Work plan creation system, work plan creation method, and program

Abstract

To provide a work plan creation system capable of reducing the workload of a user when creating a more suitable work plan.SOLUTION: A work plan creation system 100 comprises: a control device 1 that creates a work plan by arranging a plurality of work blocks assigned with work in an execution order, and accepts a modification of the arrangement of the plurality of work blocks by a user in the created work plan; and a cloud 6 that performs machine learning on the basis of the accepted modification of the arrangement of the plurality of work blocks by the user and acquires a learning result. The control device 1 creates a work plan by adjusting the arrangement of the plurality of work blocks on the basis of the learning result acquired by the cloud 6.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present invention relates to a work plan creation system, a work plan creation method, and a program. [Background technology]

[0002] BACKGROUND ART Conventionally, a work plan creation system is known (see, for example, Patent Document 1).

[0003] The above-mentioned Patent Document 1 describes a logistics planning system (work planning system) that includes a computer that creates a logistics plan for transporting cargo based on information including information on the destination of the cargo and information on the vehicle that will transport the cargo. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2007-119099 Summary of the Invention [Problem to be solved by the invention]

[0005] Although not described in Patent Document 1, there are cases where a user adjusts a work plan created by a computer by rearranging tasks at their discretion in order to make the work plan more suitable. For this reason, conventional work plan creation systems have the problem that it is difficult to reduce the workload of the user in order to create a more suitable work plan.

[0006] The present invention has been made to solve the above-mentioned problems, and one object of the present invention is to provide a work plan creation system, a work plan creation method, and a program that can reduce the workload of a user when creating a more appropriate work plan. [Means for solving the problem]

[0007] In order to achieve the above object, a work plan creation system for item placement according to a first aspect of the present invention comprises a work planning unit that creates a work plan by arranging multiple work blocks to which work is assigned in the order in which they are to be performed, a correction receiving unit that accepts user corrections to the arrangement of the multiple work blocks in the work plan created by the work planning unit, and a machine learning unit that performs machine learning based on the user corrections to the arrangement of the multiple work blocks accepted by the correction receiving unit and acquires learning results, and the work planning unit creates a work plan by adjusting the arrangement of the multiple work blocks based on the learning results acquired by the machine learning unit.

[0008] In the work plan creation system according to the first aspect of the present invention, as described above, the work planning unit creates a work plan by adjusting the arrangement of multiple work blocks based on the learning results acquired by the machine learning unit. This allows the work planning unit to create a work plan that reflects the user's intentions based on the learning results of machine learning of the user's modifications. As a result, the workload of the user modifying the work plan can be reduced, thereby reducing the workload of the user when creating a more suitable work plan.

[0009] In the work plan creation system according to the first aspect, preferably, the modification receiving unit receives a selection of whether or not to use the received user modifications to the arrangement of the plurality of work blocks for machine learning by the machine learning unit, and the machine learning unit performs machine learning using the user modifications to the arrangement of the plurality of work blocks selected for use in machine learning. This configuration allows modifications that the user wants to continue to reflect to be learned by machine learning, and also makes it possible to prevent temporarily applied modifications from being reflected. This makes it possible to easily create a more suitable work plan based on the learning results obtained by machine learning.

[0010] In the work plan creation system according to the first aspect, the machine learning unit preferably performs machine learning based on modifications to the arrangement of the work blocks for each user, and acquires learning results for each user. With this configuration, it is possible to acquire learning results that reflect modifications appropriate for each user, making it possible to easily create work plans appropriate for each user. It is possible.

[0011] A work plan creation method according to a second aspect of the present invention creates a work plan by arranging multiple work blocks to which work is assigned in the order in which they are to be executed, allows a user to modify the arrangement of the multiple work blocks in the created work plan, performs machine learning based on the user's modifications to the arrangement of the multiple work blocks, obtains learning results, and creates a work plan by adjusting the arrangement of the multiple work blocks based on the obtained learning results.

[0012] In a work plan creation method according to a second aspect of the present invention, a work plan is created by adjusting the arrangement of multiple work blocks based on the acquired learning results. This makes it possible to create a work plan that reflects the user's intentions based on the learning results obtained by machine learning of the user's modifications. As a result, the workload of the user modifying the work plan can be reduced, thereby reducing the workload of the user when creating a more appropriate work plan.

[0013] A program according to a third aspect of the present invention causes a computer to execute the work plan creation method according to the second aspect.

[0014] A program according to a third aspect of the present invention can be provided that causes a computer to execute the work plan creation method according to the second aspect, thereby reducing the workload of a user when creating a more appropriate work plan. [Effects of the Invention]

[0015] According to the present invention, as described above, it is possible to reduce the workload on the user when creating a more suitable work plan. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a block diagram illustrating an example of the configuration of a work plan creation system according to an embodiment. [Figure 2] FIG. 1 is a diagram for explaining creation of a work plan by a work plan creation system according to an embodiment. [Figure 3] FIG. 10 is a diagram for explaining machine learning of work plan correction by a work plan creation system according to an embodiment. [Figure 4] 1 is a flowchart illustrating a work planning process performed by a work planning system according to an embodiment. [Figure 5] 1 is a flowchart illustrating machine learning performed by a work plan creation system according to an embodiment. [Figure 6] 10 is a flowchart illustrating a work planning process using a learning result by the work planning system according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0017] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, specific embodiments of the present invention will be described with reference to the accompanying drawings.

[0018] A work plan creation system 100 according to one embodiment will be described with reference to FIGS.

[0019] The work plan creation system 100 according to this embodiment creates, for example, a vehicle allocation plan for logistics as a work plan. Specifically, the work plan creation system 100 creates a vehicle allocation plan including the destinations and order of movement of each transport vehicle when transporting cargo by using multiple transport vehicles (trucks) to sequentially move between loading and unloading positions.

[0020] (Device configuration example) The work plan creation method using the work plan creation system 100 according to this embodiment can be implemented by having a control device 1 (computer) execute a program 3a. As shown in FIG. 1, the work plan creation system 100 includes a control device 1. The control device 1 is configured to be able to execute the program 3a. Note that some or all of the processing performed by having the control device 1 execute the program 3a may be performed by hardware such as a dedicated arithmetic circuit. The control device 1 is an example of the "work planning unit," "correction receiving unit," and "computer" in the claims.

[0021] 1, the control device 1 includes one or more processors 2 each including a central processing unit (CPU) or the like, and a storage unit 3 including a read-only memory (ROM), a random access memory (RAM), and a storage device such as a hard disk drive or a semiconductor storage device.

[0022] The control device 1 can create a work plan by causing the processor 2 to execute a program 3a stored in the storage unit 3. The program 3a may be read from a recording medium or may be provided from an external server or the like via a transmission path such as a network such as the Internet or a LAN (Local Area Network).

[0023] The control device 1 also includes a display unit 4 such as a liquid crystal display device, and an input unit 5 including input devices such as a keyboard and a mouse.

[0024] The work plan creation method may also be executed on a cloud 6 of a network. Specifically, part or all of the processing of the work plan creation method may be performed by an external server connected via a network. For example, machine learning in the work plan creation method is executed in the cloud 6. The cloud 6 includes one or more computers connected to the network. The processing by the cloud 6 is executed by one or more computers on the network. The cloud 6 is an example of a "machine learning unit" in the claims.

[0025] (Work plan creation method) Next, a description will be given of a method for creating a work plan by the control device 1. In this embodiment, the method for creating a work plan is performed by sequentially arranging a plurality of work blocks to which work is assigned.

[0026] Specifically, the control device 1 creates a work plan by arranging multiple work blocks, to which work is assigned, in the order in which they will be performed. In this embodiment, a vehicle dispatch plan for loading and unloading locations for each truck is created. In this case, the work block includes the loading and unloading locations for the luggage. As shown in FIG. 2, the control device 1 creates a work plan by determining the movement route for each truck based on the luggage transport schedule for that day.

[0027] The control device 1 also accepts user modifications to the arrangement of multiple work blocks in the created primary work plan. While viewing the created primary work plan, the user modifies the primary work plan to create a more efficient work plan. For example, the user modifies the work plan so that a truck appropriate for the cargo loading and unloading location goes to a specific loading and unloading location (store). The user also modifies the work plan so that the specific loading and unloading location (store) is reached within a specified time.

[0028] Here, in this embodiment, the cloud 6 performs machine learning based on user modifications to the arrangement of multiple task blocks received by the control device 1, and acquires learning results. In other words, the work plan creation system 100 performs machine learning of the user modifications using the cloud 6, and acquires learning results so that the user modifications are reflected in the creation of subsequent work plans. As shown in Fig. 3, the cloud 6 performs machine learning using the primary work plan as input data and the modified work plan as output training data.

[0029] Furthermore, the control device 1 adjusts the arrangement of a plurality of task blocks based on the learning results acquired from the cloud 6 to create a task plan.

[0030] The control device 1 also accepts a selection as to whether or not the accepted user modifications to the arrangement of the plurality of work blocks are to be used for machine learning by the cloud 6. For example, when accepting a user modification to the arrangement of the plurality of work blocks, the control device 1 also accepts a selection as to whether or not the modifications are to be used for machine learning. In this case, if the modifications are not to be used for machine learning, the selection may be accepted using a checkbox or the like. The selection as to whether or not to use for machine learning may also be accepted using a pull-down box.

[0031] Cloud 6 also performs machine learning using user modifications of the arrangement of multiple working blocks selected for use in machine learning.

[0032] Furthermore, the cloud 6 performs machine learning based on modifications to the arrangement of the work blocks for each user, and obtains learning results for each user. For example, the cloud 6 performs machine learning based on modifications for each user U1 and U2, and obtains learning results G1 and G2. The cloud 6 also performs machine learning based on modifications for all users, and obtains learning result Ga.

[0033] The control device 1 accepts a selection of whether or not to use the learning results to create a work plan. Furthermore, when creating a work plan using the learning results, if the control device 1 has acquired multiple learning results, the control device 1 accepts a selection of which learning result to use to create the work plan. The control device 1 may automatically select a learning result corresponding to the user performing the operation and use it in the work plan.

[0034] (Work plan creation process) With reference to FIG. 4, the work planning process performed by the work planning system 100 before the learning results are acquired will be described.

[0035] 4, the control device 1 of the work plan creation system 100 acquires a plurality of work blocks in step S1. In step S2, the control device 1 acquires work conditions.

[0036] In step S3, the control device 1 arranges a plurality of task blocks to create a primary task plan, and in step S4, the control device 1 accepts user modifications to the primary task plan.

[0037] In step S5, the control device 1 accepts a selection of whether or not to use the user's modifications accepted in step S4 for machine learning. In step S6, the control device 1 presents a revised work plan in which the user's modifications accepted in step S4 are reflected in the primary work plan.

[0038] (machine learning processing) The machine learning process performed by the work plan creation system 100 will be described with reference to FIG.

[0039] 5, the cloud 6 of the work plan creation system 100 acquires the primary work plan and the revised work plan created by the control device 1. In step S12, the cloud 6 executes machine learning based on the primary work plan and the revised work plan. In step S13, the cloud 6 acquires the learning results from the machine learning.

[0040] (Work plan creation process using learning results) With reference to FIG. 6, the work planning process using the learning results by the work planning system 100 will be described.

[0041] 6, the control device 1 of the work plan creation system 100 acquires a plurality of work blocks in step S21. In step S22, the control device 1 acquires work conditions.

[0042] In step S23, the control device 1 uses the learning results to arrange a plurality of task blocks and create a task plan. That is, the control device 1 uses the learning results to create a task plan that reflects the user's modifications.

[0043] In step S24, the control device 1 presents a work plan.

[0044] (Effects of this embodiment) The effects of this embodiment will be described.

[0045] As described above, in this embodiment, the control device 1 creates a work plan by adjusting the arrangement of multiple task blocks based on the learning results acquired from the cloud 6. This allows the control device 1 to create a work plan that reflects the user's intentions based on the learning results of machine learning of the user's modifications. As a result, the workload of the user of the control device 1 for modifications can be reduced, thereby reducing the workload of the user when creating a more suitable work plan.

[0046] Furthermore, in this embodiment, the control device 1 accepts a selection of whether or not to use the accepted user modifications to the arrangement of the multiple work blocks for machine learning by the cloud 6. The cloud 6 performs machine learning using the user modifications to the arrangement of the multiple work blocks selected for use in machine learning. This allows the machine learning to learn modifications that the user wants to reflect in the future, and also makes it possible to prevent temporarily applied modifications from being reflected. This makes it possible to easily create a more appropriate work plan based on the learning results obtained by machine learning.

[0047] In this embodiment, the cloud 6 performs machine learning based on modifications to the arrangement of task blocks for each user, and acquires learning results for each user. This allows acquisition of learning results that reflect modifications appropriate for each user, making it possible to easily create a task plan appropriate for each user.

[0048] (Variation) The embodiments disclosed herein should be considered to be illustrative and not restrictive in all respects. The scope of the present invention is defined by the claims rather than the above description of the embodiments, and further includes all modifications (variations) within the meaning and scope of the claims.

[0049] For example, in the above embodiment, an example of a configuration in which a vehicle allocation plan for logistics is made as a work plan is shown, but the present invention is not limited to this. In the present invention, a production plan for producing an item may be made as a work plan. For example, in the production plan, work blocks may be allocated for each type of item to be produced, each process for producing the item, etc.

[0050] In the above embodiment, an example of a configuration in which machine learning is performed by a cloud on a network is shown, but the present invention is not limited to this. In the present invention, machine learning may be performed by a terminal (computer) on the user side.

[0051] In the above embodiment, an example of a configuration in which the process of creating a work plan is performed by a user terminal (computer) is shown, but the present invention is not limited to this. In the present invention, the process of creating a work plan may be performed by a cloud on a network. [Explanation of symbols]

[0052] 1. Control device (work planning section, correction reception section, computer) 3a Program 6 Cloud (Machine Learning Department) 100 Work Planning System

Claims

1. a work planning unit that arranges the multiple work blocks to which work is assigned in an order in which they will be executed to create a work plan; a modification receiving unit that receives a modification by a user of the arrangement of the plurality of work blocks in the work plan created by the work planning unit; a machine learning unit that performs machine learning based on the user's modifications to the arrangement of the plurality of work blocks received by the modification receiving unit, and acquires a learning result; A work plan creation system in which the work planning unit creates the work plan by adjusting the arrangement of the multiple work blocks based on the learning results obtained by the machine learning unit.

2. the modification receiving unit receives a selection of whether or not the received modification by the user to the arrangement of the plurality of working blocks is to be used in machine learning by the machine learning unit; The work plan creation system according to claim 1 , wherein the machine learning unit performs machine learning using a user modification of the arrangement of the plurality of work blocks selected for use in machine learning.

3. The work plan creation system according to claim 1 , wherein the machine learning unit performs machine learning based on a modification of an arrangement of work blocks for each user, and acquires the learning result for each user.

4. A work plan is created by arranging the assigned work blocks in the order in which they will be executed. In the created work plan, a user modifies the arrangement of the plurality of work blocks; performing machine learning based on a user's modification of the arrangement of the plurality of working blocks to obtain a learning result; A work plan creation method that creates the work plan by adjusting the arrangement of the plurality of work blocks based on the acquired learning results.

5. A program that causes a computer to execute the work plan creation method according to claim 4.

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