Information processing apparatus, work plan formulation method, and work plan formulation program

Abstract

To provide an information processor capable of planning a work order in a short time, a work planning method, and a work planning program.SOLUTION: The work planning program causes a computer to execute processing of: sorting multiple objects into multiple groups according to the type of constraint conditions set for each of the multiple objects regarding a work line in which works are performed on the multiple objects in order and at least some of the multiple objects have the constraint conditions on the order of performing the works; and calculating the order of performing the works for the multiple objects by the work line so that the constraint conditions set for respective objects are satisfied in each of the multiple groups.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, a work plan creation method, and a work plan creation program.

Background Art

[0002] There is a need for a technique for generating the input order of work objects to a work line by a planning algorithm (see, for example, Patent Documents 1 and 2).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] In a multi-product mixed-flow operation method, different types of products move on the work line. However, if there is a bias in the way the products flow, there is a problem that the burden on the workers becomes uneven. Therefore, in a multi-product mixed-flow operation method, it is desirable to create a work order in consideration of the constraint conditions regarding the order. However, as the constraint conditions become more complex, the time required to create the work order becomes longer.

[0005]

Means for Solving the Problems

[0006] In one aspect, the work plan creation program causes a computer to perform, for a work line in which work is sequentially performed on a plurality of objects and at least some of the plurality of objects have constraint conditions set regarding the order in which the work is performed, a process of dividing the plurality of objects into a plurality of groups according to the types of the constraint conditions set for each of the plurality of objects, and a process of calculating, in each of the plurality of groups, the order in which the plurality of objects are worked by the work line so that the constraint conditions set for each object are satisfied.

Advantages of the Invention

[0007] The work order can be established in a short time.

Brief Description of the Drawings

[0008]

Figure 1

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Figure 5

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Embodiment for Carrying Out the Invention

[0009] Prior to the description of the embodiments, an overview of the work line of the multi-variety mixed-flow operation method will be described. In the multi-variety mixed-flow operation method, different types of products are sequentially input into one work line according to a predetermined order and move sequentially on the work line. Each product will be worked on according to this predetermined order. In the example of FIG. 1, 12 products with product numbers from 001 to 012 are input into the work line with the product numbered 001 at the head. For the products from product 001 to product 012, there may be products of the same type or different types.

[0010] In the multi-variety mixed-flow operation method, the amount (lot) of working on the same type of product in one work line can be reduced, and according to the demand fluctuation, the necessary amount can be worked as much as necessary. Thereby, in a production line which is an example of a work line, the amount of wasteful inventory and intermediate products that have no value as goods can be reduced.

[0011] On the other hand, in the multi-variety mixed-flow operation method, since different types of products flow on the work line at the same time, there is a problem that if there is a bias in the flow method, there will be a bias in the burden on the workers. For example, if vehicles with sunroofs attached flow continuously on the work line, the person in charge of the sunroof will have to continue working without being able to secure a break time. In this case, ultimately, work mistakes may occur, and there is a risk of a significant impact on quality, cost, productivity, etc.

[0012] Therefore, in the multi-variety mixed-flow operation method, it is desirable to formulate the operation sequence in consideration of "constraint conditions" such as "do not place specific types of products continuously on the production line". The constraint conditions here are the constraint conditions regarding the order of each product flowing through the production line. In recent years, due to the improvement of added value, the diversification of product types has advanced, and this "constraint condition" has become complicated, making it difficult to formulate an operation sequence that adheres to diverse and complex "constraint conditions".

[0013] As a method for formulating the operation sequence of the multi-variety mixed-flow operation method considering "constraint conditions", there is a method of using a mathematical programming solver. FIG. 2 is a diagram illustrating a solution method using a mathematical programming solver. As illustrated in FIG. 2, first, mixed-flow product data is input into the mathematical programming solver. Next, the constraint conditions set for each product are input into the mathematical programming solver. Next, the mathematical programming solver optimizes by calculating the operation sequence of each product. Next, the mathematical programming solver outputs the optimization result.

[0014] This mathematical programming solver generally has the property of being able to efficiently obtain high-quality results for small-scale problems. However, when applying a mathematical programming solver to a site where operations are performed on a large number of products, such as 100 to 10,000 products per day, there is no guarantee that the result will be obtained within the realistic time (e.g., several minutes) required to calculate the formulation result. For example, there is a risk that the result cannot be obtained until the start of the operation. Also, the memory scale required for processing becomes extremely large, and there are cases where it cannot be processed by a realistic computer.

[0015] There is a method of improving the processing time by parallel processing, and parallel processing has already been implemented in commercially available mathematical programming solvers. However, it is difficult for the current mathematical programming solver to achieve the above-mentioned purpose with only a few-fold improvement in processing time. Also, although it is possible to cut off the optimization at a determined processing time, the quality of the operation sequence deteriorates, resulting in the deterioration of quality, cost, productivity, etc.

[0016] In the following embodiments, an information processing apparatus, a work plan formulation method, and a work plan formulation program that can formulate the work order of each product on the production line in a short time will be described.

Embodiment

[0017] FIG. 3(a) is a block diagram illustrating the overall configuration of the information processing apparatus 100. As illustrated in FIG. 3(a), the information processing apparatus 100 includes a product data storage unit 10, a constraint condition storage unit 20, a group creation unit 30, an order generation unit 40, an order calculation unit 50, an output unit 60, and the like.

[0018] FIG. 3(b) is a block diagram illustrating the hardware configuration of the information processing apparatus 100. As illustrated in FIG. 3(b), the information processing apparatus 100 includes a CPU 101, a RAM 102, a storage device 103, an input device 104, a display device 105, and the like.

[0019] The CPU (Central Processing Unit) 101 is a central processing unit. The CPU 101 includes one or more cores. The RAM (Random Access Memory) 102 is a volatile memory that temporarily stores programs executed by the CPU 101, data processed by the CPU 101, and the like. The storage device 103 is a non-volatile storage device. As the storage device 103, for example, a solid-state drive (SSD) such as a ROM (Read Only Memory), a flash memory, a hard disk driven by a hard disk drive, or the like can be used. The storage device 103 stores a work plan creation program. The input device 104 is an input device such as a keyboard or a mouse. The display device 105 is a display device such as an LCD (Liquid Crystal Display). By the CPU 101 executing the work plan creation program, the product data storage unit 10, the constraint condition storage unit 20, the group creation unit 30, the order generation unit 40, the order calculation unit 50, and the output unit 60 are realized. Note that, as the product data storage unit 10, the constraint condition storage unit 20, the group creation unit 30, the order generation unit 40, the order calculation unit 50, and the output unit 60, hardware such as a dedicated circuit may be used.

[0020] FIG. 4(a) is a diagram illustrating product data stored in the product data storage unit 10. The product data is stored in the product data storage unit 10 via the input device 104 or the like. As illustrated in FIG. 4(a), the product data storage unit 10 stores by associating the product number of the product being worked on the work line with the constraint condition number. The order from top to bottom represents the initial input order of each product to the work line. In the initial input order of FIG. 4(a), products from product 001 to product 012 are to be input to the work line in the order of product numbers. Among the products from product 001 to product 012, there may be products of the same type or different types. The same work is performed on products of the same type. The same constraint conditions are set for products of the same type.

[0021] FIG. 4(b) is a diagram illustrating the constraint conditions stored in the constraint condition storage unit 20. The constraint conditions are stored in the constraint condition storage unit 20 via the input device 104 or the like. As illustrated in FIG. 4(b), the constraint condition storage unit 20 stores three types of constraint conditions: operate with an interval of one or more other products (constraint condition 1), operate with an interval of two or more other products (constraint condition 2), and operate with an interval of five or more other products (constraint condition 3). For example, constraint condition 1 is provided for reasons such as not allowing continuous painting of the same color. Constraint condition 2 is provided for reasons such as the need to leave a certain interval because large vehicles take time to assemble. Constraint condition 3 is provided for reasons such as the need to leave a large interval to disperse resources because option processing such as sunroofs requires a certain number of people. As illustrated in FIG. 4(a), for each product, there may be cases where one or more constraint conditions are set, or there may be cases where no constraint condition is set.

[0022] The group creation unit 30 attaches the same label to those products among the products stored in the product data storage unit 10 that have the same type of constraint condition set. For example, for each product, the group creation unit 30 attaches labels to groups a of products for which no constraint condition is set, group b of products for which only constraint condition 1 is set, group c of products for which only constraint condition 2 is set, group d of products for which only constraint condition 3 is set, and group e of products for which constraint conditions 1 and 2 are set. In the example of FIG. 5(a), for example, product 006 and product 7 are attached with the label of group a, and product 001, product 003, product 004, and product 005 are attached with the label of group b.

[0023] Next, the group creation unit 30 calculates the ratio (appearance rate) of the number of products with each label to the total number of products stored in the product data storage unit 10. For example, since the total number of products is 12 and the number of products with the label of group a is 2, as illustrated in FIG. 5(b), the appearance rate of the number of products with the label of group a is 0.17. Since the number of products with the label of group b is 4, the appearance rate of the number of products with the label of group b is 0.33. Since the number of products with each label of groups c to e is 2, the appearance rate of the number of products with each label of groups c to e is 0.17.

[0024] Next, the group creation unit 30 divides products 001 to 012 into a plurality of groups using the calculated appearance rate so that the bias in the types of labels is reduced. For example, the group creation unit 30 divides products 001 to 012 into a plurality of groups so that the distribution of the types of labels is uniform. Since the appearance rate of the number of products with the label of group b = 0.33 is twice the appearance rate of the number of products with the labels of the other groups a, c to e = 0.17, for example, the group creation unit 30 includes 2 products with the label of group b and 1 product with the label of each of groups a, c to e in each of groups #1 and #2. Group #1 is the group that is input to the work line earlier than group #2. As an example, group #1 includes products 001, 002, 003, 006, 008, and 009. Group #2 includes products 004, 005, 007, 010, 011, and 012.

[0025] Next, the order generation unit 40 determines the order in each of Group #1 and Group #2 so that the distribution of the constraint conditions is equalized. For example, as illustrated in FIG. 6, in Group #1, the order generation unit 40 rearranges the products in the order of Product 001, Product 006, Product 002, Product 009, Product 008, and Product 003. Also, in Group #2, the order generation unit 40 rearranges the products in the order of Product 004, Product 007, Product 010, Product 012, Product 011, and Product 005. By doing so, the products belonging to Group b with only Constraint Condition 1 set are the farthest, and the products of the remaining groups are arranged between the products of Group b and the other products of Group b.

[0026] Here, let's consider the constraint conditions of each product in Group #1 and Group #2. Constraint Condition 1 is set for Product 008, Product 003, and Product 004. However, there is no other product sandwiched between Product 008 and Product 003, and there is also no other product sandwiched between Product 003 and Product 004. Therefore, the order in FIG. 6 does not satisfy Constraint Condition 1. Also, Constraint Condition 2 is set for Product 002 and Product 008. However, there are no two or more other products sandwiched between Product 002 and Product 008. Therefore, the order in FIG. 6 does not satisfy Constraint Condition 2.

[0027] Therefore, the order calculation unit 50 optimizes by calculating the order of the products using a mathematical programming solver so that each constraint condition is satisfied in each of Group #1 and Group #2.

[0028] Here, the mathematical programming solver will be explained. First, only one product is to be worked on at the j-th position (the following formula (1)). Also, Product i is to be worked on only once (the following formula (2)). x i,j means working on Product i at the j-th position. Also, x i,j is either "0" or "1".

Number

Number

[0029] Next, the condition regarding the interval is defined as in the following formula (3). In the following formula (3), "M" represents the set of interval constraints m. "C m " represents the distance of the interval to be observed by the interval constraint m. "R m " represents the set of products to which the interval constraint m is applied.

Number

[0030] FIG. 7 is a diagram illustrating optimization. In the result illustrated in FIG. 7, within each group, each of the constraint conditions (1) to (4) is satisfied. Next, the order calculation unit 50 determines whether the constraint conditions are satisfied between adjacent groups. In the example of FIG. 7, there are no more than five other products sandwiched between product 009 and product 012. Therefore, constraint condition 3 is not satisfied. Thus, the order calculation unit 50 exchanges the order of the products to other orders so that each constraint condition is satisfied even between adjacent groups. In the example of FIG. 8, the constraint conditions are satisfied even between adjacent groups. Therefore, the output unit 60 outputs the optimization result of FIG. 8. For example, the result output by the output unit 60 is displayed on the display device 105.

[0031] FIG. 9 is a diagram showing the operation of the above information processing apparatus 100 in a flowchart. As illustrated in FIG. 9, the product data storage unit 10 stores the product data input via the input device 104 or the like (step S1). The product data is the data as described in FIG. 4(a). Next, the constraint condition storage unit 20 stores the constraint conditions input via the input device 104 or the like (step S2). The constraint conditions are the conditions as described in FIG. 4(b).

[0032] Next, the group creation unit 30 refers to the product data stored in the product data storage unit 10 and attaches the same label to those with the same type of constraint condition (step S3). As a result, classification according to the type of constraint condition becomes possible. For example, as described with reference to FIG. 5(a), the group creation unit 30 attaches a label to each product.

[0033] Next, the group creation unit 30 groups each product according to the appearance rate of each group obtained in step S3 (step S4). As a result, grouping becomes possible according to the classification of the constraint conditions in step S3. For example, as described with reference to FIG. 5(b), the group creation unit 30 groups each product according to the appearance rate.

[0034] Next, the order generation unit 40 generates the input order of the products in each group so that the distribution of the constraint conditions is equalized within each group obtained in step S4 (step S5). For example, as described with reference to FIG. 6, the order generation unit 40 generates the input order.

[0035] Next, the order calculation unit 50 optimizes by calculating the order of the products so that each constraint condition is satisfied in each group (step S6). In this case, as described with reference to FIGS. 7 and 8, the order calculation unit 50 optimizes the order of the products so that the constraint conditions are also satisfied between adjacent groups.

[0036] Here, details of the method for determining the number of groups when the group creation unit 30 groups in step S4 will be described. For example, among the constraint conditions, there is a constraint such as leaving 6 intervals in between. In order to leave 6 intervals in between, as illustrated in FIG. 10(a), it is necessary to have at least 8 products in the group. However, if the number of products included in the group is 8, if there are 2 products with the constraint of leaving 6 intervals set accidentally in the group, the 2 products will be fixed at both ends. Therefore, paying attention to the maximum interval among each constraint condition, the number of products in each group is set to the maximum interval number + 2 + α (margin). The margin α is 1 or more.

[0037] Figure 10(c) is a flowchart showing an example of the process when the group creation unit 30 calculates the number of groups during grouping in step S4. As illustrated in Figure 10(c), the group creation unit 30 acquires the maximum interval L among the respective constraint conditions (step S11). Next, the group creation unit 30 sets L + 2 + α as the number D of products included in each group (step S12). Next, the group creation unit 30 sets, as the number of groups, the value obtained by dividing the total number of all products included in the product data stored in the product data storage unit 10 by the number D (step S13). It is preferable that the number of products within each group is the same, but if there is a remainder when dividing the total number of products by the number D, the remainder may be added to any one of the groups.

[0038] Next, the details of the determination method when the group creation unit 30 determines the products within the group in step S5 will be described. First, the group creation unit 30 assigns the same label to those products among all the products for which the types of set constraint conditions are the same. For example, let the set S of each label be S = {S1, S2,..., SN}. Let the number of products to which each label Si is assigned be |Si|. Let the appearance probability T of the number of products for which each label is set be T = |Si| / B. Here, "B" is the total number of products.

[0039] The group creation unit 30 sets the set T of appearance probabilities as T = {|S1| / B, |S2| / B,..., |SN| / B} (STEP1). Figure 11(a) is a diagram illustrating the appearance probability T.

[0040] Next, as illustrated in FIG. 11(b), the group creation unit 30 substitutes the appearance probability T into the cumulative appearance probability Z1 (STEP2). Next, the group creation unit 30 adds the appearance probability T to the cumulative appearance probability Z1 to calculate the cumulative appearance probability Z2, assigns the type with the largest cumulative appearance probability to the slot, and subtracts 1 from the cumulative appearance probability of that type (STEP3). In the example of FIG. 11(b), the constraint condition (1) becomes "0.66" as the maximum value, and subtracting "0.66" from 1 results in "0.34". As a result, as illustrated in FIG. 11(c), the product 001 with the constraint condition (1) set is assigned to the first slot. In the same procedure, the appearance probability T is added to the cumulative appearance probability Z3. In this case, "no constraint condition" with "0.51" becomes the maximum value, and subtracting "0.51" from 1 results in "0.49". As a result, as illustrated in FIG. 11(c), the product 006 without the constraint condition set is assigned to the second slot. The above procedure is repeated, and it ends when there are no more products to be assigned.

[0041] According to this embodiment, each product is divided into two or more groups according to the type of constraint condition set for each product. As a result, the type of constraint condition is considered during grouping. Next, within this group, the input order to the work line is calculated so that the constraint conditions set for each product are satisfied. As a result, the number of products in the group becomes less than the total number of products. From the above, since it is only necessary to calculate the input order for a small number of products within each group considering the constraint conditions, the work order of each product on the work line can be planned in a short time. For example, when using a mathematical programming solver, although an optimal solution can be calculated with high precision, there is a risk that the calculation time will become long. However, in this embodiment, since it is only necessary to calculate the work order within each group, the calculation time is short.

[0042] When calculating the input order within the group, by ensuring that the constraint conditions between adjacent groups are also satisfied, the work order of each product on the work line can be planned with higher precision.

[0043] When dividing each product into each group, attach the same label to those with the same type of constraint conditions set for each object, and divide each object into the above two or more groups so that the bias in the type of label is reduced among the above two or more groups, thereby arranging conditions closer to the optimal solution. Thereby, the time for searching for the optimal solution can be shortened.

[0044] In addition, in the above embodiment, the interval when working on the same type of product is described as a constraint condition, but it is not limited thereto. Other constraint conditions regarding the order of each product flowing on the production line can also be applied to the above embodiment.

[0045] For example, a constraint condition of "allowing up to two same-type vehicles to be lined up continuously" can be considered. This constraint condition focuses on the fact that although it is desired to alternate right-hand drive vehicles and left-hand drive vehicles, the number of right-hand drive vehicles is more than that of left-hand drive vehicles, and it is to prevent the right-hand drive vehicles from being continuously lined up more than necessary.

[0046] Or, assume that a trolley sharing parts can carry 4 parts. And assume that on that trolley, a maximum of 3 large parts can be carried, and 4 small parts can be carried. In this case, a constraint condition of "allowing up to three same-type vehicles to be lined up continuously" can be considered. In that case, if this constraint is set for the vehicle carrying large parts, the trolley will definitely be able to carry 4 parts.

[0047] Or, a constraint condition of "among 5 consecutive vehicles, only 3 same-type vehicles are allowed, and it doesn't matter whether those 3 are consecutive or not" can be considered. This constraint condition focuses on the fact that when a maximum of 3 parts for electric vehicles can always be placed on the parts shelf, it can prevent overstocking.

[0048] In each of the above examples, the product is an example of an object on which operations are performed in order on a production line. The group creation unit 30 is an example of a group creation unit that divides a plurality of objects into a plurality of groups according to the types of constraint conditions set for each of the plurality of objects. The order calculation unit 50 is an example of an order calculation unit that calculates the order of the objects so that the constraint conditions set for each object are satisfied within a group.

[0049] As described above in detail with respect to the embodiments of the present invention, the present invention is not limited to such specific embodiments, and various modifications and changes are possible within the scope of the gist of the present invention described in the claims. (Supplementary Note) (Supplementary Note 1) On a computer, Regarding a production line on which operations are sequentially performed on a plurality of objects, and at least some of the plurality of objects have constraint conditions regarding the order in which the operations are performed, a process of dividing the plurality of objects into a plurality of groups according to the types of the constraint conditions set for each of the plurality of objects, and In each of the plurality of groups, a process of calculating the order in which the plurality of objects are processed by the production line so that the constraint conditions set for each object are satisfied. A work plan creation program characterized by causing the above processes to be executed. (Supplementary Note 2) The work plan creation program according to Supplementary Note 1, wherein when calculating the order, the order is calculated so that each constraint condition between adjacent groups is also satisfied. (Supplementary Note 3) The work plan creation program according to Supplementary Note 1 or Supplementary Note 2, wherein when dividing the plurality of objects into the plurality of groups, objects having the same type of constraint condition are given the same label, and each object is divided into the plurality of groups so that the bias in the types of labels between the plurality of groups is reduced. (Supplementary Note 4) The work plan creation program according to any one of Supplementary Notes 1 to 3, wherein when calculating the order, a mathematical programming solver is used. (Supplementary Note 5) The work plan formulation program according to any one of Appendices 1 to 4, characterized in that the constraint conditions include a condition for determining the number of other objects to be interposed between two objects on which the same work is performed. (Appendix 6) Regarding a work line in which work is sequentially performed on a plurality of objects, and constraint conditions regarding the order in which the work is performed are set for at least some of the plurality of objects, according to the types of the constraint conditions set for each of the plurality of objects, the plurality of objects are divided into a plurality of groups, A work plan formulation method, characterized in that a computer executes a process of calculating an order in which the plurality of objects are worked by the work line so that the constraint conditions set for each object are satisfied in each of the plurality of groups. (Appendix 7) The work plan formulation method according to Appendix 6, characterized in that when calculating the order, the order is calculated so that each constraint condition between adjacent groups is also satisfied. (Appendix 8) The work plan formulation method according to Appendix 6 or Appendix 7, characterized in that when dividing the plurality of objects into the plurality of groups, the same label is attached to those having the same type of constraint condition, and each object is divided into the plurality of groups so that the bias of the type of label is reduced between the plurality of groups. (Appendix 9) The work plan formulation method according to any one of Appendices 6 to 8, characterized in that a mathematical programming solver is used when calculating the order. (Appendix 10) The work plan formulation method according to any one of Appendices 6 to 9, characterized in that the constraint conditions include a condition for determining the number of other objects to be interposed between two objects on which the same work is performed. (Appendix 11) For a production line where operations are performed in sequence on a plurality of objects, and at least some of the plurality of objects have constraint conditions set regarding the order in which the operations are performed, a group creation unit that divides the plurality of objects into a plurality of groups according to the types of the constraint conditions set for each of the plurality of objects, and an order calculation unit that calculates the order in which the plurality of objects are to be processed by the production line such that the constraint conditions set for each object are satisfied in each of the plurality of groups. An information processing apparatus characterized by comprising these components. (Appendix 12) The information processing apparatus according to Appendix 11, wherein when calculating the order, the order calculation unit calculates the order such that the constraint conditions between adjacent groups are also satisfied. (Appendix 13) The information processing apparatus according to either Appendix 11 or Appendix 12, wherein when dividing the plurality of objects into the plurality of groups, the group creation unit attaches the same label to those with the same type of constraint condition, and divides each object into the plurality of groups such that the bias in the types of labels between the plurality of groups is reduced. (Appendix 14) The information processing apparatus according to any one of Appendices 11 to 13, wherein when calculating the order, the order calculation unit uses a mathematical programming solver. (Appendix 15) The information processing apparatus according to any one of Appendices 11 to 14, wherein the constraint conditions include a condition that determines the number of other objects to be interposed between two objects on which the same operation is performed.

Explanation of Reference Numerals

[0050] 10 Product data storage unit 20 Constraint condition storage unit 30 Group creation unit 40 Order generation unit 50 Order calculation unit 60 Output unit 100 Information processing apparatus 101 CPU 102 RAM 103 Memory device 104 Input device 105 Display device

Claims

1. A computer, when work is sequentially performed on a plurality of objects on a work line, and at least some of the plurality of objects have a constraint condition set that determines the number of other objects to be interposed between two objects on which the same work is performed in the work order for the plurality of objects, a process of dividing the plurality of objects into a plurality of groups according to the type of the constraint condition set for each of the plurality of objects, and a process of calculating the order in which the plurality of objects are worked by the work line so that the constraint conditions set for each object are satisfied in each of the plurality of groups, are executed, wherein the process of dividing the plurality of objects into the plurality of groups is a process of dividing each object into the plurality of groups so that objects having the same type of constraint condition are labeled with the same label and the bias in the type of label is reduced between the plurality of groups. A work plan creation program characterized by this.

2. The work plan creation program according to claim 1, wherein when calculating the order, the order is calculated so that each constraint condition between adjacent groups is also satisfied.

3. The work plan creation program according to claim 1 or claim 2, wherein when calculating the order, a mathematical programming solver is used.

4. When work is sequentially performed on a plurality of objects on a work line, and at least some of the plurality of objects have a constraint condition set that determines the number of other objects to be interposed between two objects on which the same work is performed in the work order for the plurality of objects, the plurality of objects are divided into a plurality of groups according to the type of the constraint condition set for each of the plurality of objects, in each of the plurality of groups, the computer executes a process of calculating the order in which the plurality of objects are worked by the work line so that the constraint conditions set for each object are satisfied, wherein the process of dividing the plurality of objects into the plurality of groups is a process of dividing each object into the plurality of groups so that objects having the same type of constraint condition are labeled with the same label and the bias in the type of label is reduced between the plurality of groups. A work plan creation method characterized by this.

5. Operations are performed in sequence on a plurality of objects in a work line. When a constraint condition is set for at least a part of the plurality of objects to determine the number of other objects to be interposed between two objects on which the same operation is performed in the operation order for the plurality of objects, a group creation unit that divides the plurality of objects into a plurality of groups according to the type of the constraint condition set for each of the plurality of objects, In each of the plurality of groups, an order calculation unit that calculates the order in which the plurality of objects are worked on by the work line so that the constraint condition set for each object is satisfied, and The group creation unit is characterized in that when dividing the plurality of objects into the plurality of groups, the same labels are attached to those having the same type of the constraint condition, and each object is divided into the plurality of groups so that the bias in the type of labels is reduced among the plurality of groups. An information processing apparatus.

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