user selects a measure from multiple candidate measures and applies it to the production site PL. By utilizing the learning results of the learning unit 32 for online learning and fine tuning of the trained model 31, it is expected that the accuracy (validity, reliability) of the candidate policy proposed as the third policy can be improved. Note that a similar learning unit may also be used for online learning and fine tuning of the trained model 30 for the first policy and the second policy.

[0039] The measure output unit 16 has a function of outputting the measures generated by each of the generation units 11 to 13 to the production site PL. The measure output unit 16 may appropriately change the output mode (output method) depending on the type of measure. For example, if the measure is a control parameter for changing the control of the production equipment, the measure output unit 16 may update the control parameter of the production equipment at the production site PL. If the measure requires a human response, the measure output unit 16 may display the content of the measure on a manager terminal or the like at the production site PL.

[0040] The non-financial indicator acquisition unit 18 has a function of acquiring information on non-financial indicators from the production site PL. The acquired information is used to understand changes in non-financial indicators, so the type of non-financial indicators to be acquired varies depending on the type of non-financial goals that have been set. In other words, any type of information may be collected as long as it can be used to support the achievement of non-financial goals. For example, log data from various devices, detection results from sensors, energy consumption records, results of worker surveys, and results of worker biometric monitoring correspond to information on non-financial indicators. The non-financial indicator information acquired by the non-financial indicator acquisition unit 18 is stored in DB 10 together with information on the time of acquisition.

[0041] The non-financial indicator evaluation unit 19 is a function that evaluates whether or not the non-financial target has been achieved based on the change in the non-financial indicator before and after applying the second measure to the production site PL. The evaluation result of the non-financial indicator evaluation unit 19 is used by the third measure generation unit 13 and the like.

[0042] The assistance system 1 may be configured using a general-purpose computer including at least a CPU (processor), memory, storage, and a communication device. In this case, functions 10 to 19 shown in FIG. 2 are realized by loading a computer program stored in the storage into the memory and executing the program using the CPU. However, all or part of the functions shown in FIG. 2 may be replaced by circuits such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). Furthermore, by utilizing cloud computing or distributed computing, all or part of the functions shown in FIG. 2 may be executed by another computer (or in cooperation with another computer). In other words, the logical configuration of the assistance system 1 shown in FIG. 2 may be realized by a combination of hardware and software, or by hardware alone. Furthermore, it may be configured by a single piece of hardware (computer) or a combination of multiple pieces of hardware (computers).

[0043] An example of a support method by the support system 1 will be described with reference to Fig. 4. Fig. 4 is a flowchart of support processing executed by the support system according to the first embodiment.

[0044] First, the financial target acquisition unit 14 acquires financial targets from the management system MS (step S100), and the non-financial target acquisition unit 15 acquires non-financial targets from the management system MS (step S101). The acquired financial targets and non-financial targets are stored in a storage device.

[0045] The operation status acquisition unit 17 acquires current operation status data from the production equipment of the production site PL and stores it in the DB 10 (step S102). Note that the processing of step S102 continues until data necessary for generating the first measure to be executed in the subsequent stage is accumulated.

[0046] The first measure generation unit 11 generates a first measure for bringing the value of the financial indicator closer to the financial target based on the financial target acquired in step S100 and the operation status data acquired in step S102 (step S103). Then, the measure output unit 16 changes the control parameters of the production equipment of the production site PL based on the first measure generated in step S103 (step S104).

[0047] Since the application of the first measure causes changes in the operating status (for example, operating time, throughput, production volume, etc.) of the production equipment, the operating status acquisition unit 17 acquires the operating status data after the changes. The process of step S105 continues until data necessary for generating the second measure to be executed in the subsequent stage is accumulated.

[0048] The second measure generation unit 12 generates a second measure for bringing the value of the non-financial indicator closer to the non-financial target based on the non-financial target acquired in step S101 and the operation status data acquired in step S105 (step S106). Then, the measure output unit 16 changes the control parameters of the production equipment of the production site PL based on the second measure generated in step S106 (step S107). The change in control of the production equipment by applying the second measure acts in the direction of improving the non-financial indicator.

[0049] The non-financial indicator acquisition unit 18 then acquires information on non-financial indicators from the production site PL and stores the information in the DB 10 (step S108). The time interval between applying the second measure (step S107) and acquiring the non-financial indicators (S108) may be designed depending on the type of second measure and the type of non-financial indicator. For example, if the non-financial indicator is energy consumption and the second measure is optimizing the shutdown control of production equipment, the change in energy consumption can be measured several hours after the second measure is applied. Therefore, the time interval may be set to several hours to several days. In contrast, if the non-financial indicator is something like job satisfaction or work engagement, it may take several days to several weeks for the effects of applying the second measure to appear in the non-financial indicators, and acquiring the non-financial indicators also takes time because it involves measures such as worker surveys. Therefore, in such cases, the time interval may be set to several weeks to several months.

[0050] Once the non-financial indicators are acquired, the non-financial indicator evaluation unit 19 calculates the change in the non-financial indicators before and after applying the second measure, and determines whether the non-financial target acquired in step S101 has been achieved (step S109). If the non-financial target has been achieved (YES in step S109), the support process ends. Note that in this embodiment, it is assumed that the financial target has been achieved by applying the first measure, and no confirmation is made as to whether the financial target has been achieved or not.

[0051] If the non-financial target is not achieved despite the application of the second measure (NO in step S109), the third measure generation unit 13 generates a third measure that is different from the second measure (step S110). At this time, the third measure generation unit 13 generates multiple candidate measures (step S110), presents the multiple candidate measures to the user, and allows the user to select a measure to adopt (step S111).

[0052] According to the support process described above, the first and second measures are generated to achieve given financial and non-financial targets, and these measures are applied to the production equipment of the production site PL. Therefore, the production site PL can be optimized automatically and autonomously without substantially requiring the user's effort or judgment.

[0053] (Case 1) Figure 5 shows Example 1 of optimization using the support system 1. In Example 1, it is assumed that the financial target is "20% improvement in productivity" and the non-financial target is "50% reduction in energy consumption."

[0054] In the first step, the first measure, "increase the line speed by 20%," is determined as a measure to improve productivity by 20%, and the control parameters of the production equipment are changed accordingly. Assume that by applying this first measure, productivity improves by 20%, and as a result, 40% of the production equipment's surplus is created. In other words, it can be seen that by increasing the line speed, 40% of the production equipment's non-operating time has been created compared to before the application of the first measure.

[0055] In the second step, the surplus created in the first step is used to determine the second measure to reduce energy consumption, which is a non-financial target. In this example, the control parameters are changed so that the production equipment is switched to an idling state (a state with low energy consumption) during the surplus period (i.e., when the production equipment is not in operation), and as a result, a 40% reduction in energy consumption is achieved.

[0056] By implementing the first and second steps, the financial goal of "increasing productivity by 20%" was achieved, but the non-financial goal of "reducing energy consumption by 50%" was not achieved (another 10% reduction is required). Therefore, Support System 1 additionally implements the third step. In the third step, a third measure to reduce energy consumption by 10% is created and presented to the user (management and management). In this example, three candidate measures are recommended to the user: "increasing line speed by 10%, "purchasing renewable energy", and "reducing production volume".

[0057] (Case 2) Figure 6 shows Example 2 of optimization using the support system 1. In Example 2, the financial goal is assumed to be "a 20% increase in productivity" and the non-financial goal is assumed to be "a 20% increase in job satisfaction."

[0058] In the first step, the first measure, "improving the efficiency of the assembly process," is decided as a measure to improve productivity by 20%, and the control parameters of the production equipment (for example, increasing the speed of workpiece transport and robot operation speed) are changed accordingly. By analyzing the operational status data after applying the first measure, it was possible to confirm a 20% improvement in productivity, while also understanding the impact that the efficiency of the assembly process has on worker behavior (work procedures, flow lines, waiting time, etc.).

[0059] In the second step, the results of an analysis of worker behavior using operational status data after the first measure is applied are used to determine the second measure to improve job satisfaction, a non-financial goal. In this case, work support through DX (for example, visual work support using AR (augmented reality) technology, and fleet management that optimizes the routes and placement of autonomous transport robots) was implemented, resulting in a 10% improvement in job satisfaction. Job satisfaction can be evaluated through motivation analysis that utilizes worker surveys and behavioral analysis.

[0060] By implementing the first and second steps, the financial goal of "increasing productivity by 20%" was achieved, but the non-financial goal of "increasing job satisfaction by 20%" was not achieved (another 10% improvement is needed). Therefore, Support System 1 additionally implements the third step. In the third step, a third measure to increase job satisfaction by another 10% is created and presented to the user (management and management). In this example, three candidate measures are recommended to the user: "introducing robots," "increasing wages," and "reducing production volume."

[0061] Second Embodiment A second embodiment of the present invention will be described with reference to Figures 7 and 8. In the first embodiment, the financial target is considered to have been achieved by applying the first measure, and no confirmation is made as to whether the financial target was achieved or not. However, in the second embodiment, financial indicators are evaluated after applying the first measure, and if the financial target has not been achieved, the first measure is modified. The following description will focus on the differences from the first embodiment.

[0062] FIG. 7 is a block diagram showing the functional configuration of the support system according to the second embodiment. The support system 1 of this embodiment includes a financial index evaluation unit 20. The financial index evaluation unit 20 evaluates the operating status of the financial institution. This function obtains the change in financial indicators before and after applying the first measure to the production site P&L based on the situation data, and evaluates whether the financial target has been achieved based on the change in financial indicators.

[0063] Fig. 8 shows a flowchart of the support process in the second embodiment. Fig. 8 shows the process in the first step, which replaces the processes in steps S103 to S105 in the flowchart (Fig. 4) of the first embodiment.

[0064] After the processing up to step S102 is performed in the same manner as in the first embodiment, the first measure generation unit 11 generates a first measure for bringing the value of the financial indicator closer to the financial target based on the financial target acquired in step S100 and the operation status data acquired in step S102 (step S103). Then, the measure output unit 16 changes the control parameters of the production equipment of the production site PL based on the first measure generated in step S103 (step S104).

[0065] Since the application of the first measure causes changes in the operating status of the production equipment (for example, operating time, throughput, production volume, etc.), the operating status acquisition unit 17 acquires operating status data after the changes (step S105). The processing of step S105 continues until data necessary for generating the second measure to be executed in a subsequent stage is accumulated.

[0066] Thereafter, the financial indicator evaluation unit 20 calculates the value of the financial indicator after the first measure is applied based on the operational status data accumulated in the DB 10 (step S200). Then, the financial indicator evaluation unit 20 determines whether the financial target has been achieved based on the change in the financial indicator after the first measure is applied (step S201). If the financial indicator evaluation unit 20 determines that the financial target has not been achieved (NO in step S201), the first measure generation unit 11 modifies the first measure (step S202). In the above-mentioned Case 1, an example was described in which "increasing the line speed by 20%" was applied as the first measure. However, if applying this measure does not achieve a 20% improvement in productivity, an easy-to-understand example would be to modify the first measure to, for example, "increasing the line speed by 30%." Using the modified first measure, the processes of steps S104, S105, S200, and S201 are re-executed.

[0067] If the financial target is achieved as a result of repeated correction and application of the first measure, or if a predetermined termination condition is met (for example, the number of repetitions reaches an upper limit, or the change in the financial indicator due to the correction of the first measure is less than or equal to a threshold value) (YES in step S201), the loop processing is terminated and the process proceeds to step S106. The subsequent processing may be the same as in the first embodiment. According to the second embodiment described above, it is possible to drive the control of the production site toward achieving the financial target. can be done.

[0068] Third Embodiment A third embodiment of the present invention will be described with reference to Figure 9. In the first and second embodiments, the second measure is generated and applied only once, but in the third embodiment, non-financial indicators are evaluated after the second measure is applied, and if the non-financial target has not been achieved, the second measure is revised. The following description will focus on the differences from the first and second embodiments.

[0069] Fig. 9 shows a flowchart of the support process in the third embodiment. Fig. 9 shows the process in the second step, which replaces the processes in steps S106 to S108 in the flowchart (Fig. 4) of the first embodiment.

[0070] After the first measure is applied in the same manner as in the first or second embodiment, the second measure generation unit 12 generates a second measure for bringing the value of the non-financial indicator closer to the non-financial target based on the non-financial target acquired in step S101 and the operation status data acquired in step S105 (step S106). Then, the measure output unit 16 changes the control parameters of the production equipment of the production site PL based on the second measure generated in step S106 (step S107). The change in control of the production equipment by applying the second measure acts in the direction of improving the non-financial indicators. Thereafter, the non-financial indicator acquisition unit 18 acquires information on the non-financial indicators from the production site PL (step S108).

[0071] The non-financial indicator evaluation unit 19 then determines whether the non-financial target has been achieved based on the change in the non-financial indicator after the second measure has been applied (step S300). If the non-financial indicator evaluation unit 19 determines that the non-financial target has not been achieved (NO in step S300), the second measure generation unit 12 modifies the second measure (step S301). In the above-mentioned case 1, an example was described in which idling control was applied as the second measure. However, if applying this measure does not achieve a 50% reduction in energy consumption, a modification such as optimizing operating time and idle time may be considered. Using the modified second measure, the processing of steps S107, S108, and S300 is re-executed.

[0072] If the non-financial target is achieved as a result of repeated correction and application of the second measure, or if a predetermined termination condition is met (for example, the number of repetitions reaches an upper limit, or the change in the non-financial indicator due to the correction of the second measure is less than or equal to a threshold value) (YES in step S300), the process exits the loop and proceeds to step S109. The subsequent processing may be the same as in the first embodiment. According to the third embodiment described above, it is possible to drive the control of the production site toward achieving the non-financial target.

[0073] <Fourth embodiment> Before (or instead of) applying the generated first and second measures to actual production equipment (real machines) operating at the production site PL, the support system 1 may apply the measures to virtual production equipment, which is a virtual reproduction of the production equipment, and perform an operation simulation to estimate the operating status of the production equipment when the measures are applied. Using such a simulator allows the support system 1 to generate measures and verify their effectiveness within itself, thereby enabling the first to second steps to be performed without affecting the operation of the actual machines. Furthermore, unlike with real machines, simulations facilitate trial and error of measures, making it possible to compare and refine (optimize) measures. Furthermore, depending on the content of a measure, it may take time to verify its effectiveness after applying it to the actual machine. However, simulations can shorten the time required to verify its effectiveness. For example, a so-called digital twin, which reproduces the production equipment (or the entire production site PL) using a 3D model, is preferably used as the simulator. Advanced simulations using digital twins are expected to enable accurate prediction of changes in not only financial indicators but also non-financial indicators.

[0074] 10 is a block diagram showing the functional configuration of a support system according to the fourth embodiment. The support system 1 of this embodiment includes a simulator 40 that performs an operation simulation using virtual production equipment that is a reproduction of production equipment at a production site PL in a virtual space.

[0075] The simulator 40 may, for example, apply the first measure to the virtual production equipment in step S104 of Fig. 4 and execute an operation simulation to estimate the operation status of the production equipment when the first measure is applied, and store the estimated results in DB10, use them as operation status data after the first measure is applied in steps S105 and S106, or use them to estimate changes in financial indicators after the first measure is applied in step S200 of Fig. 8. Similarly, the simulator 40 may, for example, apply the second measure to the virtual production equipment in step S107 of Fig. 4 and execute an operation simulation to estimate the operation status of the production equipment when the second measure is applied, and store the estimated results in DB10, or use them as operation status data after the first measure is applied in steps S106 and S108. 8 may be used to estimate the change in non-financial indicators after the application of the second measure.

[0076] <Other> The above-described embodiments merely exemplify exemplary configurations of the present invention. The present invention is not limited to the specific embodiments described above, and various modifications are possible within the scope of the technical concept. The configurations of the first to fourth embodiments may be combined with each other as long as no technical contradiction occurs. For example, the simulator 40 of the fourth embodiment may be combined with the first to third embodiments. In this case, the simulator 40 may also function as the financial indicator evaluation unit 20, or as the non-financial indicator acquisition unit 18 and the non-financial indicator evaluation unit 19.

[0077] The present disclosure includes the following configurations, methods, and programs.

[0078] [Appendix 1] A support system (1) for supporting goal achievement in a production site (PL), a financial target acquisition unit (14) that acquires financial targets that are targets for financial indicators to be achieved at the production site (PL); a non-financial target acquisition unit (15) that acquires non-financial targets, which are targets for non-financial indicators to be achieved at the production site (PL); a first measure generation unit (11) that generates a first measure for bringing the value of a financial indicator at the production site (PL) closer to the financial target based on information representing the operating status of production equipment operating at the production site (PL) and the financial target; a second measure generation unit (12) that generates a second measure for bringing the value of a non-financial indicator at the production site (PL) closer to the non-financial target based on information representing the operating status of the production equipment when the first measure generated by the first measure generation unit (11) is applied and the non-financial target; A support system (1).

[0079] [Appendix 2] The system further includes a financial indicator evaluation unit (20) that acquires a change in a financial indicator when the first measure is applied to the production site (PL) and evaluates whether or not the financial target has been achieved based on the change in the financial indicator; When the financial indicator evaluation unit (20) evaluates that the financial target has not been achieved, the first measure generation unit (11) corrects the first measure. The assistance system (1) according to appendix 1.

[0080] [Appendix 3] The system further includes a non-financial indicator evaluation unit (19) that acquires a change in a non-financial indicator when the second measure is applied to the production site (PL) and evaluates whether or not the non-financial target has been achieved based on the change in the non-financial indicator; When the non-financial indicator evaluation unit (19) evaluates that the non-financial target has not been achieved, the second measure generation unit (12) corrects the second measure. The assistance system (1) according to appendix 1 or 2.

[0081] [Appendix 4] a non-financial indicator evaluation unit (19) that acquires a change in a non-financial indicator when the second measure is applied to the production site (PL) and evaluates whether the non-financial target has been achieved based on the change in the non-financial indicator; a third measure generation unit (13) that generates a third measure different from the second measure as a measure for bringing the value of the non-financial indicator at the production site (PL) closer to the non-financial target when the non-financial indicator evaluation unit (19) evaluates that the non-financial target has not been achieved; The assistance system (1) according to any one of appendices 1 to 3, further comprising:

[0082] [Appendix 5] the third measure generation unit (13) generates a plurality of measure candidates as the third measure and presents the generated plurality of measure candidates to a user; The assistance system (1) described in Appendix 4.

[0083] [Appendix 6] The system further includes a learning unit (32) that performs machine learning on information about a measure selected by a user from the plurality of measure candidates and a change value of the non-financial indicator when the selected measure is applied to the production site. The assistance system (1) described in Appendix 5.

[0084] [Appendix 7] the first strategy includes a control parameter for changing control of the production equipment; An assistance system (1) according to any one of appendices 1 to 6.

[0085] [Appendix 8] The support system (1) described in any one of Appendices 1 to 7, wherein the first measure generation unit (11) is configured by a trained model (30) that has been machine-learned to output measures for bringing the value of a financial indicator at the production site (PL) closer to the financial target based on information representing the operating status of the production equipment and the financial target.

[0086] [Appendix 9] The second measure generation unit (12) is configured by a trained model (30) that has been machine-learned to output measures for bringing the values ​​of non-financial indicators at the production site (PL) closer to the non-financial targets based on information representing the operating status of the production equipment and the non-financial targets. An assistance system (1) according to any one of appendices 1 to 8.

[0087] [Appendix 10] The production facility further includes a simulator (40) for performing an operation simulation using a virtual production facility that is a reproduction of the production facility in a virtual space, the simulator (40) applies the first measure generated by the first measure generation unit (11) to the virtual production equipment and executes an operation simulation to estimate an operation status of the production equipment when the first measure is applied; the second measure generation unit (12) generates the second measure by using the estimation result by the simulator (40) as information representing the operating status of the production equipment when the first measure is applied. An assistance system (1) according to any one of appendices 1 to 9.

[0088] [Appendix 11] The production facility further includes a simulator (40) for performing an operation simulation using a virtual production facility that is a reproduction of the production facility in a virtual space, the simulator (40) applies the first measure generated by the first measure generation unit (11) to the virtual production equipment and executes an operation simulation to estimate an operation status of the production equipment when the first measure is applied; the financial index evaluation unit (20) estimates a change in a financial index when the first measure is applied to the production equipment based on the estimation result by the simulator (40); The assistance system (1) described in Appendix 2.

[0089] [Appendix 12] The production facility further includes a simulator (40) for performing an operation simulation using a virtual production facility that is a reproduction of the production facility in a virtual space, the simulator (40) applies the second measure generated by the second measure generation unit (12) to the virtual production equipment and executes an operation simulation to estimate an operation status of the production equipment when the second measure is applied; the non-financial indicator evaluation unit (19) estimates a change in a non-financial indicator when the second measure is applied to the production equipment based on the estimation result by the simulator (40); Assistance system (1) according to appendix 3 or 4.

[0090] [Appendix 13] A support method for supporting goal achievement in a production site (PL) by a computer, comprising: A step in which a computer acquires financial targets, which are targets for financial indicators to be achieved at the production site (PL); A step in which a computer acquires non-financial targets, which are targets for non-financial indicators to be achieved at the production site (PL); A step in which a computer generates a first measure for bringing the value of a financial indicator at the production site (PL) closer to the financial target based on information representing the operating status of production equipment operating at the production site (PL) and the financial target; A step in which a computer generates a second measure for bringing the value of a non-financial indicator at the production site (PL) closer to the non-financial target based on information representing the operating status of the production equipment when the first measure is applied and the non-financial target; Support methods including:

[0091] [Appendix 14] A program for causing a computer to execute each step of the method described in Appendix 13. [Explanation of symbols]

[0092] 1: Support system MS: Management Systems PL: Production site

Claims

1. A support system for supporting goal achievement at a production site, a financial target acquisition unit that acquires financial targets that are targets for financial indicators to be achieved at the production site; a non-financial target acquisition unit that acquires non-financial targets that are targets for non-financial indicators to be achieved at the production site; a first measure generation unit that generates a first measure for bringing the value of a financial indicator at the production site closer to the financial target based on information representing the operating status of production equipment operating at the production site and the financial target; a second measure generation unit that generates a second measure for bringing the value of a non-financial indicator at the production site closer to the non-financial target, based on information representing the operating status of the production equipment when the first measure generated by the first measure generation unit is applied and the non-financial target; A support system having:

2. a financial indicator evaluation unit that acquires a change in a financial indicator when the first measure is applied to the production site and evaluates whether the financial target has been achieved based on the change in the financial indicator; When the financial indicator evaluation unit evaluates that the financial target has not been achieved, the first measure generation unit modifies the first measure. The assistance system according to claim 1 .

3. a non-financial indicator evaluation unit that acquires a change in a non-financial indicator when the second measure is applied to the production site and evaluates whether the non-financial target has been achieved based on the change in the non-financial indicator; When the non-financial indicator evaluation unit evaluates that the non-financial target has not been achieved, the second measure generation unit modifies the second measure. The assistance system according to claim 1 .

4. a non-financial indicator evaluation unit that acquires a change in a non-financial indicator when the second measure is applied to the production site and evaluates whether the non-financial target has been achieved based on the change in the non-financial indicator; a third measure generation unit that generates a third measure different from the second measure as a measure for bringing the value of the non-financial indicator at the production site closer to the non-financial target when the non-financial indicator evaluation unit evaluates that the non-financial target has not been achieved; The assistance system according to claim 1 , further comprising:

5. the third measure generation unit generates a plurality of measure candidates as the third measure and presents the generated plurality of measure candidates to a user; The assistance system according to claim 4.

6. a learning unit that performs machine learning on information about a measure selected by a user from the plurality of measure candidates and a change in the non-financial indicator when the selected measure is applied to the production site; The assistance system according to claim 5.

7. the first measure includes a control parameter for changing control of the production equipment; The support system according to any one of claims 1 to 6.

8. The first measure generation unit generates a production plan based on information representing the operation status of the production equipment and the financial target. The system is configured by a trained model that has been machine-learned to output measures for bringing the values ​​of financial indicators at the production site closer to the financial targets. The assistance system according to claim 1 .

9. The second measure generation unit is configured by a trained model that is machine-learned to output measures for bringing the values ​​of non-financial indicators at the production site closer to the non-financial targets based on information representing the operation status of the production equipment and the non-financial targets. The assistance system according to claim 1 .

10. The production system further includes a simulator that performs an operation simulation using virtual production equipment that is a reproduction of the production equipment in a virtual space, the simulator applies the first measure generated by the first measure generation unit to the virtual production equipment and executes an operation simulation, thereby estimating an operation status of the production equipment when the first measure is applied; the second measure generation unit generates the second measure by using the estimation result by the simulator as information representing the operating status of the production equipment when the first measure is applied. The assistance system according to claim 1 .

11. The production system further includes a simulator that performs an operation simulation using virtual production equipment that is a reproduction of the production equipment in a virtual space, the simulator applies the first measure generated by the first measure generation unit to the virtual production equipment and executes an operation simulation, thereby estimating an operation status of the production equipment when the first measure is applied; the financial index evaluation unit estimates a change in a financial index when the first measure is applied to the production equipment based on an estimation result by the simulator. The assistance system according to claim 2 .

12. The production system further includes a simulator that performs an operation simulation using virtual production equipment that is a reproduction of the production equipment in a virtual space, the simulator applies the second measure generated by the second measure generation unit to the virtual production equipment and executes an operation simulation, thereby estimating an operation status of the production equipment when the second measure is applied; the non-financial indicator evaluation unit estimates a change in a non-financial indicator when the second measure is applied to the production equipment based on an estimation result by the simulator; The assistance system according to claim 3 or 4.

13. A support method for supporting goal achievement at a production site by a computer, comprising: A step in which a computer acquires a financial target, which is a target of a financial indicator to be achieved at the production site; A step in which a computer acquires non-financial targets, which are targets for non-financial indicators to be achieved at the production site; A step in which a computer generates a first measure for bringing the value of a financial indicator at the production site closer to the financial target based on information representing the operating status of production equipment operating at the production site and the financial target; a step in which a computer generates a second measure for bringing the value of a non-financial indicator at the production site closer to the non-financial target based on information representing the operating status of the production equipment when the first measure is applied and the non-financial target; Support methods including:

14. A program for causing a computer to execute each step of the method according to claim 13.

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