Method and device for setting the resources used.

Abstract

To set resources to be used while simultaneously taking into account the update accuracy of working time and predicted values including variations in production KPIs.SOLUTION: A resource use setting method is executed by a resource use setting device: the resource use setting device includes a control unit and a storage unit where the storage unit holds resource type information, working time information, and production planning information: the resource use setting method includes a first procedure in which the control unit predicts a calculation accuracy of a required time for a work in a resource use plan that allocates one or more resources to the work in each process of producing a product based on the resource type information, working time information, and production planning information, and a second procedure in which the control unit predicts an evaluation index of product production at the time when the resource use plan is adopted based on the resource use plan, working time information, and production planning information: the second procedure includes a procedure in which the control unit predicts variations in the evaluation indices based on the calculation accuracy of the required time for the work in the resource use plan.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a technology for setting used resources in a production process, which achieves both update accuracy and production efficiency when automatically updating working hours by utilizing production results.

Background Art

[0002] In the modeling of working hours using production results, when the number of candidates for available manufacturing resources is large, the number of results per resource decreases, and the accuracy of working hours decreases. As a result, various indicators related to production efficiency (production KPIs) deteriorate compared to the planning stage. On the other hand, when the number of resources is small, a good plan for production KPIs cannot be made. Japanese Patent Application Laid-Open No. 2010-238085 (Patent Document 1) describes "a production information management system that connects a data collection system and a screen display system via a network and manages information that serves as evaluation indicators for productivity and reliability in a production system, such as key performance indicators (KPIs)".

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modeling work time using production data, an effective method is to pre-set the resources used during the design phase of a new product, and then automatically update work time by collecting and analyzing work data for each resource available in each process after mass production begins. When setting resources, the more resources set, the lower the accuracy of work time updates, but the higher the planned KPIs. Conversely, the fewer resources set, the higher the accuracy of work time updates, but the lower the planned KPIs. Furthermore, the lower the accuracy of work time updates, the higher the likelihood that production KPIs will deviate from and decrease from planned KPIs. Therefore, a challenge when designing a new product is to set resources that simultaneously consider both the accuracy of work time updates and predicted values ​​including variability in production KPIs. [Means for solving the problem]

[0005] To solve at least one of the above problems, the present invention provides a resource usage setting method performed by a resource usage setting device, wherein the resource usage setting device comprises a control unit and a storage unit, the storage unit holds resource type information, work time information and production plan information, the resource type information includes information that identifies each type of resource that can be used for work in a process for producing a product, the work time information includes information that indicates the time required for work previously performed using each resource, and the production plan information includes information that indicates the number of products for which production is planned, and the resource usage setting method The method includes: a first step in which the control unit predicts the accuracy of calculating the required time for work in a proposed resource usage plan that allocates one or more of the resources to work in each process of producing the product, based on the resource type information, the work time information, and the production plan information; and a second step in which the control unit predicts an evaluation index for the production of the product if the proposed resource usage plan is adopted, based on the proposed resource usage plan, the work time information, and the production plan information, wherein the second step includes a step in which the control unit predicts the variability of the evaluation index based on the accuracy of calculating the required time for work in the proposed resource usage plan. The storage unit further stores resource usage information, the resource usage information includes information that identifies one or more resources that can be used for the work of each process for producing the product, the resource usage setting method further includes a third step in which the control unit generates a plurality of resource usage proposals based on the resource usage information, and the first and second steps are performed for each of the plurality of resource usage proposals generated in the third step. It is characterized by the following: [Effects of the Invention]

[0006] According to one aspect of the present invention, when designing a new product, it becomes possible to set the resources to be used while simultaneously considering the accuracy of updating work time and predicted values ​​including variability in production KPIs. Other issues, configurations, and effects not mentioned above will be clarified by the following description of the embodiments. [Brief explanation of the drawing]

[0007] [Figure 1] This is a block diagram showing an example of the system configuration of Example 1. [Figure 2] This block diagram shows an example of a hardware configuration for realizing the system of Example 1. [Figure 3] This block diagram shows an example of an actual usage scenario for an information terminal that implements the system of Example 1. [Figure 4] This is an explanatory diagram showing an example of a new product's resource usage information storage unit, which is stored in the information storage unit of the resource usage setting device of Example 1. [Figure 5] This is an explanatory diagram showing an example of a resource type information storage unit held in the information storage unit of the resource setting device used in Embodiment 1. [Figure 6] This is an explanatory diagram showing an example of a storage unit for past product work performance information held in the information storage unit of the resource setting device used in Example 1. [Figure 7] This is an explanatory diagram showing an example of a past product work time information storage unit held in the information storage unit of the resource setting device used in Example 1. [Figure 8] This is an explanatory diagram showing an example of a new product sales plan information storage unit held in the information storage unit of the resource setting device used in Example 1. [Figure 9] This flowchart shows an example of the processing performed by the control unit of the resource setting device in Example 1. [Figure 10A] This flowchart shows an example of the process performed by the work time update accuracy prediction function of the resource setting device used in Example 1. [Figure 10B]It is a flowchart showing an example of the process executed by the KPI prediction function of the resource usage setting device according to the first embodiment. [Figure 11] It is an explanatory diagram showing an example of a resource usage plan display screen displayed by the result display unit of the resource usage setting device according to the first embodiment. [Figure 12] It is a block diagram showing the system configuration of the resource usage setting device according to the second embodiment. [Figure 13] It is a flowchart showing an example of the process executed by the resource usage plan search function of the resource usage setting device according to the second embodiment. [Figure 14] It is an explanatory diagram showing an example of a selection screen of evaluation indexes displayed by the result display unit of the resource usage setting device according to the first embodiment. [Figure 15] It is an explanatory diagram showing an example of a resource usage plan search result display screen displayed by the result display unit of the resource usage setting device according to the second embodiment.

Mode for Carrying Out the Invention

[0008] Hereinafter, embodiments will be described with reference to the drawings.

Embodiment

[0009] <00000,83>In the first embodiment, taking the case where the work time update accuracy for the resource usage plan and the probability prediction value of the KPI are visualized and the result is confirmed by a person to select an appropriate resource usage as an example.

[0010] FIG. 1 is a block diagram showing an example of the system configuration according to the first embodiment.

[0011] The resource usage setting device 101 according to the first embodiment includes an information storage unit 102, a control unit 103, and a result display unit 104.

[0012] The information storage unit 102 includes a resource usage information storage unit 400 for new products and a resource type information storage unit 500.

[0013] In addition, the information storage unit 102 includes a work performance information storage unit 600 for past products, a work time information storage unit 700 for past products, and a sales plan information storage unit 800 for new products. The work performance information storage unit 600 for past products reads and stores the work performance information 106 of past products included in the production management device 105. The work time information storage unit 700 for past products reads and stores the work time information 107 of past products included in the production management device 105. The sales plan information storage unit 800 for new products reads and stores the sales plan information 109 of new products included in the sales plan formulation device 108.

[0014] Note that the production management device 105 is a device that manages the production of products in a factory or the like. The sales plan formulation device 108 is a device that formulates a sales plan for the produced products. Since these devices may be those conventionally used, detailed descriptions thereof are omitted.

[0015] The control unit 103 includes a usage resource plan generation function 111, a work time update accuracy prediction function 112, a KPI prediction function 113, and a prediction result visualization function 114. The usage resource plan generation function 111 generates all usage resource plans that can be considered from combinations of facilities and workers available during production implementation. The work time update accuracy prediction function 112 predicts the relationship between the usage resource plan and the work time update accuracy. The KPI prediction function 113 predicts the relationship between the usage resource plan and the probability-added predicted value of the KPI. The prediction result visualization function 114 visualizes the relationship between the resource plan and the work time update accuracy and the relationship between the usage resource plan and the probability-added predicted value of the KPI. The usage resource setting device 101 can perform the setting of usage resources while considering the update accuracy of the work time and the probability-added predicted value of the production KPI by the above functions.

[0016] FIG. 2 is a block diagram showing an example of the hardware configuration for realizing the system of Example 1.

[0017] The resource usage setting device 101 may be implemented by an information terminal 201 as shown in Figure 2. The information terminal 201 has input devices 202 such as a keyboard and mouse, output devices 203 such as a display, auxiliary storage devices 204, and an arithmetic unit 205 that performs various functions. The arithmetic unit 205 includes a central processing unit (hereinafter referred to as CPU) 206, main memory 207, and an interface 208. This arithmetic unit 205 is connected to the input devices 202, output devices 203, and auxiliary storage devices 204 via the interface 208. In this embodiment, the execution results of each function of the resource usage setting device 101 (for example, the resource usage proposal generation function 111 of the control unit 103, the work time update accuracy prediction function 112, the KPI prediction function 113, and the prediction result visualization function 114) are stored in a memory area reserved in the main memory 207. Each of these functions is pre-stored in the auxiliary storage device 204, read into the main memory 207 at the time of execution, and executed by the CPU 206.

[0018] In this embodiment, the case in which the information terminal 201 is implemented by a general-purpose information processing device and software is described as an example, but it may also be implemented by hardware including hardwired logic, or by hardware and a pre-programmed general-purpose information processing device.

[0019] Figure 3 is a block diagram showing an example of the actual usage of the information terminal 201 that realizes the system of Example 1.

[0020] As shown in Figure 3, the information terminal 201 can be operated by the person in charge 301. For example, the person in charge 301 can input information 302 to the information terminal 201 which implements the resource usage setting device 101 at any time. The control unit 103 implemented by the information terminal 201 calculates the relationship between the resource plan and the work time update accuracy, and the relationship between the resource usage plan and the predicted values ​​with probabilities of the KPI, and outputs information 303 that visualizes the calculation results. The person in charge 301 can check the visualized relationship between the resource plan and the work time update accuracy, and the relationship between the resource usage plan and the predicted values ​​with probabilities of the KPI.

[0021] The following sections will describe the details of each component of the resource setting device 101.

[0022] Figure 4 is an explanatory diagram showing an example of a new product resource information storage unit 400 held in the information storage unit 102 of the resource setting device 101 of Embodiment 1.

[0023] The new product resource information storage unit 400 stores information about the processes required to produce the new product and the resources available for use in those processes. For example, in this embodiment, the new product resource information storage unit 400 stores a table as shown in Figure 4.

[0024] The resource usage information storage unit 400 shown in Figure 4 has columns 401 to 404. Column 401 stores resource usage ID information to uniquely identify each record in the resource usage information storage unit 400 for the new product (i.e., each row in the resource usage information storage unit 400 in Figure 4). Column 402 stores the name information of the new product. Column 403 stores the process name information of the process required for the production of the product. Column 404 stores the name information of the resources that can be used for the process required for the production of the product.

[0025] In the example in Figure 4, the first and second records indicate that there are at least two resources (e.g., machine tools that perform cutting) that can be used for the cutting process to produce product A, and that these are identified by the resource names "Cutting 1" and "Cutting 2," respectively.

[0026] The information storage unit 102 in Figure 1 receives input processing 302 regarding resource usage information for the new product from the person in charge 301 in Figure 3, and stores the input information in the resource usage information storage unit 400 for the new product.

[0027] Figure 5 is an explanatory diagram showing an example of a resource type information storage unit 500 held in the information storage unit 102 of the resource setting device 101 used in Embodiment 1.

[0028] The resource type information storage unit 500 stores information for identifying the type of resource for each resource. For example, in this embodiment, the resource type information storage unit 500 stores a table as shown in Figure 5.

[0029] The resource type information storage unit 500 shown in Figure 5 has columns 501 to 503. Column 501 stores resource type ID information to uniquely identify each record in the resource type information storage unit 500. Column 502 stores resource name information. Column 503 stores resource type information corresponding to the resource identified by the name stored in column 502.

[0030] Here, the type of resource is one of the following: "person," "equipment + person," or "automated equipment." A resource of type "person" is, for example, a person such as a factory worker. In other words, the process using that resource is performed manually by the worker (for example, using tools). A resource of type "equipment + person" is, for example, equipment that requires manual operation. In other words, the process using that resource is performed by, for example, a worker operating machinery or other equipment. A resource of type "automated equipment" is equipment that operates automatically without requiring manual operation. In other words, the process using that resource is performed automatically by machinery or other equipment.

[0031] However, the resource types listed above are merely examples, and resources may be classified into other categories. For example, resources may be classified according to the type of equipment, performance, skill level of personnel, etc.

[0032] The example in Figure 5 shows that resources named "Cutting 1" and "Cutting 2" are equipment that requires manual operation (e.g., machine tools that perform cutting processes), while resources named "Painting 1" are automated equipment that does not require manual operation.

[0033] The information storage unit 102 in Figure 1 receives input processing 302 regarding resource type information from the person in charge 301 in Figure 3, and stores the input information in the resource type information storage unit 500.

[0034] Figure 6 is an explanatory diagram showing an example of a past product work performance information storage unit 600 held in the information storage unit 102 of the resource setting device 101 of Embodiment 1.

[0035] The past product work performance information storage unit 600 stores the start time information and end time information for each resource that performed the production work, based on past production performance information for products that are already in mass production. For example, in this embodiment, the past product work performance information storage unit 600 stores a table as shown in Figure 6.

[0036] The past product work performance information storage unit 600 shown in Figure 6 has columns 601 to 604. Column 601 stores work performance ID information to uniquely identify each record in the past product work performance information storage unit 600. Column 602 stores the name information of the resource that performed the work. Column 603 stores the time information when the work started. Column 604 stores the time information when the work ended.

[0037] The information storage unit 102 in Figure 1 reads information corresponding to each of the above items from the work performance information 106 of past products stored in the production management device 105 in Figure 1, and stores it in the work performance information storage unit 600 of past products.

[0038] Figure 7 is an explanatory diagram showing an example of a past product work time information storage unit 700 held in the information storage unit 102 of the resource setting device 101 of Embodiment 1.

[0039] The past product work time information storage unit 700 stores standard work time information set for products that have already been mass-produced, for each resource. For example, in this embodiment, the past product work time information storage unit 700 stores a table as shown in Figure 7.

[0040] The past product work time information storage unit 700 shown in Figure 7 has columns 701 to 703. Column 701 stores work time ID information to uniquely identify each record in the past product work time information storage unit 700. Column 702 stores the name information of the resource that performed the work. Column 703 stores the standard work time information for the work. Here, the standard work time may be, for example, a statistical value of the work time for each resource calculated from the work start time and work end time in the past product work performance information storage unit 600.

[0041] The information storage unit 102 in Figure 1 reads information corresponding to each of the above items from the work time information 107 of past products stored in the production management device 105 in Figure 1, and stores it in the work time information storage unit 700 of past products.

[0042] Figure 8 is an explanatory diagram showing an example of a new product sales plan information storage unit 800 held in the information storage unit 102 of the resource setting device 101 of Embodiment 1.

[0043] The new product sales plan information storage unit 800 stores sales plan information to determine how many units of the new product, which is scheduled for mass production in the future, will be produced. For example, in this embodiment, the new product sales plan information storage unit 800 stores a table as shown in Figure 8.

[0044] The new product sales plan information storage unit 800 shown in Figure 8 has columns 801 to 803. Column 801 stores product ID information for uniquely identifying the new product. Column 802 stores the name information of the product. Column 803 stores planned sales volume information for the product.

[0045] The information storage unit 102 in Figure 1 reads information corresponding to each of the above items from the new product sales plan information 109 stored in the sales plan planning device 108 in Figure 1, and stores it in the new product sales plan information storage unit 800.

[0046] Next, the entire process executed by the control unit 103 in Figure 1 will be explained with reference to Figure 9.

[0047] Figure 9 is a flowchart showing an example of the processing performed by the control unit 103 of the resource setting device in Embodiment 1.

[0048] First, the resource usage plan generation function 111 of the control unit 103 generates a resource usage plan (step S901).

[0049] Next, the work time update accuracy prediction function 112 of the control unit 103 calculates a predicted value for the work time update accuracy (step S902). Details of this process will be described later with reference to Figure 10A.

[0050] Next, the KPI prediction function 113 of the control unit 103 calculates the predicted value of the KPI with probabilities (step S903). Details of this process will be described later with reference to Figure 10B.

[0051] Next, the prediction result visualization function 114 visualizes the prediction results (step S904). Specifically, it outputs information for displaying the prediction results. Details of this process will be described later with reference to Figure 11.

[0052] Next, the processes performed by the control unit 103 in Figure 1 when visualizing the relationship between the resource plan and the work time update accuracy, and the relationship between the resource usage plan and the probabilistic predicted values ​​of the KPI, will be explained with reference to Figures 10A and 10B.

[0053] Figure 10A is a flowchart showing an example of the process performed by the work time update accuracy prediction function 112 of the resource utilization setting device in Embodiment 1.

[0054] The work time update accuracy prediction function 112 of the control unit 103 reads each information item (columns 401 to 404) from the resource usage information storage unit of the new product, each information item (columns 501 to 503) from the resource type information storage unit of the information storage unit 102, each information item (columns 601 to 604) from the work performance information storage unit of the past product, each information item (columns 701 to 703) from the work time information storage unit of the past product, and each information item (columns 801 to 803) from the sales plan information storage unit of the new product (step S101).

[0055] The sales plan information for the new product read here is used to predict the production volume of the new product (more specifically, the actual number of operations performed for future production). In other words, the number of units sold for the new product obtained here is treated as the planned production volume for the new product. If the production plan can be obtained from information other than the sales plan, that information may be obtained instead.

[0056] Next, the work time update accuracy prediction function 112 learns the relationship between the actual number and the work time update accuracy for each type of resource that has been loaded (step S102). Any means can be used to learn the relationship between the actual number and the work time update accuracy, but for example, machine learning may be used.

[0057] Specifically, the work time update accuracy prediction function 112 classifies the records in the read past product's work performance information storage unit 600 by resource type by matching each information item (columns 501 to 503) in the read resource type information storage unit 500 with each information item (columns 601 to 604) in the read past product's work performance information storage unit 600, and calculates the number of actual work for each resource type. In addition, the work time update accuracy prediction function 112 extracts standard work time information for each resource type by matching each information item (columns 701 to 703) in the read resource type information storage unit 500 with each information item (columns 701 to 703) in the read past product's work time information storage unit 700.

[0058] The work time update accuracy prediction function 112 then calculates the update accuracy when updating work time information using work performance information, based on the work performance information for each classified resource type and the standard work time information for each extracted resource type. By using machine learning with the relationship between the number of actual work performed for each resource type calculated from past information and the update accuracy for each resource type calculated from past information as training data, the relationship between the number of actual work performed for each resource type and the work time update accuracy can be learned.

[0059] Generally, the larger the number of actual data points, the higher the accuracy of updating work time. Furthermore, when the resource type is automated equipment that performs tasks without human intervention (as in the example in Figure 5), the variability in work time tends to be smaller compared to other cases (as in the example in Figure 5, "equipment + people" or "people"). Therefore, even with the same number of actual data points, the accuracy of updating work time tends to be higher when the resource type is automated equipment than when it is other types. For example, the above trend could be learned as the relationship between the number of actual data points for each resource type and the accuracy of updating work time.

[0060] Next, the work time update accuracy prediction function 112 performs the processing in the following steps S104 to S108 for all possible resource usage proposals that can be considered from the combinations of equipment and workers available during production, which have been generated by the resource usage proposal generation function 111 (step S103). The resource usage proposal generation function 111 may generate all resource usage proposals in the following way, for example. That is, the resource usage proposal generation function 111 aggregates each information item (columns 401 to 404) of the resource usage information storage unit 400 of the new product that has been read, using the product name information 402 as the key, for each product, and generates all resource usage proposals by listing all combination patterns of resources that can be used for each process performed when manufacturing each product.

[0061] Next, the work time update accuracy prediction function 112 performs the following steps S105 to S107 for all resources included in one resource usage plan (step S104).

[0062] The work time update accuracy prediction function 112 uses the read sales plan information for the new product to predict the number of actual units that can be obtained in the future using that resource (S105). As a means of predicting the number of actual units that can be obtained in the future using a certain resource, by assigning a certain resource usage proposal for the product to each piece of information (columns 801 to 803) in the read sales plan information storage unit for the new product, for example, by making the assumption that work is evenly allocated to multiple selectable resources, the number of actual units that can be obtained in the future using that resource can be predicted.

[0063] For example, if the new product is product A, the sales target for product A based on the sales plan is 1000 units. In a certain resource usage plan, if two resources, "Cutting 1" and "Cutting 2," are used in the cutting process of product A, the actual number of units that can be acquired in the future using each resource may be "500," which is 1000 units divided equally between the two resources. However, depending on the status of each resource, the actual number of units that can be acquired in the future may be calculated using methods other than equal allocation.

[0064] Next, the work time update accuracy prediction function 112 uses each information item (columns 501 to 503) from the read resource type information storage unit to determine the resource type of the resource in question (step S106).

[0065] Then, the work time update accuracy prediction function 112 predicts the work time update accuracy for the resource in question (step S107). For example, the work time update accuracy prediction function 112 extracts the relationship between the actual number of tasks and the work time update accuracy for each resource type, which was learned in step S102, and the resource type information determined in step S106. By applying the number of tasks that can be obtained in the future, as predicted in step S105, to the extracted relationship between the actual number of tasks and the work time update accuracy for that resource type, the work time update accuracy can be predicted.

[0066] The work time update accuracy prediction function 112 performs the processing from step S105 onward for all resources included in a single resource usage plan, and then aggregates the work time update accuracy of that resource usage plan (step S108). For example, the work time update accuracy prediction function 112 may determine the work time update accuracy of the resource usage plan by applying a predetermined weight coefficient to the work time update accuracy of the resources in each process of the resource usage plan and performing a weighted sum.

[0067] The work time update accuracy prediction function 112 obtains the work time update accuracy for each resource usage plan by performing the processes in steps S104 to S108 for all resource usage plans.

[0068] Furthermore, the accuracy of updating work time can be rephrased as the accuracy of calculating new work time for updating work time information.

[0069] Figure 10B is a flowchart showing an example of the process performed by the KPI prediction function 113 of the resource utilization setting device in Example 1.

[0070] When the work time update accuracy prediction function 112 calculates the work time update accuracy for each resource option using the process shown in Figure 10A, the KPI prediction function 113 of the control unit 103 then executes the process shown in Figure 10B. First, the KPI prediction function 113 reads the work time update accuracy information for each resource option calculated by the work time update accuracy prediction function 112, in addition to the information held by the information storage unit 102 (step S201).

[0071] The KPI prediction function 113 performs the following processing on all proposed resource usage combinations that can be considered from the combinations of equipment and workers available during production, which have been generated by the proposed resource usage generation function 111 (step S202).

[0072] The KPI prediction function 113 calculates the planned KPI for one resource usage proposal (step S203). For example, the KPI prediction function 113 may assume that when producing a new product in quantities of 803 units, the work is evenly distributed among multiple selectable resources, assign each task to each resource, and then use event-driven simulation to calculate the time from the start time to the end time of each task, thereby formulating a production plan for the new product.

[0073] The work time used to calculate the time from the start time to the end time of each task may, for example, be the work time 703 of each resource contained in the work time information storage unit 700 of the loaded past products, or the estimated work time of the new product entered by the person in charge 301 in the input process 302 may be used. By calculating the number of units produced per unit time and the utilization rate of each resource for the devised production plan, it is possible to calculate the planned KPI for one resource usage plan.

[0074] Next, the KPI prediction function 113 calculates a probabilistic predicted value of the KPI, which represents the discrepancy between the planned KPI and the KPI when production is actually carried out (step S204). For example, the KPI prediction function 113 uses the loaded work time update accuracy information to assign a range to the work time of each resource used, centered on the standard work time, based on the magnitude of the work time update accuracy value for each resource type. Then, the KPI prediction function 113 formulates multiple production plans by changing the work time used when performing event-driven simulation within the above work time range. For each production plan, the KPIs such as the number of units produced per unit time and the utilization rate of each resource are calculated and aggregated to calculate a probabilistic predicted value of the KPI for one resource usage plan.

[0075] Here, the probabilistic predicted value of the KPI may be a value indicating the magnitude of the variation in the KPI predicted based on the work time update accuracy. For example, in calculating the probabilistic predicted value of the KPI (step S204), the KPI prediction function 113 may calculate the KPIs for multiple production plan patterns formulated for one resource usage proposal as described above, and obtain the maximum and minimum values ​​of the range in which the KPI varies as the probabilistic predicted value of the KPI based on the work time update accuracy for each resource. The maximum and minimum values ​​of the range in which the KPI varies are also referred to as the actual KPI upper limit and actual KPI lower limit for the resource usage proposal, respectively. In general, the lower the work time update accuracy of the resources included in the resource usage proposal, the larger the range in which the KPI varies.

[0076] The KPI prediction function 113 calculates a probabilistic predicted value of the KPI for each resource option by performing the processes in steps S203 to S204 for all resource usage options.

[0077] Next, the prediction result visualization function 114 of the control unit 103 displays the calculated work time update accuracy and the predicted values ​​with probabilities of KPIs for each resource plan on the result display unit 104 of the resource usage setting device 101, for example, in a format like that shown in Figure 11.

[0078] Figure 11 is an explanatory diagram showing an example of the resource usage proposal display screen displayed by the result display unit 104 of the resource usage setting device 101 of Embodiment 1.

[0079] The resource usage proposal display screen 1101 in the example output screen of Embodiment 1 shown in Figure 11 includes a resource usage proposal display unit 1102, a work time update accuracy and KPI relationship display unit 1103, a KPI details display unit 1104, and a work time update accuracy details display unit 1105.

[0080] The resource usage proposal display unit 1102 of the resource usage proposal display screen 1101 can accept input processing 302 in which the person in charge 301 selects any resource. The result display unit 104 updates the display contents of the resource usage proposal display unit 1102, the work time update accuracy and KPI relationship display unit 1103, and the KPI details display unit 1104 to visualize the work time update accuracy and predicted value information with probabilities of KPIs calculated for the resource proposal based on the resources selected by the person in charge 301.

[0081] Here, we will explain a specific example of the output screen shown in Figure 11. The resource usage plan display unit 1102 displays, for each process necessary to produce a new product (for example, product A), the resources to which work can be assigned in a process, and the resources to which work has been assigned in the resource usage plan. In Figure 11, resources to which work has been assigned in the resource usage plan (i.e., applicable resources) are shown as black rectangles, and resources to which work can be assigned but which have not been assigned in the resource usage plan (i.e., unapplicable resources) are shown as dotted lines and outlined rectangles.

[0082] Figure 11 shows an example of work allocation for four processes, from process 1 to process 4, for the production of a new product. In this example, the work for processes 1, 2, 3, and 4 can be allocated to two, three, two, and two resources, respectively. In the displayed resource usage plan, the work for processes 1, 2, 3, and 4 is allocated to two, two, one, and two resources, respectively.

[0083] The KPI detail display unit 1104 displays the predicted KPI values ​​for the resource usage plan shown in the resource usage plan display unit 1102. The KPIs displayed here may be the planned KPIs calculated in step S203. Various indicators can be used as KPIs. In the example in Figure 11, the number of resource paths a product takes from the time it is put into the production line until it is completed, the production volume per unit time, and the production cost are calculated and displayed.

[0084] The detailed work time update accuracy display unit 1105 displays information regarding the predicted work time update accuracy for the proposed resource usage displayed in the proposed resource usage display unit 1102. Specifically, the detailed work time update accuracy display unit 1105 may display the name of each applicable resource in the displayed proposed resource usage, the actual number predicted in step S105 for each applicable resource, the resource type determined in step S106 for each applicable resource, and the predicted work time update accuracy in step S107 for each applicable resource.

[0085] The Work Time Update Accuracy and KPI Relationship Display Unit 1103 displays the relationship between work time update accuracy and KPI calculated for all resource usage proposals generated by the resource usage proposal generation function 111, as well as the resource usage proposal display unit 1102. Figure 11 shows a graph with work time update accuracy on the horizontal axis and KPI on the vertical axis. The black circles plotted on the graph represent the planned KPI calculated for each resource usage proposal, and the error bars indicate the range from the upper limit to the lower limit of the actual KPI.

[0086] Generally, the fewer resources used, the lower the KPI, such as production per unit of time. However, fewer resources mean a higher number of actual tasks performed by each resource, thus increasing the accuracy of work time updates. For this reason, resource usage plans with higher work time update accuracy tend to result in lower planned KPI values. The upper limit of actual KPIs follows a similar trend. On the other hand, lower work time update accuracy tends to increase KPI variability, so as work time update accuracy increases, the lower limit of actual KPIs may also increase.

[0087] In the example in Figure 11, the upper limits of the planned KPI and actual KPI decrease monotonically with increasing accuracy of work time updates, while the lower limit of the actual KPI has a peak. Therefore, if person in charge 301 prioritizes KPI values ​​that do not take variability into account, it is appropriate to adopt the resource usage plan that maximizes the planned KPI and minimizes the accuracy of work time updates. However, if the priority is to obtain relatively good KPIs even in the worst-case scenario, it is appropriate to adopt the resource usage plan that maximizes the lower limit of the actual KPI.

[0088] Furthermore, the person in charge may specify whether to apply or exclude each resource by clicking or tapping the rectangle representing each resource displayed in the resource usage proposal display unit 1102. When the resource usage proposal is changed in this way, the display of the KPI details display unit 1104 and the work time update accuracy details display unit 1105 will also be changed accordingly. In addition, among the KPIs displayed in the work time update accuracy and KPI relationship display unit 1103, those corresponding to the resource usage proposal displayed in the resource usage proposal display unit 1102 may be displayed separately from others (for example, by using a different color or a different shape).

[0089] As a result, by visualizing the accuracy of work time updates and the probabilistic predicted values ​​of KPIs (e.g., predicted values ​​within the range of KPI variability) for proposed resource usage, and by allowing people to judge the trade-offs and select appropriate resources, it becomes possible to set resource usage while simultaneously considering the accuracy of work time updates and the probabilistic predicted values ​​of production KPIs. [Examples]

[0090] In Example 2, we describe a case where, based on the accuracy of updating work time for proposed resource usage and the calculation results of probabilistic predicted values ​​of KPIs, a proposed resource usage that maximizes a predetermined evaluation indicator is searched for. Except for the differences described below, each part of the system in Example 2 has the same function as each part with the same reference numerals in Example 1, so their descriptions are omitted.

[0091] Figure 12 is a block diagram showing the system configuration of the resource usage setting device in Example 2.

[0092] Note that the various devices connected to the resource usage setting device 1201 are the same as the various devices connected to the resource usage setting device 101 in the system configuration of Embodiment 1 shown in Figure 1, and therefore are not shown in Figure 12.

[0093] The resource usage setting device 1201 described in Example 2 has basically the same configuration as the resource usage setting device 101 in the system configuration of Example 1 shown in Figure 1, and the means described in Example 1 can be used to calculate the work time update accuracy and the probabilistic predicted value of the KPI for the proposed resource usage.

[0094] In other words, the resource usage setting device 1201 comprises an information storage unit 1202, a control unit 1203, and a result display unit 1204. The information storage unit 1202 comprises a new product resource usage information storage unit 400, a resource type information storage unit 500, a past product work performance information storage unit 600, a past product work time information storage unit 700, and a new product sales plan information storage unit 800. These are the same as those provided in the information storage unit 102 of the resource usage setting device 101 of Embodiment 1, so their explanation is omitted.

[0095] The control unit 1203 includes a resource usage plan generation function 1211, a work time update accuracy prediction function 1212, a KPI prediction function 1213, a prediction result visualization function 1214, and a resource usage plan search function 1215. Of these, the resource usage plan generation function 1211, the work time update accuracy prediction function 1212, the KPI prediction function 1213, and the prediction result visualization function 1214 are the same as the resource usage plan generation function 111, the work time update accuracy prediction function 112, the KPI prediction function 113, and the prediction result visualization function 1214 in Embodiment 1, respectively, so their explanation is omitted. That is, each of these functions performs the same processing as in Figures 9 to 10B. The resource usage plan search function 1215 searches for a resource usage plan that maximizes the evaluation indicators for pre-set evaluation indicators.

[0096] In the following section, the process performed by the resource usage suggestion search function 1215 of the resource usage setting device 1201 when searching for a resource usage suggestion that maximizes the evaluation index will be explained with reference to Figure 13. Note that the process of the resource usage suggestion search function 1215 may also be performed in step S904 of Figure 9.

[0097] Figure 13 is a flowchart showing an example of the process performed by the resource usage suggestion search function 1215 of the resource usage setting device 1201 in Embodiment 2.

[0098] First, the resource usage suggestion search function 1215 of the resource usage setting device 1201 accepts the selection of an evaluation index (step S1301). For example, the resource usage suggestion search function 1215 may accept the selection of an evaluation index using an evaluation index selection screen 1401, as shown in Example 1 of the output screen of Embodiment 2 (Figure 14).

[0099] Figure 14 is an explanatory diagram showing an example of the selection screen for evaluation indicators displayed by the result display unit 1204 of the resource setting device 1201 of Embodiment 1.

[0100] Specifically, the results display unit 1204 displays several pre-designed evaluation indicators on the evaluation indicator selection screen 1401 and accepts input processing 302 from the person in charge 301 to select an evaluation indicator. In this embodiment, as illustrated in Figure 14, three candidates are listed as candidates for selecting an evaluation indicator: (1) the highest planned KPI, (2) the highest upper limit of the actual KPI, and (3) the highest lower limit of the actual KPI.

[0101] (1) If the evaluation metric is selected as maximizing the planned KPI, then the resource usage plan that maximizes the planned KPI will be explored, without considering the discrepancy between the planned KPI and the KPI when production is actually carried out.

[0102] (2) If the upper limit of the actual KPI is selected as the evaluation metric, the resource usage plan that maximizes the maximum value of the probabilistic predicted value of the production KPI calculated by the means described in Example 1 is searched for, in other words, the resource usage plan that maximizes the KPI when actual production is carried out in the most rational way.

[0103] (3) If the lower limit of the actual KPI is selected as the evaluation metric, the resource usage plan is searched for that maximizes the minimum value of the probabilistic predicted value of the production KPI calculated by the means described in Example 1, in other words, the resource usage plan that maximizes the KPI even in the most irrational case of actual production.

[0104] Next, the resource usage proposal search function 1215 of the resource usage setting device 1201 reads the predicted values ​​with probabilities of the work time update accuracy and KPIs for the resource usage proposal, which were calculated by the means described in Example 1 (step S1302).

[0105] Then, the resource usage plan search function 1215 of the resource usage setting device 1201 searches for a resource usage plan that maximizes the selected evaluation indicator (step S1303). For example, if the selected evaluation indicator is (3) the lower limit of the actual KPI is maximized, a full search is performed on all resource usage plans generated by the means described in Example 1 to find the resource usage plan that maximizes the minimum value of the probabilistic predicted value of the production KPI. The resource usage plan obtained as a result of this search (in the above example, the resource usage plan that maximizes the lower limit of the actual KPI) will be referred to as the searched resource usage plan in the following description.

[0106] The resource usage suggestion search function 1215 of the resource usage setting device 1201 outputs the searched resource usage suggestions (S1304). For example, the resource usage suggestion search function 1215 displays a screen in the format of Example 2 of the output screen of Embodiment 2 shown in Figure 15 on the result display unit 1204 of the resource usage setting device 1201.

[0107] Figure 15 is an explanatory diagram showing an example of the resource usage suggestion search result display screen displayed by the result display unit 1204 of the resource usage setting device 1201 of Embodiment 2.

[0108] The resource usage proposal search result display screen 1501 shown in Figure 15 includes a display unit 1502 for the searched resource usage proposals, a display unit 1503 for the relationship between work time update accuracy and KPIs, a detailed KPI display unit 1504, and a detailed work time update accuracy display unit 1505.

[0109] The resource usage plan display unit 1502 on the resource usage plan search result display screen 1501 displays the resources that were applied and the resources that were not applied in the searched resource usage plan. The display method of the searched resource usage plan display unit 1502 may be the same as that of the resource usage plan display unit 1102 in Embodiment 1.

[0110] The resource usage proposal search result display screen 1501, specifically the work time update accuracy and KPI relationship display unit 1503, displays the position of the searched resource usage proposal in relation to the work time update accuracy and KPI. The display method of the work time update accuracy and KPI relationship display unit 1503 may be basically the same as that of the work time update accuracy and KPI relationship display unit 1103 in Embodiment 1. However, in the work time update accuracy and KPI relationship display unit 1503, the KPI corresponding to the searched resource usage proposal may be clearly indicated by highlighting or other means.

[0111] The KPI detail display section 1504 on the resource usage proposal search result display screen 1501 displays detailed information about the KPIs when the searched resource usage proposals are applied. The display method of the KPI detail display section 1504 may be the same as that of the KPI detail display section 1104 in Embodiment 1.

[0112] The detailed work time update accuracy display unit 1505 on the resource usage proposal search result display screen 1501 displays detailed information about the work time update accuracy when the searched resource usage proposal is applied. The display method of the detailed work time update accuracy display unit 1505 may be the same as that of the detailed work time update accuracy display unit 1105 in Embodiment 1.

[0113] Based on the above, it becomes possible to search for resource usage proposals that maximize evaluation indicators, based on the accuracy of updating work time for proposed resource usage and the calculation results of probabilistic predicted values ​​for KPIs, and to output the searched resource usage proposals.

[0114] Furthermore, the system of the embodiment of the present invention may be configured as follows.

[0115] (1) A method for setting resources to be used, which is performed by a resource usage setting device (e.g., resource usage setting device 101 or 1201), wherein the resource usage setting device comprises a control unit (e.g., control unit 103 or 1203) and a storage unit (e.g., storage unit 102 or 1202), the storage unit holding resource type information (e.g., information contained in resource type information storage unit 500), work time information (e.g., information contained in past product work performance information storage unit 600), and production plan information (e.g., information contained in new product sales plan information storage unit 800), the resource type information includes information that identifies the type of resource that can be used for work in the process of producing a product, the work time information includes information that indicates the time required for work previously performed using each resource, and production plan information The method for setting resources includes information indicating the number of products whose production is planned, and the method for setting resources includes a first step (e.g., step S902, Figure 10A) in which the control unit predicts the accuracy of calculating the required time for work in a proposed resource usage plan that allocates one or more resources to work in each process of producing a product, based on resource type information, work time information, and production plan information, and a second step (e.g., step S903, Figure 10B) in which the control unit predicts evaluation indicators (e.g., KPIs such as production volume and cost) for product production if the proposed resource usage plan is adopted, based on the proposed resource usage plan, work time information, and production plan information, and the second step includes a step (e.g., step S204) in which the control unit predicts the variability of the evaluation indicators based on the accuracy of calculating the required time for work in the proposed resource usage plan.

[0116] This makes it possible to calculate predicted values ​​that include the accuracy of work time updates for proposed resource usage and the variability of key performance indicators (KPIs), and then set the resources to be used while taking these factors into consideration.

[0117] (2) In (1) above, the storage unit further stores resource usage information (for example, information contained in the new product resource usage information storage unit 400), the resource usage information includes information that identifies one or more resources that can be used for the work of each process in producing the product, and the resource usage setting method further includes a third step (for example, step S901) in which the control unit generates a plurality of resource usage proposals based on the resource usage information, and the first and second steps are performed for each of the plurality of resource usage proposals generated in the third step.

[0118] This makes it possible to select the appropriate resource from multiple resource usage options.

[0119] (3) The above (1) further includes a fourth step (for example, step S904) in which the control unit outputs information for displaying the results of predicting the variation of the evaluation index on the screen.

[0120] This makes it possible to visualize the accuracy of work time updates and the range of KPI variations for proposed resource usage, allowing people to make trade-off judgments and select appropriate resources.

[0121] (4) In the first step of (1) above, the control unit learns the relationship between the number of actual tasks and the calculation accuracy of the required time for each type of resource based on the resource type information and the work time information (for example, step S102), predicts the number of actual tasks to be performed in the future with the resources allocated to each process based on the proposed resource usage and the production plan information (for example, step S105), determines the type of resource allocated to each process based on the proposed resource usage and the resource type information (for example, step S106), and predicts the calculation accuracy of the required time for the proposed resource usage by applying the predicted number of actual tasks and the determination result of the resource type to the learned relationship between the number of actual tasks and the calculation accuracy of the required time for each type of resource (for example, step S107).

[0122] This allows for accurate prediction of the time required for each proposed use of resources.

[0123] (5) In (4) above, the types of resources include at least automated equipment that performs work without human intervention (for example, the value of resource type 503 "automated equipment") and others (for example, the value of resource type 503 "equipment + person" or "person").

[0124] This makes it possible to predict the accuracy of the required time calculation with high precision, based on the variation in work time depending on the type of resource.

[0125] (6) In (1) above, the first and second steps are performed for each of the multiple resource usage options, and the resource usage setting method further includes a fifth step (for example, the processing of the resource usage option search function 1215 in step S904) in which the control unit selects one of the multiple resource usage options according to predetermined selection criteria based on evaluation indicators.

[0126] This enables the search for resource usage proposals that maximize evaluation metrics, based on the accuracy of work time updates for proposed resource usage and the predicted range of KPI variability, as well as the output of the searched resource usage proposals.

[0127] (7) In the fifth step of (6) above, if information specifying one of several selection criteria is input (for example, input from the screen shown in Figure 14), the control unit selects one of several resource usage options according to the specified selection criteria.

[0128] This makes it possible to configure resource usage based on selection criteria chosen by the user.

[0129] (8) In (1) above, the multiple selection criteria are that the evaluation indicator that does not include variability based on the accuracy of calculating the required time for work in the proposed resource usage (e.g., the planned KPI calculated in step S203) is the highest, the upper limit of the range of variability in the evaluation indicator (e.g., the upper limit of the actual KPI calculated in step S204) is the highest, and the lower limit of the range of variability in the evaluation indicator (e.g., the lower limit of the actual KPI calculated in step S204) is the highest.

[0130] This makes it possible to configure resource usage based on selection criteria chosen by the user.

[0131] (9) In the first step of (1) above, if information specifying any resource is input, the control unit predicts the accuracy of calculating the time required for the work in the proposed resource usage, including the allocation of the specified resource to the work.

[0132] This allows for the evaluation of proposed resource usage, including resources arbitrarily specified by the user.

[0133] The above-described embodiments are not limiting to the present invention, and the present invention includes various modifications. The above-described embodiments are described in detail to explain the present invention in an easy-to-understand manner, and for example, it is not necessary to have all of the described configurations. Furthermore, it is possible to replace parts of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add configurations from other embodiments to the configuration of one embodiment. In addition, it is possible to add, delete, or replace parts of the configuration of each embodiment with other configurations.

[0134] Furthermore, each of the above configurations, functions, processing units, and processing means may be implemented in hardware, in whole or in part, for example, by designing them as integrated circuits. Alternatively, each of the above configurations, functions, and means may be implemented in software by having the processor interpret and execute programs that implement each function. Information such as programs, tables, and files that implement each function can be stored in memory, a recording device such as a hard disk or SSD (Solid State Drive), or a computer-readable non-temporary data recording medium such as an IC card, SD card, or DVD.

[0135] Furthermore, the control lines and information lines shown are those deemed necessary for explanatory purposes, and do not necessarily represent all control lines and information lines in the actual product. In practice, it can be assumed that almost all components are interconnected. [Explanation of Symbols]

[0136] 101, 1201... Resource usage setting device 102, 1202...information storage section 103, 1203… Control Unit 104, 1204...Result display section 105…Production control equipment 106…Work performance information for past products 107…Work time information for past products 108...Sales planning device 109…New product sales plan information 111, 1211... Resource usage proposal generation function 112, 1212... Work time update accuracy prediction function 113, 1213…KPI prediction function 114, 1214... Prediction result visualization function 400... New product resource information storage unit 500... Resource type information storage unit 600...Storage unit for past product work performance information 700...Storage unit for storing information on the working time of past products 800... New product sales plan information storage unit 201… Information terminal 202...Input device 203…Output device 204…Auxiliary storage device 205...Arithmetic device 206…Central Processing Unit (CPU) 207…Main memory 208… Interface 301... Person in charge 302... Input Processing 303... Output processing 1215... Resource Usage Proposal Search Function

Claims

1. A method for setting resources used by a resource setting device, The aforementioned resource setting device includes a control unit and a storage unit. The aforementioned storage unit holds resource type information, work time information, and production plan information. The aforementioned resource type information includes information that identifies the type of resource that can be used in the work of the process for producing the product, The aforementioned work time information includes information indicating the time required for tasks previously performed using each of the aforementioned resources. The production plan information includes information indicating the number of the products for which production is planned, The aforementioned method for setting the resources to be used is: The control unit performs a first step of predicting the accuracy of calculating the required time for each task in a resource usage plan, which allocates one or more of the resources to each task in the process of producing the product, based on the resource type information, the work time information, and the production plan information. The control unit includes a second step of predicting an evaluation index for the production of the product if the proposed resource usage is adopted, based on the proposed resource usage, the work time information, and the production plan information. The second procedure includes a step in which the control unit predicts the variability of the evaluation index based on the calculation accuracy of the required time for the work in the proposed resource usage, The storage unit further stores information about the resources being used. The resource usage information includes information that identifies one or more resources that can be used for the work of each process in producing the product. The method for setting the resource usage further includes a third step in which the control unit generates a plurality of resource usage proposals based on the resource usage information, A method for setting usage resources, characterized in that the first and second steps are performed for each of the plurality of usage resource proposals generated in the third step.

2. A method for setting the resources to be used according to Claim 1, A method for setting resources to be used, further comprising a fourth step in which the control unit outputs information for displaying the results of predicting the variation of the evaluation index on the screen.

3. A method for setting resources to be used, which is performed by a resource setting device, The aforementioned resource setting device includes a control unit and a storage unit. The aforementioned storage unit holds resource type information, work time information, and production plan information. The aforementioned resource type information includes information that identifies the type of resource that can be used in the work of the process for producing the product, The aforementioned work time information includes information indicating the time required for tasks previously performed using each of the aforementioned resources. The production plan information includes information indicating the number of the products for which production is planned, The aforementioned method for setting the resources to be used is: The control unit performs a first step of predicting the accuracy of calculating the required time for each task in a resource usage plan, which allocates one or more of the resources to each task in the process of producing the product, based on the resource type information, the work time information, and the production plan information. The control unit includes a second step of predicting an evaluation index for the production of the product if the proposed resource usage is adopted, based on the proposed resource usage, the work time information, and the production plan information. The second procedure includes a step in which the control unit predicts the variability of the evaluation index based on the calculation accuracy of the required time for the work in the proposed resource usage, In the first step described above, the control unit, Based on the resource type information and the work time information, the relationship between the actual number of tasks performed and the calculation accuracy of the required time for each resource type is learned. Based on the proposed resource usage and the production plan information, the actual number of tasks to be performed in the future using the resources allocated to each process is predicted. Based on the proposed resource usage and the resource type information, the type of resource assigned to each of the processes is determined. A method for setting resources to use, characterized by predicting the calculation accuracy of the required time for tasks in the proposed resource usage plan by applying the predicted number of tasks and the determination result of the resource type to the relationship between the number of tasks performed for each type of resource learned and the calculation accuracy of the required time for tasks.

4. A method for setting the resources to be used according to Claim 3, A method for setting resources to be used, characterized in that the types of resources include at least automated equipment that performs work without human intervention and other resources.

5. A method for setting resources to be used, which is performed by a resource setting device, The aforementioned resource setting device includes a control unit and a storage unit. The aforementioned storage unit holds resource type information, work time information, and production plan information. The aforementioned resource type information includes information that identifies the type of resource that can be used in the work of the process for producing the product, The aforementioned work time information includes information indicating the time required for tasks previously performed using each of the aforementioned resources. The production plan information includes information indicating the number of the products for which production is planned, The aforementioned method for setting the resources to be used is: The control unit performs a first step of predicting the accuracy of calculating the required time for each task in a resource usage plan, which allocates one or more of the resources to each task in the process of producing the product, based on the resource type information, the work time information, and the production plan information. The control unit includes a second step of predicting an evaluation index for the production of the product if the proposed resource usage is adopted, based on the proposed resource usage, the work time information, and the production plan information. The second procedure includes a step in which the control unit predicts the variability of the evaluation index based on the calculation accuracy of the required time for the work in the proposed resource usage, The first and second procedures are performed for each of the multiple resource usage proposals, The method for setting the resources to be used is characterized in that the control unit further includes a fifth step in which it selects one of the plurality of proposed resources to be used according to predetermined selection criteria based on the evaluation index.

6. A method for setting the resources to be used according to Claim 5, In the fifth step, the control unit, when information specifying one of a plurality of selection criteria is input, selects one of the plurality of resource usage options according to the specified selection criteria, characterized in that the resource usage setting method is characterized in that

7. A method for setting the resources to be used according to Claim 6, A method for setting resources to be used, characterized in that the multiple selection criteria are any of the following: the evaluation index which does not include variability based on the calculation accuracy of the required time for work in the proposed resource usage is the highest; the upper limit of the range of variability in the evaluation index is the highest; and the lower limit of the range of variability in the evaluation index is the highest.

8. A method for setting the resources to be used according to Claim 1, A method for setting resources to be used, characterized in that, in the first step, when information specifying any of the resources is input, the control unit predicts the accuracy of calculating the required time for the work in the proposed resource usage plan, including the allocation of the specified resources to the work.

9. A resource setting device, It has a control unit and a storage unit, The aforementioned storage unit holds resource type information, work time information, and production plan information. The aforementioned resource type information includes information that identifies the type of resource that can be used in the work of the process for producing the product, The aforementioned work time information includes information indicating the time required for tasks previously performed using each of the aforementioned resources. The production plan information includes information indicating the number of the products for which production is planned, The control unit, Based on the resource type information, the work time information, and the production plan information, the accuracy of calculating the required time for each task in the resource usage plan, which allocates one or more of the resources to each task in the process of producing the product, is predicted. Based on the proposed resource usage, the work time information, and the production plan information, the evaluation indicators for the production of the product when the proposed resource usage is adopted are predicted. Based on the accuracy of calculating the required time for the tasks in the proposed resource usage, the variability of the evaluation indicators is predicted. The storage unit further stores information about the resources being used. The resource usage information includes information that identifies one or more resources that can be used for the work of each process in producing the product. The control unit, Based on the resource usage information, a plurality of proposed resource usage options are generated. A resource usage setting device characterized by performing, for each of the generated plurality of resource usage proposals, the following: predicting the accuracy of calculating the required time for the work in the resource usage proposal; predicting the production evaluation indicators for the product if the resource usage proposal is adopted; and predicting the variability of the evaluation indicators.

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