Plan coordination support apparatus, plan coordination support system, and plan coordination support method

Abstract

To provide a method and a device for cooperating a plurality of plans capable of optimizing the whole supply chain by cooperating the plans of different planning cycles.SOLUTION: A plan coordination support device capable of executing a process of coordinating a plurality of plans having contents different from each other output by one or more planning devices, wherein an output of the planning device includes a time-series plan output and an index related to a KPI of the plan output, and the plan coordination support device includes a filter function unit that determines that plan coordination is performed when the KPI satisfies a predetermined condition and plan coordination is not performed when the KPI does not satisfy the predetermined condition.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a plan coordination support device, a plan coordination support system, and a plan coordination support method. [Background technology]

[0002] In various plants, plant operation plans are prepared in advance and then operated. However, in order to prepare a plant operation plan, it is necessary to comprehensively consider departmental plans prepared by multiple departments, each taking into consideration the circumstances of that department, and ultimately come up with the most optimal plant operation plan possible.

[0003] For example, when formulating a plant operation plan, it is desirable to optimize the final plan by coordinating the plans of each department, such as the sales plan for sales, the process plan for production processes, the production plan for product production, the personnel plan for work instructions to workers, the inventory replenishment plan for inventory replenishment, and the procurement plan for procurement of parts, etc., based on the requirements of these departmental plans.

[0004] However, it is generally difficult to coordinate plans between departments, and plans tend to be formulated with priority given to each department's KPIs, resulting in many situations where overall optimization is not being achieved.In addition, in recent years, rising energy costs and the need for environmental considerations have led to a demand for plans that take energy costs and carbon neutrality into consideration.As such, there is a need for technology that can optimize the entire supply chain plan.

[0005] In this regard, Patent Document 1 discloses "a value chain planning collaboration method that uses a value chain planning collaboration device that configures and executes a combination of multiple software programs according to business operations, wherein at least one of the multiple software programs uses output parameters obtained from any other software program included in the multiple software programs as input parameters, and the value chain planning collaboration device performs an alternative solution request step that calculates multiple output parameters for each of the multiple software programs, and a display step that displays, as an overall plan, the output parameters that provide the best key performance indicator value for the entire value chain according to the combination of input and output parameters of the multiple software programs." [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Publication No. 2022-50057 Summary of the Invention [Problem to be solved by the invention]

[0007] When multiple plans are created in a specified order, the plan linking process may be started when a request is received after the device is started, or according to a predetermined cycle (for example, every day).

[0008] In such a case, the processing time of the entire device is determined by the plan with the longest processing time (typically, the processing time is proportional to the planning target period), while the execution cycle of the plan linkage process is determined by the plan with the shortest planning cycle.

[0009] For example, in a case where a production plan and a power plan are linked, if the processing time for the production plan is six hours and the planning cycle is once a month, and the processing time for the power plan is ten minutes and the planning cycle is once every 30 minutes, then the processing time for the entire device is six hours and the planning cycle is once every 30 minutes. In other words, since a process that takes six hours for the entire device is executed once every 30 minutes, the plan linkage process cannot be completed. Therefore, in order to complete the plan linkage process, Patent Document 1 has no choice but to exclude plans with short planning cycles from being linked. Therefore, it is difficult to link plans with planning cycles shorter than the processing time of the entire device.

[0010] As mentioned above, if overall optimization is attempted without taking differences in planning cycles into consideration, it may be difficult to coordinate plans with short planning cycles among the plans to be coordinated. In such cases, the plans to be coordinated are limited, reducing the effectiveness of overall optimization.

[0011] In Patent Document 1, the above-mentioned problem is not taken into consideration.

[0012] In view of this, the present invention aims to provide a plan coordination support device, a plan coordination support system, and a plan coordination support method that can coordinate plans with different planning cycles to optimize the entire supply chain. [Means for solving the problem]

[0013] In view of the above, the present invention provides a "plan coordination support device capable of executing a process for linking a plurality of plans with mutually different contents output by one or more planning devices, wherein the output of the planning devices includes a time-series plan output and an index related to the KPI of the plan output, and the plan coordination support device is characterized in that it has a filter function unit that determines to perform plan coordination if the KPI satisfies a predetermined condition, and not to perform plan coordination if the KPI does not satisfy the predetermined condition."

[0014] Furthermore, the present invention is defined as "a plan coordination support system made up of one or more planning devices that create plans with mutually different contents, and a plan coordination support device that can execute processing to coordinate multiple plans from the planning devices, wherein the output of the planning devices includes a time-series plan output and an index related to the KPI of the plan output, and the plan coordination support device is provided with a filter function unit that determines to perform plan coordination if the KPI satisfies a predetermined condition, and not to perform plan coordination if the KPI does not satisfy the predetermined condition."

[0015] Furthermore, the present invention is defined as "a plan coordination support method capable of using a computer to execute a process for coordinating multiple plans with different contents output by one or more planning devices, wherein the plans include a time-series plan output and an indicator related to a KPI of the plan output, and the computer determines to perform plan coordination if the KPI satisfies a predetermined condition, and not to perform plan coordination if the KPI does not satisfy the predetermined condition." [Effects of the Invention]

[0016] It is possible to provide a method and device for linking multiple plans that can link plans with different planning cycles to optimize the entire supply chain. [Brief explanation of the drawings]

[0017] [Figure 1] FIG. 2 is a diagram showing an example of functional blocks of the planning device 10. [Figure 2] FIG. 2 is a diagram showing an example of functional blocks of the plan coordination support device 20. [Figure 3] FIG. 1 is a diagram showing an example of the hardware and software configuration of a planning device 10. [Figure 4] FIG. 2 is a diagram showing an example of the hardware and software configuration of the plan coordination support device 20. [Figure 5] FIG. 10 is a diagram showing an example of master information D11 for a production plan. [Figure 6] FIG. 10 is a diagram showing an example of planned data D21 for a production plan. [Figure 7] FIG. 10 is a diagram showing an example of a planning output D31 for a production plan. [Figure 8] FIG. 10 is a diagram showing an example of an evaluation value D41 for a production plan. [Figure 9] FIG. 10 is a diagram showing an example of master information D12 for a power plan. [Figure 10] FIG. 10 is a diagram showing an example of planned data D22 for a power plan. [Figure 11] FIG. 10 is a diagram showing an example of a planned output D32 for a power plan. [Figure 12] FIG. 10 is a diagram showing an example of an evaluation value D42 for a power plan. [Figure 13] FIG. 10 is a diagram showing an example of a filter output D5 for a power plan. [Figure 14] 10 is a diagram showing an example of linked range data D6, which is one of the processing results of the plan linkage support device 20. FIG. [Figure 15] 10 is a diagram showing an example of targeting output data D7, which is one of the processing results of the plan coordination support device 20. FIG. [Figure 16] A flow diagram showing the overall flow of the planning collaboration support system. [Figure 17] FIG. 3 is a flowchart showing the processing flow of the planning device 10. [Figure 18A] FIG. 10 is a flowchart showing the flow of a filter process. [Figure 18B] FIG. 10 is a flowchart showing the flow of a filter process. [Figure 19A] FIG. 10 is a flowchart showing the flow of a targeting process. [Figure 19B] FIG. 10 is a flowchart showing the flow of a targeting process. [Figure 20] FIG. 4 is a diagram showing an example of a display screen of a display unit. [Figure 21] FIG. 10 is a diagram for explaining the concept of a threshold determination method. [Figure 22] FIG. 10 is a diagram showing an example of a targeting processing result. [Figure 23] FIG. 10 is a diagram showing an example of a targeting processing result. [Figure 24] FIG. 2 is a diagram schematically illustrating a series of processing steps according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0018] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0019] This invention targets the following supply chain plans. First, each department draws up a plan to optimize KPIs. Second, it is assumed that there is an upstream-downstream relationship between the processes of each department. Third, it is assumed that downstream processes draw up plans to meet the demand of upstream processes. In addition, the planning period and planning cycle differ for each process. The timing of planning is when the plan of a linked process is updated, or when the master information for the plan (e.g., production demand, electricity market price) is updated. Furthermore, it is assumed that the plan for the updated range is output each time the input is updated. [Example]

[0020] The plan collaboration support device according to the embodiment of the present invention is connected to a plurality of planning devices that create plans for each department, and obtains a plurality of department plans that are the processing results of these devices. Therefore, in the first embodiment, first, configuration examples of the plan collaboration support device are shown in Figures 2 and 4, and configuration examples of the planning device are shown in Figures 1 and 3 to clarify the functions and configuration examples of the hardware and software.

[0021] First, an example of the configuration of the planning device 10 will be described with reference to Figures 1 and 3. Figure 1 is a diagram showing an example of the functional blocks of the planning device 10, and the planning device 10, which is realized using a computer, can be represented as functional blocks of a memory unit 11, a processing unit 12, an input / output unit 13, and a communication unit 14. The memory unit 11 is formed with a plan input information storage area 11A that stores plan input information D1 and D2, and a plan output information storage area 11B that stores plan output information D3 and D4, and the processing functions of the processing unit 12 include at least a plan input update detection unit 12A, a plan planning unit 12B, and a plan evaluation unit 12C.

[0022] FIG. 3 is a diagram showing an example of the hardware and software configuration of the planning device 10. The planning device 10 is realized using a computer, and includes an input / output unit 13 including an input device 13A and an output device 13B, a communication device 14, a storage unit 11 including auxiliary storage devices 11-1 and memory 11-2, and a processor 12, which is a processing unit, all connected via a bus 15.

[0023] The auxiliary storage device 11-1 in Figure 3 corresponds to part of the storage unit 11 in Figure 1, and stores master information D1, which is plan input information, and planned data D2 in a plan input information storage area 11A, and store plan output information D3 and plan evaluation values ​​D4 in a plan output information storage area 11B. These data D1, D2, D3, and D4 are sometimes referred to as a table because they are stored in tabular form. Although not shown in the storage unit 11 in Figure 1, memory 11-2, which corresponds to part of the storage unit 11, stores at least a plan input update detection program PrA, a plan formulation program PrB, and a plan evaluation program PrC as programs to be executed by the processor 12.

[0024] Next, an example of the configuration of the plan coordination support device 20 will be described with reference to Figures 2 and 4. Figure 2 is a diagram showing an example of the functional blocks of the plan coordination support device 20. The plan coordination support device 20, which is realized using a computer, can be represented as functional blocks including a memory unit 21, a processing unit 22, an input / output unit 23, a communication unit 24, and a display unit 25. The memory unit 21 includes a plan cache memory area 21A that stores plan cache information D5 and a collaboration range memory area 21B that stores collaboration range memory information D6 and D7. The processing functions of the processing unit 22 include at least a filter function unit 22A and a targeting function unit 22B. In Figure 2, reference numeral 50 denotes a connection unit between the plan formulation device 10 and the plan coordination support device 20. Multiple unit plans are input to the plan coordination support device 20 via the connection unit 50.

[0025] The planning device 10 itself does not need to be multiple; one or more devices may be sufficient. The planning device 10 may be configured as an independent device, or may be a device that creates plans as part of the functionality of a core system or management system. Furthermore, the present invention can be applied to cases where a core system or management system creates multiple different types of plans.

[0026] 4 is a diagram showing an example of the hardware and software configuration of the plan coordination support device 20. The plan coordination support device 20 is realized using a computer and includes an input device 23A and an output device 23B as an input unit 23, a communication device 24, an auxiliary storage device 21-1 and a memory 21-2 as a storage unit 21, and a processor 22 as a processing unit, all of which are connected via a bus 26. However, the display unit 25 in FIG. 2 is shown as a partial function of the output device 23B in FIG. 4.

[0027] The auxiliary storage device 21-1 in Fig. 4 corresponds to the storage unit 21 in Fig. 2, and stores filter output information D5, which is planning cache information, in a planning cache storage area 21A, and stores linkage range information D6 and targeting output D7 in a linkage range storage area 21B. These data D5, D6, and D7 are sometimes referred to as a table because they are stored in table format. Although not shown in the storage unit 21 in Fig. 2, the memory 21-2 also includes at least a user interface program PrF in addition to a filter program PrD and a targeting program PrE as programs executed by the processor 22.

[0028] Next, various types of information handled by the planning device 10 and the plan collaboration support device 20 will be described with reference to Fig. 5 to Fig. 15. At this time, an example in which the plan collaboration support device 20 achieves plan collaboration between a production plan and a power plan will be described.

[0029] First, the planning device 10 handles master information D1 and planned data D2, which are input information stored in a plan input information storage area 11A, and the processing results of the planning device 10 are plan output D3 and evaluation value D4, which are stored in a plan output storage area 11B. Figures 5 to 8 show examples of master information D11, planned data D21, plan output D31, and evaluation value D41 for a production plan.

[0030] Figure 5 shows an example of master information D11 for production planning, where information such as product ID (D11a), delivery date D11b, and required quantity D11c is organized in a table format. According to this, which product should be produced, by when, and in how much is set as the basic requirements of the production planning department.

[0031] FIG. 6 shows an example of planned data D21 for a production plan, with information such as plan ID (D21a), production date D21b, product ID (D21c), and production volume D21d organized in table format. However, at this input stage, the production volume for each date is undetermined. This determines which products can be produced on each specific date. Note that the master information D11 for the production plan and the planned data D21 are linked to each other by product IDs and can be referenced from each other. Note that in this embodiment, plan IDs for production plans are assigned on a monthly basis.

[0032] 5 and 6 show input information for the production plan, while FIGS. 7 and 8 show examples of the plan output D31 and evaluation value D41 as the processing results of the planning device 10.

[0033] Figure 7 shows an example of plan output information D31 for a production plan, with information such as plan ID (D31a), production date D31b, product ID (D31c), and requested production volume D11c organized in table format. This table structure is basically the same as the planned data D21 in Figure 6, with the number of units to be produced on each production date added as a planned value. This sets a plan for which products to produce, when, and in what quantities.

[0034] Figure 8 shows an example of evaluation values ​​D41 for a production plan, with information such as plan ID (D41a), evaluation indicators D41b, and evaluation values ​​D41c organized in a table format. This allows you to determine what evaluation indicators to use for each individual plan and to express the evaluation results as specific numerical values. Evaluation values ​​are generally called key performance indicators (KPIs).

[0035] The plan output information D31 and the evaluation value D41 for the production plan are linked to each other by the plan ID and can be referenced. Furthermore, since the plan output information D31 has product ID information, all of the input / output data D11, D21, D31, and D41 for the production plan are linked to each other and can be referenced.

[0036] According to the production plan plan output D31 in Figure 7, for production plan 001, by continuing production with the content of producing 100 units of product 01 and 1,000 units of product 2 on 2024 / 01 / 10, and then producing 100 units of product 01 and 2,000 units of product 2 on 2024 / 01 / 11, a production plan has been presented that shows that by producing 3,000 units of product 01, 10,000 units of product 02, and 5,000 units of product 03 by delivery date D11b (2024 / 01 / 25) in Figure 5.

[0037] Furthermore, according to the evaluation value D41 of the production plan in Figure 8, when production plan 001 is evaluated from the perspective of evaluation index 01, the evaluation value is 100, whereas when it is evaluated from the perspective of evaluation index 02, the evaluation value is 50, which indicates that the evaluation index is a smaller value.

[0038] Figures 5 to 8 show examples of master information D11, planned data D21, planned output D31, and evaluation value D41 for production plans, while Figures 9, 10, 11, and 12 show examples of master information D12, planned data D22, planned output D32, and evaluation value D42 for power plans.

[0039] Generally, the production planning system and the power planning system are separate systems, and the plans are created to reflect the circumstances of each department.

[0040] 9 shows an example of master information D12 for a power plan, with information such as a process ID (D12a), product ID (D12b), lead time D12c, and unit consumption D12d organized in a table format. According to this, the basic requirements of the power planning department are set as to which products are handled in each process at the plant's production site, the lead time from the start to the end of the work, and the amount of power consumption as a unit consumption.

[0041] 10 is an example of planned data D22 for a power plan, in which information such as a plan ID (D22a), a production date D22b, a product ID (D21c), and a production amount D21d is organized in a table format. This indicates how much of each product can be produced on each specific date. The master information D11 and the planned data D21 for the production plan are linked to each other by product IDs and can be referenced. In this embodiment, the plan ID for the power plan is assigned on a daily basis.

[0042] 9 and 10 show input information for the power plan, while FIGS. 11 and 12 show examples of the plan output D32 and evaluation value D42 as the processing results of the plan formulation device 10. In FIG.

[0043] 11 shows an example of plan output information D32 for a power plan, in which information such as a plan ID (D32a), a date and time D32b, a process ID (D32c), and power consumption D32d is organized in a table format. According to this table, the power consumption for each process at each date and time is described as the value of a decision variable.

[0044] 12 is an example of an evaluation value D42 for a power plan, and the information on the plan ID (D42a), evaluation criteria D42b, and evaluation value D42c (KPI) is organized in a table format. This allows you to see what the evaluation criteria for a power plan are and express the evaluation results as specific numerical values.

[0045] The plan output information D32 and the evaluation value D42 for the power plan are linked to each other by a plan ID and can be referenced by each other. Furthermore, since the plan output information D32 and the evaluation value D42 contain information on either the plan ID or the process ID, or both, they can be referenced by each other with the master information D12 and the planned data D22, which are information on the input side of the power plan. As a result, all of the input / output data D11, D21, D31, and D41 for the power plan are linked to each other and can be referenced by each other.

[0046] Furthermore, in the above example, the power plan and production plan were generally initially created independently of each other, taking into account the circumstances of each department. However, because each of these information groups contains information about dates, it is possible to understand the interrelationships between the power and production plans at specific dates and times.

[0047] Although an electric power plan and a production plan are shown as examples here, in general there are upstream and downstream process relationships between the plans, and downstream plans are changed in order to comply with the upstream plan. For this reason, the plan linkage support device 20 of the present invention notifies the user that a relationship that will cause a problem between the upstream plan and the downstream plan has arisen, indicating that mutual adjustment is necessary and that linkage is required.

[0048] 11 shows that for power plan 001, process A will be executed at 10:00 on 2024 / 01 / 10, with the power consumption set to 300 kWh, while process B being executed at the same time will have a power consumption of 1000 kWh. A similar power plan is formulated, for example, at 30-minute intervals, and shows that process A will be executed at 10:30 on 2024 / 01 / 10, with the power consumption set to 500 kWh, while process B being executed at the same time will have a power consumption of 1500 kWh.

[0049] 12, the evaluation value D42 of the power plans indicates that the evaluation value of power plan 001 when evaluated from the perspective of evaluation index 03 is 1300, whereas the evaluation value of power plan 002 when evaluated from the perspective of evaluation index 03 is 2000, which is a larger numerical value for the evaluation index. Here, the evaluation values ​​in FIGS. 8 and 12 are obtained by calculating the key performance indicators KPI.

[0050] The production plan data D11, D21, D31, and D41 and the power plan data D12, D22, D32, and D42 have been explained above. These include various IDs and date and time information, and therefore can be referenced by each other. In order to execute a production plan at a certain date and time, it is necessary to take into account the power plan at that date and time, and the plan coordination support device 20 determines the need for adjustment between these data in accordance with the upstream and downstream relationships.

[0051] For this purpose, the plan collaboration support device 20 shown in Figures 2 and 4 obtains, as plans created by the plan formulation device 10, plan output data D31 in Figure 7 and evaluation value D41 in Figure 8 for the production plan, and plan output data D32 in Figure 11 and evaluation value D42 in Figure 12 for the power plan.

[0052] The plan coordination support device 20 generates data D5, D6, and D7 shown in FIGS. 13 to 15 during the process through its internal processing.

[0053] Fig. 13 is an example of the filter output D5 for a power plan, in which information such as a plan ID (D5a), date and time D5b, a process ID (D5c), and power consumption D5d is organized in table format. The format of this table is the same as the plan output data D32 for the power plan in Fig. 11. According to this table, the period, process, and power consumption of the power plan that violate the constraints of the power plan are described as the filter output D5.

[0054] FIG. 14 shows an example of collaboration range data D6, which is one of the processing results of the plan collaboration support device 20. The ID of the combination of the production plan and the power plan is written as the plan ID (D6a) to be collaborated, D6b shows the period during which the production plan and the power plan cannot be achieved simultaneously as the excess range, and D6c shows the days on which simultaneous operation is possible as the collaboration range.

[0055] For example, the first line shows that the conditions for production plan 001 and power plan 001 for 2024 / 01 / 10 do not match (are in the exceeded range) for 30 minutes from 10:00. Similarly, the second line shows that the conditions for production plan 001 and power plan 002 for 2024 / 01 / 10 and 2024 / 01 / 11 do not match (are in the exceeded range) for 30 minutes from 10:00 on 2024 / 01 / 10 and 30 minutes from 11:30 on 2024 / 01 / 11.

[0056] 15 shows an example of targeting output data D7, which is one of the processing results of the plan coordination support device 20, with D7a describing the plan ID of the production plan, D7b showing the production date, D7c showing the product ID, and D7d showing the production volume. The information in Fig. 15 presents the plan ID, production date, and product ID as information for correcting the production plan when the production plan cannot comply with the constraints of the power plan if it remains the initial plan, and is intended to determine the production volume for each individual period by formulating a new production plan.

[0057] The overall flow of the plan collaboration support system for obtaining output data from the various input data described above is shown as a flow diagram in Figure 16. This shows the overall flow of the plan formulation device 10 and the plan collaboration support device 20. In this flow, processing step S100a declares that the plans to be collaborated will be revised. In this example, for example, what should be focused on in the production plan and power plan is defined. Note that processing step S100a is paired with processing step S100b, and the intervening processing steps S200, S300, S400, and S500 are repeatedly executed until all processing for the initially defined production plan and power plan is completed.

[0058] In processing step S200 of Figure 16, the planning process shown in detail in Figure 17 is executed, in S300 the filtering process shown in detail in Figures 18A and 18B is executed, in S400 the targeting process shown in detail in Figures 19A and 19B is executed, and in S500 the planning input of the partner is updated.

[0059] In the first stage of the overall flow in Fig. 16, planning is performed by the planning device 10, the details of which are shown in Fig. 17 (processing step S200 in Fig. 16). Specifically, in the first processing step S201a in Fig. 17, all processing steps S202, S203, S204, and S205 between processing step S201a and processing step S201b are executed as a repetitive process until all plans are completed. Note that, in this case, the production plan is handled first, followed by the power plan.

[0060] Next, in processing step S202, it is determined whether the master information D11, D12 or the plan of the linked process (planned data D12, D22) has been updated, and if there is no change, no new planning is performed, but if there is a change, the process proceeds to processing step S203 and planning is performed. Thereby, in processing step S202, the startup timing (planning timing) of the planning device 10 is determined.

[0061] This is because the planning period differs for each process and the planning cycle differs for each process, so in this invention, the planning timing is set to when one of the following conditions is met: when the plan of the linked process (planned data D12, D22) is updated, or when the master information D11, D12 of the plan (e.g., production demand, electricity market price) is updated, and the plan for the updated range is output every time the input is updated.

[0062] Generally, plans are formulated on a large scale from a long-term or medium-term perspective, but by reviewing the plan triggered by changes to the above input data (D11, D12, D21, D22), it becomes possible to apply the plan to relatively recent, small-scale changes.

[0063] 17, if the conditions for planning are met, then in processing step S203, planning processing is performed to obtain plan output data D31 and D32, in processing step S204, plan evaluation is performed to obtain evaluation value data D41 and D42, and in processing step S205, post-planning outputs D31, D32, D41, and D42 are output to the plan collaboration support device 20. Here, the present invention is characterized mainly in the plan collaboration support device 20, and the specific processing in the plan planning device 10 may be that of an existing method. For this reason, a detailed description of the planning processing will be omitted.

[0064] Furthermore, by determining the timing of planning based on whether the master information D11, D12 or the plan of the linked process (planned data D12, D22) has been updated, it is possible to reduce the frequency of planning cycles and shorten the processing time, thereby achieving the effect of optimizing the response of the entire linked processing.

[0065] Fig. 18A is a diagram showing detailed processing contents of the filter processing in processing step S300 in Fig. 16. In the filter processing, first, in processing step S301, the planned output (in the case of a production plan, the planned output D31 in Fig. 7, and in the case of a power plan, the planned output D32 in Fig. 11) is saved as a plan cache in the plan cache storage area 21A in the storage unit 21 in Fig. 2. At this time, evaluation value data D41 and D42 are also saved. Hereinafter, the evaluation value may be simply referred to as KPI.

[0066] Next, in processing step S302, thresholds for the planned outputs D31 and D32 are determined by the process shown in detail in Fig. 18B. In processing step S303, it is determined whether the KPIs (D41, D42) of the planned outputs D31 and D32 exceed the thresholds.

[0067] If the threshold is exceeded (Yes in processing step S303), the process proceeds to processing step S304, where the planned output (planned output D31 in FIG. 7 for a production plan, or planned output D32 in FIG. 11 for a power plan) is output as the plan cache. If the threshold is not exceeded (No in processing step S303), the process proceeds to processing step S305, where empty (0) is output as the plan cache.

[0068] Here, the evaluation value is calculated as shown in Figure 18B. Figure 18B shows an example of a threshold determination method, but thresholds can be set for other cases as well. In this example, first, in processing step S302a, the Pareto front is calculated from the input plan cache.

[0069] FIG. 21 is a diagram for explaining the concept of the threshold determination method. Here, for example, a two-dimensional plane is assumed with the production plan evaluation value KPI1 and the power plan evaluation value KPI2, and the input cache evaluation values ​​of past planning data are plotted on this KPI plane. The smaller the evaluation value, the more favorable it is. Each plotted point exists within a certain area, but since this area contains a distribution that includes both favorable and unfavorable evaluation values, a Pareto front calculated simply from past planning data will look like a curve L1, for example, that includes the majority of these. The Pareto front calculated in processing step S302a corresponds to this curve L1.

[0070] In processing step S302b, a curve L2 is calculated that is a distance d away from the Pareto front. The direction of the distance d is set to the side where the majority exists. In processing step S302c, each point on the curve L2 is set to a threshold value.

[0071] The determination in processing step S303 distinguishes (filters) between outside and inside threshold L2 in Fig. 21. If it is inside (below the threshold), it means that the plan is in a good operating range and operation is possible as is, and if it is outside (above the threshold), it means that the plan is in a bad operating range and operation as is is inappropriate. Therefore, when it is below the threshold, there is no need to change the plan and operation as is is acceptable, but when it is above the threshold, some kind of change to the plan is necessary and operation as is is not acceptable.

[0072] In other words, if the value is below the threshold, it can be left as is and no correction is required, so it will not be used in subsequent processing (the data is set to 0 in processing step S305d). If the value is above the threshold, it is necessary to either change this plan or change another plan to ensure that it is below the threshold, and in either case, the data at this time should be saved as a subject for consideration when making corrections (Yes in processing step S303, output as plan cache). Note that changing this plan or changing another plan means linking the plans.

[0073] These processes are executed sequentially for each evaluation value D41, D42 of the imported plan (for example, power plan 001 and power plan 002 for power plans). For example, power plan 001 in the first line of Figure 12 has an evaluation value of 1300, which is below the threshold value (for example, 1500), so it is not output as a plan cache (0 output), but power plan 002 in the second line of Figure 12 has an evaluation value of 2000, which is above the threshold value (for example, 1500), so it is output as a plan cache.

[0074] According to the processing in Fig. 18A, for each plan ID, the KPI for this ID is monitored to classify (filter) plans into adoptable and unadoptable plans. Note that, according to the data structure in Fig. 12, the KPI is calculated for each power plan, but by calculating an evaluation value for each power plan classified by process or date and time information, filtering by process and date and time becomes possible.

[0075] Here, to summarise the filtering function of FIG. 18A, the filter function section function slows down and suppresses high frequency planning cycles, which has the effect of reducing the frequency of planning cycles for the entire device.

[0076] Looking at this operational logic, the filter function unit determines whether to perform plan linkage depending on the contents of the plan output. If plan linkage is not performed, the plan output is saved as a plan cache, and if the plan cache is not empty, it is accumulated, but the filter output is set to empty (filtered). If plan linkage is performed, the plan output is saved as a plan cache, and if the plan cache is not empty, it is accumulated, but the filter output is set to the plan cache (not filtered), and the plan cache is reset to empty.

[0077] The condition for determining whether or not to perform plan coordination is that if the KPI of the plan output is equal to or greater than a threshold, it is determined that plan coordination is to be performed, and if it is less than the threshold, it is determined that plan coordination is not to be performed.

[0078] Furthermore, to summarize the threshold setting process in FIG. 18B, in this invention, as shown in FIG. 21, a parameter d input by the user is given, and the threshold is set to a curve L2 that is a distance d away from the Pareto front L1 calculated from past planning data. Curve L2 can be interpreted as a curve that "weakens Pareto optimality by the distance d." This allows for filtering decisions that take into account the optimality of multiple KPIs. For example, when KPI1 is 10, the threshold for KPI2 is 20, and when KPI1 is 20, the threshold for KPI2 is 10. This allows for filtering that takes multiple KPI values ​​into account.

[0079] If the present invention is not adopted, the limit value for revising the plan if the KPI worsens beyond that value is used as the threshold for filtering. As a result, the trade-off relationship between KPIs cannot be taken into consideration, and plan linkage becomes more frequent, reducing the effectiveness of the filtering function. For example, because KPI1 and KPI2 are in a trade-off relationship, if KPI1 is 10, KPI2 cannot be made smaller than 20. However, setting the threshold for KPI2 to 10 results in a situation where plan linkage becomes more frequent.

[0080] Regarding filter judgment, it is easiest to understand and highly feasible to explain it using a threshold, but it does not necessarily have to be a threshold judgment; for example, you could make a threshold judgment on the rate of change of the KPI rather than the KPI itself, look at the magnitude relationship with other indicators, or use a labeled evaluation. Generally, it is sufficient to be able to distinguish between when the KPI meets a certain condition and when it does not. A threshold is just one specific method.

[0081] Next, a specific processing example of the plan collaboration support device shown in Figures 18A and 18B will be described. Here, first, the production plan and power plan for the same day and time are focused on, and it is determined that the KPI of the power plan at the date and time when the production plan was executed exceeds its threshold, and only the information on the power plan for the period in which the threshold was exceeded is extracted as filter output data D5.

[0082] In other words, as a result of employing the filtering function in Figure 18A, data that has been determined to require plan coordination as a result of determining whether the KPI threshold has been exceeded is extracted as filter output data D5. In the example of the power plan in Figure 13, it was determined that coordination was required for process A and process B for 30 minutes from 10:00 on 2024 / 01 / 10 in power plan 001. When compared with data D32 in Figure 11, which is the previous power plan output, it can be seen that there were no KPI problems with operations during other time periods, and that only this period was extracted as the target for coordination.

[0083] Fig. 19A shows detailed procedures for the targeting process (processing step S400) in the overall process of Fig. 16. In this process, first, the filter output data D5 of Fig. 13, which is the output of the filtering function, is input, and it is determined whether this input is 0. If it is 0, the process proceeds to processing step S408, where 0 is output. If significant filter output data D5 exists, the process from processing step S402 onwards is executed. Note that processing step S402 is a repetitive process between processing step S405, and each period is extracted for the input filter output data D5. Note that the viewpoint of extraction may be equipment (process in the illustrated example) in addition to the period.

[0084] When the filter output data D5 is a power plan, extracting the period involves extracting the date and time, and first extracting information on the 30-minute period for process A from 10:00 on 2024 / 01 / 10 from the first row, and at the next processing opportunity, extracting information on the 30-minute period for process B from 10:00 on 2024 / 01 / 10 from the second row.

[0085] In processing step S403, it is determined whether the KPI for each period exceeds the threshold, and if a period that exceeds the threshold is extracted, this period is set as the exceedance range in processing step S404. If the KPI for the information on the period of process A for 30 minutes from 10:00 on 2024 / 01 / 10 in the first row exceeds the threshold, the 30 minutes from 10:00 on 2024 / 01 / 10 is set as the exceedance range.

[0086] When all the filter output data D5 has been checked from the viewpoint of the period and the equipment, the range of cooperation is determined in processing step S406, and the plan output narrowed down to the range of cooperation is output in processing step S407.

[0087] The cooperation range data D6 in FIG. 10 and the targeting data D7 in FIG. 11 reflect these processes, and the specific processing methods will be described below.

[0088] The targeting function outlined above limits the scope of collaboration to specific periods and specific targets where collaboration is most effective, thereby achieving the effect of shortening the processing time of the entire device.

[0089] The operating logic here is that if the filter output is empty, the targeting output is set to empty (no planning collaboration), and if the filter output is not empty, the following action is taken. First, a period or target where the fluctuations are large is identified as the period in which the KPI of the filter output is fluctuating (this is called the "excess range"). Then a period or target where the collaboration effect is high, corresponding to the excess range, is identified (this is called the "collaboration range"). Then the planning output limited to the collaboration range is set as the targeting output.

[0090] 22 and 23 are examples showing the results of targeting processing, with Fig. 22 showing a case where the period (date and time) is limited, and Fig. 23 showing a case where the target (process) is limited. Here, the criteria for determining whether to link plans is that if the KPI of the plan output is equal to or greater than the threshold, it is determined to link plans, and if it is less than the threshold, it is determined not to link plans.

[0091] Figure 22 shows an example of a case where you want to reduce power consumption during the late night hours, with the late night hours being used as the excess range (range of planned output) and the equipment operating during the late night hours being used as the coordination range. Figure 23 shows an example of a case where you want to reduce inventory for a specified month, with the specified month being used as the excess range (range of planned output) and the equipment producing products with delivery dates within the specified month being used as the coordination range. In this example, the planned output needs to be reviewed for the range where the KPI for planned output is above the threshold, and the content of the plan review is the coordination range.

[0092] In the case of a production plan and a power plan, this can be said to determine the scope and content of the revision of the production plan that can comply with the power system when the production plan violates the constraints of the power plan. Depending on the targeting processing results, it will instruct that the production plan should be revised again in accordance with the period, process, and processing content in accordance with this output.

[0093] To explain in more detail how to determine the range of collaboration, we want to determine a range of collaboration that will optimize excessive KPIs with as few collaborations as possible. For example, optimizing the KPI of equipment A can sometimes cause the KPI of equipment B to exceed the limit, resulting in a whack-a-mole situation, so determining the range of collaboration is generally difficult. For this reason, in this invention, we believe that if the range of collaboration is set wide enough, it should be possible to optimize the KPIs within that range, so we gradually expand the range of collaboration until the KPIs fall within the appropriate range.

[0094] Here, we will explain specific examples and operational considerations for gradually expanding the collaboration range. First, if the range identified as a candidate for the collaboration range is a first range, and the KPI does not meet the criteria within the first range, the collaboration range is expanded. In the expansion process, a range of a predetermined unit related to the first range is determined as the expanded range. Examples of "related to the first range" include a relationship based on the characteristics of the process (upstream / downstream of the process, related equipment, etc.) or a continuous period, and the user may set this appropriately depending on the target. The predetermined unit may be determined based on the size of the first range or the category of the range to be expanded. For example, if the first range is one day, the expanded range may be one day before and one day after. Then, the above-mentioned plan collaboration process is performed again within the second range, which is the combination of the first range and the expanded range. Then, it is determined whether the KPI satisfies the condition. This process is repeated until the KPI satisfies the condition.

[0095] Taking the example of Figure 22 where it is desired to reduce power consumption during the late night hours, in the first coordination, the excess range of power consumption during the late night hours and the operation process during the late night hours (processes include equipment and work; the following explanation will use the example of operating equipment) are the coordination range, in the second coordination, the excess range of power consumption at 8 o'clock and the operation equipment during the late night hours and the operation equipment at 8 o'clock are the coordination range, in the third coordination, the excess range of power consumption at 12 o'clock and the operation equipment during the late night hours, the operation equipment at 8 o'clock and the operation equipment at 12 o'clock are the coordination range, and in the fourth coordination, the excess range is eliminated and a situation can be created where no coordination is required.

[0096] To explain the situation in which you want to reduce the inventory quantity for a specified month in the example in Figure 23, in the first linkage, the excess range for December inventory and the linked range is the equipment that produces products with a delivery date in December, and in the second linkage, the excess range for December and August inventory and the linked range is the equipment that produces products with delivery dates in December, November, and August, and by changing this, you can reduce the inventory quantity for the specified month.

[0097] Figure 20 is a diagram showing an example of a display screen when the processing results of the plan coordination support device are displayed on the display unit 25. The upper part of Figure 20 displays the plan name, the name of the plan to be coordinated, the necessity of plan coordination, the scope of coordination, etc., along with the execution date and time, and the lower part displays the execution contents in chronological order or by process.

[0098] 24 is a diagram showing a schematic diagram of a series of processing steps according to the present invention. Here, the planning device 10 creates a production plan and a power plan separately. The production plan is, for example, a calculation of the production volume for each process as of January 10, 2024, while the power plan shows the amount of power consumed by date and time as of the same date and time as of January 10, 2024.

[0099] In the plan coordination support device 20, a comparison of the production plan and the power plan shows that the power consumption threshold was exceeded for process A between 10:00 and 10:30 on 2024 / 01 / 10, and so the filter function determines that plan coordination for this period is necessary. Furthermore, the targeting function extracts the production plan for process A on 2024 / 01 / 10 as the coordination range and makes it the target for correction.

[0100] Thereafter, the cooperation range is passed to the production planning device 10, and the production plan is revised to one that can comply with the constraints on the amount of power consumption on the power plan side.

[0101] The plan coordination support device according to the present invention described above in relation to the embodiments is essentially configured as "a plan coordination support device capable of executing processing to link a plurality of plans having mutually different contents output by one or more planning devices, wherein the output of the planning devices includes a time-series plan output and an index related to a KPI of the plan output, and the plan coordination support device is characterized in that it has a filter function unit that determines to perform plan coordination if the KPI satisfies a predetermined condition, and not to perform plan coordination if the KPI does not satisfy the predetermined condition."

[0102] Regarding KPI indicators, in principle, the KPI output by the planning device can be used for filter judgment, but it is also possible for the collaboration support device to calculate the KPI to be used for filtering based on the information output by the planning device. One example is calculating an evaluation value that is appropriate for the filter function, or converting it into an evaluation value that can be compared between different plans. Therefore, the KPI may or may not be the same as the one used for filter function judgment.

[0103] In the examples, it has been explained that "the plan coordination support device is equipped with a filter function unit that compares the KPI with a threshold value and determines that plan coordination will be performed if the KPI exceeds the threshold value, and that plan coordination will not be performed if the KPI does not exceed the threshold value," but in a broader sense, or more generally, this can be said to mean that "the plan coordination support device is equipped with a filter function unit that determines that plan coordination will be performed if the KPI satisfies specified conditions, and that plan coordination will not be performed if the KPI does not satisfy the specified conditions." [Explanation of symbols]

[0104] 10: Planning device 11: Storage part 11A: Planning input information storage area 11B: Plan output information storage area 11-1: Auxiliary storage device 11-2: Memory 12 Processing section 12A: Plan input update detection unit 12B: Planning Department 12C: Planning and Evaluation Department 13: Input / output section 14: Communications Department 15: Bus 21: Storage section 21A: Plan cache storage area 21B: Link range storage area 22: Processing section 22A: Filter function section 22B: Targeting function section 23: Input / output section 24: Communications Department 25: Display section 26: Bus 50: Connection

Claims

1. A plan coordination support device capable of executing a process of coordinating multiple plans having different contents output by one or more plan formulation devices, the output of the planning device includes a time-series plan output and an index related to a KPI of the plan output; The plan coordination support device is characterized by having a filter function unit that determines to perform plan coordination if the KPI satisfies a predetermined condition, and not to perform plan coordination if the KPI does not satisfy the predetermined condition.

2. The plan coordination support device according to claim 1, A planning collaboration support device characterized in that the specified condition is a line that is a distance d away from the Pareto front when KPIs are plotted using past planning data within an area determined by multiple KPIs.

3. The plan coordination support device according to claim 1, A plan collaboration support device characterized in that the filter function unit is provided with a targeting function unit that, when plan collaboration is to be carried out, limits the scope of collaboration to a specific period and specific target for which collaboration is highly effective.

4. The plan coordination support device according to claim 3, The targeting function unit identifies the period or target process in which the KPI fluctuates as an excess range, and identifies the period or target process in which the collaboration effect is high corresponding to the excess range as a collaboration range.

5. The plan coordination support device according to claim 4, The plan coordination support device is characterized in that the coordination range is expanded in stages until the KPI falls within an appropriate range.

6. A plan coordination support system including one or more planning devices that create plans with different contents from each other, and a plan coordination support device that can execute a process for linking a plurality of plans from the planning devices, the output of the planning device includes a time-series plan output and an index related to a KPI of the plan output; The plan coordination support system is characterized in that the plan coordination support device is equipped with a filter function unit that determines to perform plan coordination if the KPI satisfies specified conditions, and not to perform plan coordination if the KPI does not satisfy the specified conditions.

7. The plan coordination support system according to claim 6, A plan collaboration support system characterized in that the filter function unit of the plan collaboration support device is provided with a targeting function unit that, when plan collaboration is performed, limits the scope of collaboration to a specific period and specific target where collaboration is most effective.

8. The plan coordination support system according to claim 6, The planning device stores input data for planning, and when there is a change in the input data, re-executes planning for at least the changed portion of the data.

9. A plan coordination support method capable of executing a process of coordinating multiple plans having different contents output by one or more planning devices using a computer, comprising: The plan includes time-series plan outputs and indicators related to the KPIs of the plan outputs, A plan coordination support method characterized in that a computer determines that plan coordination will be performed if the KPI satisfies a predetermined condition, and that plan coordination will not be performed if the KPI does not satisfy the predetermined condition.

10. The plan coordination support method according to claim 9, When determining the plan coordination between a first plan and a second plan including a constraint condition of the first plan, a plan coordination support method for determining that the first plan and the second plan should be coordinated with respect to a part of the first plan that violates a constraint condition of the second plan at that time, and instructing the re-planning of at least the part of the first plan that corresponds to the violation of the constraint condition.

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