Information processing device and information processing method

Abstract

To determine the positions of a plurality of preparation areas on a production floor more appropriately than before. [Solution] An information processing device (1) determines the locations of multiple preparation areas for multiple types of preparation work that workers must do on a production floor before starting work to produce a product. Each of the multiple preparation areas on the production floor corresponds one-to-one to each of the multiple types of preparation work. The information processing device (1) determines the locations of each of the multiple preparation areas by performing mathematical optimization based on an objective function that corresponds to all of the types of preparation work.

Description

[Technical Field]

[0001] One aspect of the present invention relates to an information processing device that determines the location of a staging area (described below) on a production floor. [Background technology]

[0002] Various techniques for optimizing production facilities have been proposed. As an example, Patent Document 1 below discloses a method for determining the location of a preparation area (referred to as a work area in Patent Document 1) on a production floor through mathematical optimization. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-123056 Summary of the Invention [Problem to be solved by the invention]

[0004] An object of one aspect of the present invention is to determine the locations of multiple preparation areas on a production floor more appropriately than has been possible in the past. [Means for solving the problem]

[0005] An information processing device according to one embodiment of the present invention is an information processing device that determines the positions of multiple preparation areas for multiple types of preparation work before workers start work to produce a product on a production floor, wherein each of the multiple preparation areas on the production floor corresponds one-to-one to each of the multiple types of preparation work, and the information processing device determines the positions of each of the multiple preparation areas by performing mathematical optimization based on an objective function that corresponds to all types of preparation work.

[0006] An information processing method according to one aspect of the present invention is an information processing method for determining the positions of multiple preparation areas for multiple types of preparation work before workers start work to produce a product on a production floor, wherein each of the multiple preparation areas on the production floor corresponds one-to-one to each of the multiple types of preparation work, and the information processing method includes a step of determining the position of each of the multiple preparation areas by performing mathematical optimization based on an objective function that corresponds to all types of preparation work. [Effects of the Invention]

[0007] According to one aspect of the present invention, the locations of multiple preparation areas on a production floor can be determined more appropriately than ever before. [Brief explanation of the drawings]

[0008] [Figure 1] 1 shows an example of the configuration of an information processing device according to a first embodiment. [Figure 2] 1 shows an example of a production floor on which multiple pieces of production equipment are arranged. [Figure 3] 10 is a diagram for explaining processing by a preparation area setting unit according to the first embodiment. FIG. [Figure 4] 1 is a flowchart illustrating a processing flow by the information processing apparatus of the first embodiment. [Figure 5] 3 shows an example of a floor layout determined by a floor layout determination unit of the first embodiment. [Figure 6] FIG. 10 is a diagram for explaining the arrangement of a plurality of preparation areas in a comparative example. DETAILED DESCRIPTION OF THE INVENTION

[0009] [Embodiment 1] The first embodiment will be described below. For ease of explanation, components having the same functions as those described in the first embodiment will be denoted by the same reference numerals in the following embodiments, and the description thereof will not be repeated. For simplicity, the description of matters similar to those in the publicly known technology will also be omitted as appropriate.

[0010] Unless otherwise specified, the components and values ​​described in this specification are merely examples. Therefore, for example, unless otherwise specified, the positional relationship and connection relationship of the components are not limited to the examples in the drawings. The order of the processing flow in the flowcharts is also not limited to the examples shown in the drawings unless otherwise specified.

[0011] (One configuration example of the information processing device 1) 1 shows an example of the configuration of an information processing device 1 according to embodiment 1. The information processing device 1 serves as a layout determination device that determines the layout of a production floor on which multiple pieces of production equipment are arranged. The information processing device 1 may also be configured to serve as a production management device.

[0012] The information processing device 1 includes a production processing unit 2, a production plan storage unit 3, and a floor information storage unit 4. The production processing unit 2 may be embodied by a control unit of the information processing device 1. Therefore, for example, the production processing unit 2 may be embodied by any processor of the information processing device 1.

[0013] 1 includes a preparation task frequency calculation unit 21, a preparation area setting unit 22, and a floor layout determination unit 23. The preparation area setting unit 22 includes a travel distance calculation unit 221, a weighting unit 222, and an optimization processing unit 223.

[0014] The production plan storage unit 3 may be any storage device. Production information 31 is stored in advance in the production plan storage unit 3. Information indicating the preparation work frequency calculated by the production processing unit 2 is stored in the production plan storage unit 3 as preparation work frequency information 32.

[0015] The production information 31 includes information related to product production plans. The production information 31 in the first embodiment includes information indicating the planned production quantity, the planned start time of production, and the planned end time of production for each type of product produced in the production facility. The production information 31 may also include information indicating the names and installation positions of parts to be attached to the product for each type of product produced in the production facility.

[0016] The floor information storage unit 4 may also be any storage device. In Fig. 1, a configuration is illustrated in which the floor information storage unit 4 is a storage device separate from the production plan storage unit 3. However, the floor information storage unit 4 and the production plan storage unit 3 may also be embodied as an integrated storage device.

[0017] The floor information storage unit 4 stores in advance layout information 41. The floor information storage unit 4 stores floor layout information 42 derived by the production processing unit 2.

[0018] The layout information 41 in the first embodiment includes information indicating (i) the equipment layout of multiple pieces of production equipment installed on the production floor, (ii) the initial location of the preparation area, (iii) the location of the material storage shed, and (iv) the location of the prohibited placement area, which is an area where the placement of the preparation area is prohibited. In this specification, the preparation area refers to an area on the production floor where preparation work is performed before workers start work to produce a product on the production floor. In the first embodiment, a case where there are multiple preparation areas is exemplified.

[0019] The production processing unit 2 acquires production information 31 from the production plan storage unit 3 and acquires layout information 41 from the floor information storage unit 4. The preparation work frequency calculation unit 21 calculates the preparation work frequency for each preparation work type (type of preparation work) based on the production information 31 and the layout information 41 (more specifically, information indicating the equipment layout of multiple production facilities). The preparation work frequency calculation unit 21 in the first embodiment is configured to be able to calculate the preparation work frequency for each position on the production floor. In the first embodiment, a case where there are multiple preparation work types will be illustrated.

[0020] Preparation work on the production floor in the first embodiment includes, for example, (i) supply work to replenish parts used in the production equipment, and (ii) replacement work to replace parts used in the production equipment in conjunction with a production changeover. The preparation work frequency calculation unit 21 outputs information indicating the preparation work frequency calculated by itself as preparation work frequency information 32. In the example of FIG. 1 , the preparation work frequency calculation unit 21 stores the preparation work frequency information 32 in the production plan storage unit 3.

[0021] Next, each component of the preparation area setting unit 22 will be described. First, the travel distance calculation unit 221 calculates the travel distance, which is the distance the worker must travel from the worker's current position to the target work position. Specifically, the travel distance calculation unit 221 determines the worker's travel route on the production floor. The travel distance calculation unit 221 determines the travel route so as to bypass areas on the preparation floor where objects that may obstruct the worker's movement (e.g., production equipment) are located. Next, the travel distance calculation unit 221 calculates the distance of the travel route as the travel distance. The travel distance calculation unit 221 in the first embodiment is configured to be able to calculate the travel distance for each preparation work type.

[0022] The weighting unit 222 acquires preparation work frequency information 32 from the production plan storage unit 3. The weighting unit 222 sets a weight based on the preparation work frequency of the position for the movement distance calculated by the movement distance calculation unit 221. The weight based on the preparation work frequency may be set arbitrarily. In the first embodiment, for the sake of simplicity, a case will be illustrated in which the preparation work frequency indicated in the preparation work frequency information 32 is used as the weight as is.

[0023] The weighting unit 222 calculates a weighted travel distance, which is a value obtained by multiplying the travel distance by the weight. The weighting unit 222 in the first embodiment is configured to be able to calculate the total weighted travel distance (the sum of the weighted travel distances) for each preparation work type.

[0024] The optimization processing unit 223 determines the position of each of the multiple preparation areas based on the weighted total travel distance calculated by the weighting unit 222. In the first embodiment, one preparation area is assigned to one preparation work type. That is, in the first embodiment, each of the multiple preparation areas corresponds one-to-one to each of the multiple preparation work types.

[0025] Therefore, the optimization processor 223 in the first embodiment is configured to determine the position of the preparation area for each preparation work type. Specifically, the optimization processor 223 determines the position of the preparation area for each preparation work type by applying any optimization method based on the weighted total travel distance. As an example, the optimization processor 223 determines the position of the preparation area for each preparation work type so as to minimize an objective function, which will be described later.

[0026] The floor layout determination unit 23 determines the floor layout in accordance with the arrangement information 41 and the arrangement of the preparation area for each preparation work type determined by the optimization processing unit 223. In this case, the floor layout determination unit 23 determines the positions of the temporary storage shelves and transport preparation locations within the preparation area so as not to interfere with production equipment existing around the preparation area.

[0027] The floor layout determination unit 23 outputs information indicating the floor layout determined by itself as floor layout information 42. In the example of FIG. 1, the floor layout determination unit 23 stores the floor layout information 42 in the floor information storage unit 4.

[0028] (Example of processing by information processing device 1) FIG. 2 shows an example of a production floor FP where multiple pieces of production equipment are located. FIG. 2 illustrates a case where one worker W is located on the production floor FP. The example of FIG. 2 illustrates a case where an information processing device 1 is located on the production floor FP. However, there may be multiple workers W on the production floor FP. The information processing device 1 may also be located outside the production floor FP.

[0029] FIG. 2 illustrates a production floor FP where mounted boards are produced as products. Mounted boards are an example of electronic devices. One or more component mounting lines made up of multiple pieces of production equipment are arranged within the production floor FP. In the example of FIG. 2, two component mounting lines are arranged in parallel. The two component mounting lines in the example of FIG. 2 are referred to as component mounting lines L1 and L2, respectively. Component mounting line L1 may be referred to as a first component mounting line, and component mounting line L2 may be referred to as a second component mounting line.

[0030] Each of the component mounting lines L1 to L2 is configured by connecting multiple pieces of production equipment, including printing devices, component mounting devices, etc. Each of the component mounting lines L1 to L2 is configured to be able to produce mounted boards, where components are mounted on a board, as products.

[0031] 2, the information processing device 1 is placed at a position away from the component mounting lines L1 to L2. A material storage warehouse 92 is placed near the information processing device 1. The material storage warehouse 92 is an example of a storage area where materials used in the production equipment are stored.

[0032] On the production floor FP, multiple preparation areas are arranged near the component mounting lines L1 to L2. As described above, the total number of preparation areas arranged on the production floor FP is equal to the total number of preparation work types. In the first embodiment, a case where the total number of preparation work types is three is illustrated. For this reason, three preparation areas are illustrated in FIG. 2.

[0033] The three preparation areas in the example of Fig. 2 are referred to as preparation areas Aw1 to Aw3, respectively. Preparation area Aw1 may be referred to as the first preparation area, preparation area Aw2 may be referred to as the second preparation area, and preparation area Aw3 may be referred to as the third preparation area. The positions of preparation areas Aw1 to Aw3 in the example of Fig. 2 are the same as the initial positions of preparation areas Aw1 to Aw3 shown in placement information 41.

[0034] 2, a temporary storage shelf 93 and a transport preparation location 94 are arranged inside each of the multiple preparation areas. The sizes of the temporary storage shelf 93 and the transport preparation location 94 may differ for each preparation area.

[0035] The temporary storage shelf 93 is an example of an area for temporarily storing materials transported from the material storage warehouse 92. Materials may be transported from the material storage warehouse 92 to the temporary storage shelf 93 by a worker W or by an automatic transport robot. The transport preparation area 94 is an example of an area for preparing materials for transport to production equipment. Transport carts and the like are temporarily placed in the transport preparation area 94.

[0036] Fig. 3 is a diagram for explaining the processing by the preparation area setting unit 22. The information processing device 1, the worker W, and the preparation areas Aw1 to Aw3 are not shown in Fig. 3. Instead, in Fig. 3, the placement prohibition area is represented by the symbol Ae.

[0037] 3, the preparation area setting unit 22 places multiple nodes in an area on the production floor FP excluding the material storage 92, component mounting lines L1-L2, and the prohibited placement area Ae. Specifically, the preparation area setting unit 22 places multiple nodes in the above area at predetermined intervals. The intervals between the nodes in FIG. 3 may be set in consideration of the constraints described below.

[0038] FIG. 3 illustrates an example in which the total number of nodes is 18. The 18 nodes in the example of FIG. 3 are denoted as nodes N1 to N18. For example, node N1 may be referred to as the first node, and node N18 may be referred to as the 18th node. In the example of FIG. 3, nodes N1 to N4 are located in the first row (top row). Nodes N4 to N11 are located in the second row (middle row). Nodes N12 to N18 are located in the third row (bottom row).

[0039] In the example of Fig. 3, in a given row, the node number increases from left to right on the page. In the example of Fig. 3, node N4 is the rightmost node in the first row, node N11 is the rightmost node in the second row, and node N18 is the rightmost node in the third row. In the example of Fig. 3, node N4, node N11, and node N18 are in the same position in the column direction.

[0040] In the example of FIG. 3, node N1 is the leftmost node in the first row, node N5 is the leftmost node in the second row, and node N12 is the leftmost node in the third row. However, node N1 is not located in the same position as nodes N5 and N12 in the column direction. This is because, in the example of FIG. 3, material storage 92 is positioned so as to overlap with nodes N5 to N7 and nodes N12 to N14 when viewed in the column direction. For this reason, node N1 in the example of FIG. 3 is located in the same position as nodes N8 and N15 in the column direction.

[0041] As described above, in the first embodiment, one preparation area is assigned to one preparation work type. Therefore, in this specification, the preparation work type corresponding to the preparation area Aw1 will be referred to as preparation work type 1. Similarly, the preparation work type corresponding to the preparation area Aw2 will be referred to as preparation work type 2, and the preparation work type corresponding to the preparation area Aw3 will be referred to as preparation work type 3. Preparation work types 1 to 3 may also be referred to as the first to third preparation work types, respectively.

[0042] In Fig. 3, p1 to p3 represent the preparation work frequencies of preparation work type 1 to preparation work type 3, respectively. p1 to p3 are calculated in advance by the preparation work frequency calculation unit 21 prior to processing by the preparation area setting unit 22. In the example of Fig. 3, p1 to p3 are illustrated so that the larger the value of a certain preparation work frequency, the larger the size of the circular object representing that preparation work frequency. As shown in Fig. 3, p1 to p3 can differ depending on the position.

[0043] Next, reference will be made to Fig. 4. Fig. 4 is a flowchart illustrating the flow of processing by the information processing device 1. First, in step S1, the production processing unit 2 acquires layout information 41 from the floor information storage unit 4. In step S2, the production processing unit 2 acquires production information 31 from the production plan storage unit 3.

[0044] In this specification, the number of the preparation work type is represented by the subscript m. In step S3, the production processing unit 2 initializes m. Specifically, in step S3, the production processing unit 2 sets m to 1.

[0045] In step S4, the preparation work frequency calculation unit 21 calculates the preparation work frequency for m based on the production information 31 and the allocation information 41.

[0046] In this specification, a predetermined node among the multiple nodes set by the preparation area setting unit 22 is referred to as the focus node. In step S5, the travel distance calculation unit 221 selects one node from nodes N1 to N18 as the focus node. Then, the travel distance calculation unit 221 calculates the travel distance from the focus node to each work position of each production facility for preparation work type m.

[0047] In step S6, the travel distance calculation unit 221 calculates the travel distance from the focus node to each work position in each material storehouse for the preparation work type m.

[0048] In step S7, the travel distance calculation unit 221 determines whether or not calculation of the travel distance for all nodes for the preparation work type m has been completed. If the answer is YES in step S7, that is, if calculation of the travel distance for all nodes for the preparation work type m has been completed, the process proceeds to step S8.

[0049] On the other hand, if the result in step S7 is NO, that is, if calculation of the travel distance for all nodes for preparation work type m has not been completed, the process returns to step S5. In this way, the processes in steps S5 to S6 are repeated until the result in step S7 becomes YES.

[0050] When returning from step S7 to step S5, the movement distance calculation unit 221 again selects, as the node of interest, one of the nodes N1 to N18 that has not yet been selected as the node of interest.

[0051] In step S8, the weighting unit 222 calculates the total weighted travel distance for all nodes for m. In the example of embodiment 1, the weighting unit 222 calculates the sum of (i) the weighted travel distance from the focus node to all work positions in the production equipment and (i) the weighted travel distance from the focus node to all work positions in the material storage facility as the total weighted travel distance for all nodes for m.

[0052] In the example of the first embodiment, the total number of preparation work types is represented as M. In step S9, the weighting unit 222 determines whether m = M. The determination in step S9 corresponds to determining whether calculation of the weighted total travel distance corresponding to each preparation area has been completed for all preparation work types and for all nodes.

[0053] If the answer to step S9 is YES, that is, if m = M, it can be said that calculation of the weighted total travel distance corresponding to each preparation area for all preparation work types and for all nodes has been completed. Therefore, if the answer to step S9 is YES, proceed to step S11.

[0054] On the other hand, if the answer to step S9 is NO, that is, if m≠M, it can be said that calculation of the weighted total travel distance corresponding to each preparation area for all preparation work types and for all nodes has not been completed. Therefore, if the answer to step S9 is NO, proceed to step S10.

[0055] In step S10, the production processing unit 2 counts up m by 1. Then, the process returns to step S4. In this way, the processes of steps S4 to S8 are repeated until the result in step S9 becomes YES.

[0056] In step S11, the optimization processor 223 determines the optimal layout of each preparation area based on the weighted total travel distance corresponding to each preparation area. Specifically, the optimization processor 223 determines the layout of each preparation area by performing mathematical optimization based on the weighted total travel distance.

[0057] In the first embodiment, one or more objectives may be set in the mathematical optimization. For simplicity of explanation, the first embodiment illustrates a case where the number of objectives is one. Specifically, the first embodiment illustrates a case where one objective, "determine a node that minimizes the sum of weighted travel distances for all preparatory work types," is set in the mathematical optimization.

[0058] In the mathematical optimization, one or more constraints may be set. Condition 1: One preparation area is placed on one node; Condition 2: Each of the multiple preparation areas is located on a different node; Condition 3: The preparation areas are not located on adjacent nodes; The following example illustrates a case where the following three constraints are set. As shown in FIG. 3 above, in the example of the first embodiment, a horizontally long preparation area is assumed. Therefore, "adjacent" in condition 3 means adjacent in the column direction.

[0059] If we formulate the above objectives and constraints in mathematical optimization, we get

number

[0060] Equation (1) corresponds to the above-mentioned objective. The object of min (minimization) in equation (1) is the objective function in the mathematical optimization of embodiment 1. In this way, the above-mentioned objective is formulated as a minimization problem of the objective function. Equations (2-1) to (2-3) correspond to the above-mentioned conditions 1 to 3, respectively. "i" is a subscript representing the node number.

[0061] As described above, in the first embodiment, one or more objectives may be set in the mathematical optimization. Therefore, in the first embodiment, it is sufficient that one or more objective functions are set. In the first embodiment, for the sake of clarity, a case where the number of objective functions is one will be exemplified.

[0062] x mi is a decision variable in the mathematical optimization of the first embodiment. mi is set to 1 when Awm, the preparation area corresponding to preparation work type m, is placed on Ni, the i-th node. Otherwise, x mi is set to 0. y mi is the total weighted travel distance when the preparation area Awm is placed on the node Ni.

[0063] In step S12, the floor layout determination unit 23 determines the floor layout in accordance with the arrangement of each preparation area determined by the optimization processing unit 223.

[0064] 5 shows an example of a floor layout determined by the floor layout determination unit 23. In the example of the first embodiment, it is assumed that the above-mentioned objective function is minimized when the preparation area Aw1 is placed on node N14, the preparation area Aw2 is placed on node N16, and the preparation area Aw3 is placed on node N18.

[0065] The layout of each preparation area in the example of Fig. 5 can be derived by solving the minimization problem of the objective function by the optimization processing unit 223. The layout of each preparation area in the example of Fig. 5 satisfies the above-mentioned conditions 1 to 3.

[0066] (Comparative Example) Fig. 6 is a diagram for explaining the arrangement of multiple preparation areas in a comparative example. In the example of Fig. 6, the positions of each of the multiple preparation areas are determined by conventional technology (e.g., the technology of Patent Document 1). Fig. 6 is a diagram paired with Fig. 3. Fig. 6 also illustrates an example in which the positions of three preparation areas are determined.

[0067] The constraints in the mathematical optimization of the comparative example are the same as those in the first embodiment. However, unlike the first embodiment, the mathematical optimization of the comparative example sets the weighted total travel distance corresponding to one preparation work type as the objective function. Specifically, in the mathematical optimization of the comparative example, the position of the preparation area is determined so as to minimize the weighted total travel distance corresponding to one preparation work type.

[0068] Therefore, in the comparative example, the positions of the multiple preparation areas are determined sequentially. In the example of Fig. 6, the positions of the preparation areas are determined in the order of preparation area Aw1 → preparation area Aw2 → preparation area Aw3.

[0069] As shown by reference numeral 610 in FIG. 6 , in the comparative example, the position of preparation area Aw1 is determined first. In the comparative example, the position of preparation area Aw1 is determined so as to minimize the sum of weighted travel distances corresponding to preparation area Aw1. The weight corresponding to preparation area Aw1 is based only on p1. Therefore, in the comparative example, the position of preparation area Aw1 is determined taking into account only p1, without considering p2 and p3. In other words, in the comparative example, the position of preparation area Aw1 is determined taking into account only preparation work type 1, without considering preparation work type 2 and preparation work type 3.

[0070] In the comparative example, when the preparation area Aw1 is placed on the node N14, the minimum value of the weighted movement distance sum corresponding to the preparation area Aw1 is obtained. Therefore, in the example of reference numeral 610, the preparation area Aw1 is placed on the node N14.

[0071] As indicated by reference numeral 620, in the comparative example, the position of preparation area Aw1 is determined, and then the position of preparation area Aw2 is determined. In the comparative example, the position of preparation area Aw2 is determined so as to minimize the sum of weighted travel distances corresponding to preparation area Aw2. The weight corresponding to preparation area Aw2 is based only on p2. Therefore, in the comparative example, the position of preparation area Aw2 is determined taking into account only p2, without taking into account p1 and p3. In other words, in the comparative example, the position of preparation area Aw2 is determined taking into account only preparation work type 2, without taking into account preparation work type 1 and preparation work type 3.

[0072] In the comparative example, when the preparation area Aw2 is placed on node N14, the minimum value of the weighted movement distance sum corresponding to the preparation area Aw2 is obtained. However, since the preparation area Aw1 is already placed on node N14, the preparation area Aw2 cannot be placed on node N14.

[0073] Considering the above-mentioned condition 3, the nodes where the preparation area Aw2 can be placed are limited to nodes N1 to N12 and N16 to N18, which are not adjacent to node N14. In the comparative example, when the preparation area Aw2 is placed on node N16 among nodes N1 to N12 and N16 to N18, the minimum value of the weighted movement distance sum corresponding to the preparation area Aw2 is obtained. Therefore, in the example of reference numeral 620, the preparation area Aw2 is placed on node N16.

[0074] As indicated by reference numeral 630, in the comparative example, the position of preparation area Aw2 is determined, and then the position of preparation area Aw3 is determined. In the comparative example, the position of preparation area Aw3 is determined so as to minimize the sum of weighted travel distances corresponding to preparation area Aw3. The weight corresponding to preparation area Aw3 is based only on p3. Therefore, in the comparative example, the position of preparation area Aw3 is determined by considering only p3, without considering p1 and p2. In other words, in the comparative example, the position of preparation area Aw3 is determined by considering only preparation work type 3, without considering preparation work type 1 and preparation work type 2.

[0075] In the comparative example, when preparation area Aw3 is placed on node N14, the minimum value of the weighted travel distance sum corresponding to preparation area Aw3 is obtained. However, because preparation area Aw1 is already placed on node N14, preparation area Aw3 cannot be placed on node N14. In addition, because preparation area Aw2 is already placed on node N16, preparation area Aw3 cannot be placed on node N16 either.

[0076] Considering the above-mentioned condition 3, the nodes where the preparation area Aw3 can be placed are limited to nodes N1 to N12 and N18, which are not adjacent to nodes N12 and N14. In the comparative example, if the preparation area Aw3 is placed on node N8 out of nodes N1 to N12 and N18, the minimum value of the weighted travel distance sum corresponding to the preparation area Aw3 is obtained. Therefore, in the example of reference numeral 630, the preparation area Aw3 is placed on node N8.

[0077] (Effects of the First Embodiment) As described above, in the comparative example, the position of a preparation area corresponding to one preparation work type is determined by performing mathematical optimization based on the weighted travel distance sum corresponding to that preparation work type. Therefore, in the comparative example, the positions of multiple preparation areas are determined sequentially. Therefore, the later the preparation area is in the order in which the calculation to be mathematically optimized is performed, the fewer nodes the preparation area can be placed on. For this reason, there is a concern that the comparative example may not be able to determine the overall optimal positions for multiple preparation areas.

[0078] On the other hand, in the first embodiment, the positions of the multiple preparation areas are determined by performing mathematical optimization based on an objective function that corresponds to all preparation work types (e.g., the sum of the weighted travel distances for all preparation work types). In this way, in the first embodiment, an objective function different from that in the comparative example is set, and mathematical optimization is performed based on this objective function.

[0079] By setting the objective function as shown in the first embodiment, it is possible to treat each of the multiple preparation areas equally in the mathematical optimization, unlike the comparative example. Therefore, according to the first embodiment, it is possible to determine the overall optimal positions for the multiple preparation areas, unlike the comparative example. As described above, according to the first embodiment, it is possible to determine the positions of the multiple preparation areas on the production floor more appropriately than before.

[0080] [Embodiment 2] (1) The mathematical optimization algorithm according to one embodiment of the present invention is not particularly limited, and examples of the algorithm include linear programming, nonlinear programming, and genetic algorithms.

[0081] (2) In the first embodiment, an example is given in which the optimization problem is formulated so as to minimize the objective function. However, the formulation of the optimization problem is not limited to the example of the first embodiment. The optimization problem may be formulated so as to be suitable for determining the positions of multiple preparation areas on a production floor. For example, the optimization problem may be formulated so as to maximize the objective function.

[0082] (3) In the first embodiment, a production floor for producing electronic devices is illustrated. However, the product according to one aspect of the present invention is not limited to electronic devices. For example, the product according to one aspect of the present invention may be a processed food.

[0083] Therefore, the method according to one aspect of the present invention can be used to determine the locations of multiple preparation areas on a production floor for producing any product. As an example, the method according to embodiment 1 can be used to determine the locations of multiple preparation areas on a production floor for producing processed foods.

[0084] [Software implementation example] The functions of the information processing device 1 (hereinafter referred to as the "device") can be realized by a program that causes a computer to function as the device, and a program that causes a computer to function as each control block of the device (in particular, each part included in the production processing unit 2).

[0085] In this case, the device includes a computer having at least one control device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing the program. The control device and storage device execute the program, thereby realizing the functions described in each of the above embodiments.

[0086] The program may be non-transitory and may be recorded on one or more computer-readable recording media. The recording media may or may not be included in the device. In the latter case, the program may be supplied to the device via any wired or wireless transmission medium.

[0087] Some or all of the functions of the control blocks can be realized by logic circuits. For example, an integrated circuit in which a logic circuit that functions as each of the control blocks is formed is also included in the scope of one aspect of the present invention. In addition, the functions of the control blocks can also be realized by, for example, a quantum computer.

[0088] The processes described in the above embodiments may be executed by AI (Artificial Intelligence). In this case, the AI ​​may run on the control device or on another device (for example, an edge computer or a cloud server).

[0089] [Additional Notes] One aspect of the present invention is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of one aspect of the present invention. [Explanation of symbols]

[0090] 1. Information processing equipment 2 Production Processing Department 3 Production plan memory section 4. Floor information storage unit 21 Preparation work frequency calculation section 22 Preparation area setting section 23 Floor Layout Decision Section 31 Production Information 32 Work Frequency Information 41 Placement information 42 Floor Layout Information FP Production Floor W Worker Aw1~Aw3 Preparation Area

Claims

1. An information processing device that determines the positions of a plurality of preparation areas for a plurality of types of preparation work before a worker starts work to produce a product on a production floor, each of the plurality of preparation areas on the production floor corresponds one-to-one to each of the plurality of types of preparation work; The information processing device determines the positions of each of the plurality of preparation areas by performing mathematical optimization based on an objective function that corresponds to all types of the preparation work.

2. 1. An information processing method for determining the locations of a plurality of preparation areas for a plurality of types of preparation work before a worker starts work to produce a product on a production floor, comprising: each of the plurality of preparation areas on the production floor corresponds one-to-one to each of the plurality of types of preparation work; The information processing method includes a step of determining the positions of each of the plurality of preparation areas by performing mathematical optimization based on an objective function corresponding to all types of the preparation work.

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