Layout generation method, layout generation device, and program

Abstract

The layout generation method acquires input data including work plan data for work to be performed in an automated warehouse that can be configured by combining multiple bases, first performance index data that indicates the goals of the automated warehouse, and constraint data for the automated warehouse; generates layout design data for the automated warehouse that is configured by arranging multiple bases based on the input data; calculates second performance index data that indicates the performance index of the automated warehouse that corresponds to the layout design data based on the layout design data; and repeats the generation of the layout design data until the second performance index data satisfies the first performance index data.

Description

[Technical Field]

[0001] The present disclosure relates to a layout generation method, a layout generation device, and a program for an automated warehouse. [Background technology]

[0002] Patent Literature 1 discloses a computer-based technique for simulating warehouse automation designs and evaluating the results of the simulation to inform various decisions. For example, warehouse automation can be simulated with the goal of determining an optimal warehouse automation design given various parameters specific to a warehouse, such as projected customer inventory demand over time, warehouse layout, and / or specific automation mechanisms (e.g., machines) considered within the warehouse. This allows for the identification of an optimal warehouse automation design that maximizes warehouse efficiency by minimizing pallet loading and unloading times, minimizing truck loading and unloading times, and minimizing / eliminating bottlenecks that prevent the warehouse from meeting threshold performance criteria. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japan Special Publication No. 2020-520526 Summary of the Invention [Problem to be solved by the invention]

[0004] In order to efficiently carry out warehouse operations, it is important to determine the optimal layout of the warehouse, for example, determining what to place where in the warehouse. However, determining the optimal warehouse layout requires comprehensive consideration of meeting the warehouse performance desired by the user while also satisfying physical and cost constraints. In other words, determining the optimal warehouse layout is by no means an easy task. Patent Document 1 discloses simulation technology for warehouse automation design, but does not disclose simulation technology that takes into account the above-mentioned comprehensive considerations, and there is likely room for improvement.

[0005] The present disclosure has been devised in view of the above-described conventional situation, and aims to generate an optimal layout for an automated warehouse that satisfies not only the constraints related to the automated warehouse but also the performance of the automated warehouse desired by the user. [Means for solving the problem]

[0006] The present disclosure provides a layout generation method that acquires input data including work plan data for work to be performed in an automated warehouse that can be configured by combining a plurality of bases, first performance index data that indicates goals for the automated warehouse, and constraint data for the automated warehouse, generates layout design data for the automated warehouse that is configured by arranging the plurality of bases based on the input data, calculates second performance index data that indicates performance indexes for the automated warehouse that correspond to the layout design data based on the layout design data, and repeats generation of the layout design data until the second performance index data satisfies the first performance index data.

[0007] The present disclosure also provides a layout generation device including a processor and a memory, wherein the processor cooperates with the memory to acquire input data including work plan data for work to be performed in an automated warehouse that can be configured by combining a plurality of bases, first performance index data indicating targets for the automated warehouse, and constraint data for the automated warehouse, generates layout design data for the automated warehouse configured by arranging the plurality of bases based on the input data, calculates second performance index data indicating performance indexes for the automated warehouse that correspond to the layout design data, and repeats generation of the layout design data until the second performance index data satisfies the first performance index data.

[0008] The present disclosure also provides a program for causing a layout generation device, which is a computer, to execute the following processes: acquiring input data including work plan data for work to be performed in an automated warehouse that can be configured by combining multiple bases, first performance index data indicating goals for the automated warehouse, and constraint data for the automated warehouse; generating layout design data for the automated warehouse configured by arranging the multiple bases based on the input data; calculating second performance index data indicating performance indexes for the automated warehouse that correspond to the layout design data based on the layout design data; and repeating the generation of the layout design data until the second performance index data satisfies the first performance index data.

[0009] These comprehensive or specific aspects may be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or a recording medium, or may be realized as any combination of a system, an apparatus, a method, an integrated circuit, a computer program, and a recording medium. [Effects of the Invention]

[0010] According to the present disclosure, it is possible to generate an optimal layout for an automated warehouse that satisfies not only the constraints related to the automated warehouse but also the performance of the automated warehouse desired by the user. [Brief explanation of the drawings]

[0011] [Figure 1] A three-dimensional diagram showing an example of the layout and external structure of an automated warehouse [Figure 2] FIG. 1 is a block diagram showing an example of the hardware configuration of a layout generation system according to an embodiment of the present invention. [Figure 3] FIG. 1 is a diagram showing a schematic flow of calculation processing performed by a processor of a calculation device. [Figure 4] A flowchart showing an example of the overall operation procedure of the calculation process for the layout design of an automated warehouse by a calculation device in chronological order. [Figure 5] A flowchart showing a detailed example of the base layout design procedure in step St1 of FIG. 4 in chronological order. [Figure 6A] A diagram showing a schematic example of the warehouse area design process in step St12 of FIG. [Figure 6B] FIG. 6 is a diagram illustrating an example of the outline of the base layout design process in step St13 of FIG. 5. [Figure 7] A flowchart showing a detailed example of the bin layout design procedure in step St2 of Figure 4 in chronological order. [Figure 8] FIG. 8 is a diagram showing a schematic example of the bin layout design process in step St23 of FIG. [Figure 9] FIG. 5 is a diagram showing a schematic example of the product layout optimization process in step St3 of FIG. [Figure 10] FIG. 5 is a diagram illustrating an example of a resource design process outline in step St4 of FIG. 4. [Figure 11] A diagram showing an example of calculation processing conditions for layout design of an automated warehouse [Figure 12] A diagram showing the first example of the calculation results for the layout design of an automated warehouse. [Figure 13] Figure showing the second example of the calculation results for the layout design of an automated warehouse DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, with reference to the drawings as appropriate, detailed descriptions of embodiments specifically disclosing a layout generation method, a layout generation device, and a program according to the present disclosure will be described in detail. However, unnecessary detailed descriptions may be omitted. For example, detailed descriptions of well-known matters and redundant descriptions of substantially identical configurations may be omitted. This is to avoid unnecessary redundancy in the following description and to facilitate understanding by those skilled in the art. Note that the accompanying drawings and the following description are provided to enable those skilled in the art to fully understand the present disclosure, and are not intended to limit the subject matter of the claims.

[0013] 1. Layout of automated warehouse First, an example of the external structure of the layout of an automated warehouse generated by the layout generation method according to the present disclosure will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the external structure of the layout of the automated warehouse AST1 in three dimensions. Fig. 1 shows an example of the external structure that shows the layout of the automated warehouse AST1 in three dimensions, and the layout of this automated warehouse AST1 is configured based on warehouse automation design data generated by a computing device 10, which will be described later.

[0014] In the following description, an automated warehouse is a structure having at least a warehouse area AR1, which is an area for physically arranging the warehouse; shelves arranged in the warehouse area AR1 and capable of storing multiple large-capacity boxes (e.g., bins B1) for storing products; and a picking station ST. The picking station ST temporarily arranges bins B1 (e.g., storage bins) transported from the shelves by a robot or the like and bins B1 (e.g., shipping bins) for storing products to be shipped from the automated warehouse AST1, and is a location where the products stored in the storage bins are transferred to the shipping bins. The product transfer may be performed automatically by a robot or manually by a worker (person); both automatic and manual transfers are considered acceptable in this specification. Thus, the layout generation method according to this embodiment makes it possible to generate warehouse automation design data showing an example of the layout appearance structure of an automated warehouse as shown in FIG. 1.

[0015] In the example of the automated warehouse AST1 in Fig. 1, one warehouse area AR1, one shelf, and two picking stations ST are arranged. However, the number of warehouse areas, shelves, and picking stations arranged in the automated warehouse AST1 is not particularly limited.

[0016] As shown in FIG. 1, the components of the automated warehouse excluding the warehouse area (for example, shelves, picking stations ST) are made up of one or more bases BS1.

[0017] A brief explanation of the base BS1 will be given.

[0018] The base BS1 is a structure formed by combining one rectangular, flat floor board PB1 with four poles PL1 fixed in contact with the four corners of the rectangular floor board PB1.

[0019] For example, a shelf is made up of multiple bases BS1. Specifically, the shelf is made up of multiple bases BS1 arranged adjacent to each other in the front-to-back, left-to-right, top-to-bottom directions. The shelf may also be made up of multiple floors (a six-story structure in the example of Figure 1). In other words, a single-story shelf may be constructed, or a multi-story shelf may be constructed. By arranging the shelves in the automated warehouse AST1, multiple large-capacity bins B1 can be stored.

[0020] Furthermore, for example, the elevator EV1 is composed of multiple bases BS1. Specifically, the bases BS1 arranged in a vertically stacked configuration may be replaced with elevators EV1 that can raise and lower bins B1. By providing the elevators EV1 in the automated warehouse AST1, the transportation of bins B1 from shelves configured with multiple levels to picking stations ST and the like is simplified.

[0021] Furthermore, for example, the picking station ST is configured with a plurality of bases BS1. Specifically, the picking station ST has a workbench space where storage bins B1 and shipping bins transported from the shelves are temporarily placed and where products are transferred from the storage bins to the shipping bins.

[0022] 2. Layout Generation System Configuration Next, with reference to FIG. 2, an example of a system configuration of a layout generation system 100 according to this embodiment will be described. FIG. 2 is a block diagram showing an example of a hardware configuration of the layout generation system 100 according to this embodiment. The layout generation system 100 includes a computing device 10 as an example of a layout generation device, and an external database 20. Although not clearly shown in FIG. 2, the computing device 10 and the external database 20 may be directly connected to each other so as to enable data communication, or may be connected via a network so as to enable data communication. For simplicity of explanation, an example in which the computing device 10 and the external database 20 are directly connected to each other so as to enable data communication will be described below.

[0023] The computing device 10 uses various input data (see FIG. 3) to generate warehouse automation design data that shows an example of the external structure of the automated warehouse AST1 as shown in FIG. 1. The computing device 10 is, for example, a computer such as a desktop personal computer or a server computer. Note that the computing device 10 is not limited to these stationary computers, and may also be, for example, a portable computer such as a smartphone or a tablet terminal. The computing device 10 includes a communication I / F 11, a memory 12, an input device 13, a display device 14, and a processor 15.

[0024] The communication I / F 11 is an interface circuit that performs wireless or wired communication between the computing device 10 and the external database 20. Here, I / F refers to an interface. The communication between the computing device 10 and the external database 20 may be via a network. The communication method used by the communication I / F 11 is, for example, a Wide Area Network (WAN), a Local Area Network (LAN), Long Term Evolution (LTE), mobile communication such as 4G or 5G, power line communication, short-range wireless communication (e.g., Bluetooth (registered trademark) communication), or communication for mobile phones.

[0025] The memory 12 is configured using, for example, Random Access Memory (RAM) and Read Only Memory (ROM), and temporarily stores programs necessary for the operation of the computing device 10 and data acquired or generated during operation. The RAM is, for example, a work memory used during the operation of the computing device 10. The ROM stores and stores, in advance, programs for controlling the computing device 10, for example.

[0026] The input device 13 is a device that accepts input from a user of the computing device 10. The input device 13 may be, for example, a mouse, a keyboard, a touch panel, or the like, or a combination thereof.

[0027] The display device 14 displays the results of calculations executed by the computing device 10. The calculation results are, for example, text data or graphic images such as character strings showing an example of the external structure of the layout of the automated warehouse AST1 based on warehouse automation design data (see FIG. 1), which will be described later, or an example of a plan view of each level of the automated warehouse AST1 (see FIG. 12 or FIG. 13). The display device 14 is, for example, a Liquid Crystal Display (LCD) or an organic EL display. The input device 13 and the display device 14 may be configured as one unit, in which case the input device 13 is a touch panel display or the like.

[0028] The processor 15 is configured by at least one of, for example, a central processing unit (CPU), a digital signal processor (DSP), a graphical processing unit (GPU), or a field programmable gate array (FPGA). The processor 15 functions as a controller that manages the overall operation of the computing device 10. The processor 15 performs control processing for overseeing the operation of each unit of the computing device 10, data input / output processing between each unit of the computing device 10, data arithmetic processing, and data storage processing. The processor 15 operates according to a program stored in the memory 12. The processor 15 uses the memory 12 during operation, and temporarily stores data generated or acquired by the processor 15 in the memory 12. The processor 15 realizes the functions of a data acquisition unit 16, an automated warehouse layout design unit 17, a model generation unit 18, and a performance evaluation unit 19 by using the programs and data stored in the memory 12.

[0029] The data acquisition unit 16 acquires input data (see Figure 3) required for the operation of each of the automated warehouse layout design unit 17, model generation unit 18, and performance evaluation unit 19 by referring to the memory 12 or an external database 20.

[0030] The automated warehouse layout design unit 17 generates warehouse automation design data (see FIG. 3) that satisfies various conditions included in the input data (see FIG. 3) based on the input data acquired by the data acquisition unit 16. Here, the warehouse automation design data is data that indicates the three-dimensional layout of the automated warehouse AST1 shown in FIG. 1. An overview of the processing of the automated warehouse layout design unit 17 will be described later with reference to FIG. 3.

[0031] The model generation unit 18 inputs the warehouse automation design data generated by the automated warehouse layout design unit 17 and constructs (generates) a simulation model corresponding to the warehouse automation design data using, for example, a Multi Agent Simulator (MAS). Using the generated simulation model, the model generation unit 18 executes a simulation (virtual experiment) that reproduces the automated warehouse corresponding to the warehouse automation design data, and calculates performance indicators (KPIs, see below) that can be achieved by this automated warehouse through this simulation.

[0032] The performance evaluation unit 19 acquires the key performance indicators (KPIs) calculated by the model generation unit 18 from the model generation unit 18, and also acquires the key performance indicators (KPIs) that the automated warehouse should satisfy from the memory 12 or the external database 20. The performance evaluation unit 19 determines whether the performance indicators (KPIs, an example of second performance indicator data) calculated by the model generation unit 18 satisfy the performance indicators (KPIs, an example of first performance indicator data) that the automated warehouse should satisfy. The performance evaluation unit 19 may output and display this determination result on the display device 14 or the like.

[0033] The external database 20 is configured, for example, by a database management system (DBMS) or a storage device such as a hard disk, and stores and accumulates input data (see Figure 3) required to execute various processes performed by the computing device 10, and output data (see Figure 3) obtained by those processes.

[0034] Next, the flow of various processes performed by the computing device 10 will be described with reference to Fig. 3. Fig. 3 is a diagram schematically showing the flow of calculation processes performed by the processor 15 of the computing device 10. As shown in Fig. 3, the processor 15, which is the main body of the calculation processes performed by the computing device 10, executes various processes of steps S1, S2, and S3 using input data, thereby outputting output data.

[0035] First, the input data will be described.

[0036] All or part of the input data may be stored in advance in the memory 12, or all or part of the input data may be acquired from an external database 20 and stored in the memory 12. The input data includes, for example, work plan data I1, key performance indicator (KPI) data I2, machine parameter data I3, priority data I4, constraint data I5, and cost data I6. Note that if there is only one performance indicator data I2 that the automated warehouse must satisfy, the priority data I4 is unnecessary.

[0037] The work plan data I1 indicates a work plan for the automated warehouse AST1, that is, data related to a work schedule that indicates what work is planned to be done within the automated warehouse AST1. The work plan data I1 includes the work start time, work type, and work target. For example, when a certain product is to be shipped out from the automated warehouse AST1, the work type is "shipping," and the work target specifies the product ID and quantity that specify the product to be shipped out.

[0038] The performance index (KPI) data I2 is data indicating Key Performance Indicators (KPIs), which are performance indicators that the automated warehouse AST1 must meet. In other words, the performance indicators indicate what goals the automated warehouse AST1 is expected to be configured with. The performance indicators may be, for example, a goal such as "keeping implementation costs low," or a goal such as "increasing storage capacity," or "increasing processing capacity" (see FIG. 11). Note that these goals are merely examples of performance indicators and are not limited to these.

[0039] The machine parameter data I3 is parameter data that indicates specifications such as the size of a bin transport robot (an example of a resource) such as an Autonomous Mobile Robot (AMR) that is introduced and placed in the automated warehouse AST1.

[0040] When multiple pieces of performance index (KPI) data I2 are provided, the priority data I4 indicates which piece of performance index (KPI) data I2 should be given priority consideration when generating warehouse automation design data for the automated warehouse AST 1. As described above, when only one piece of performance index (KPI) data I2 is provided, the priority data I4 is unnecessary.

[0041] The constraint data I5 is data indicating constraints for generating warehouse automation design data for the automated warehouse AST 1. The constraint data I5 includes, for example, data on user-input constraints input based on the intentions of the user operating the computing device 10, and data on constraints specific to automated warehouses, such as the size and layout of the automated warehouse AST 1.

[0042] The cost data I6 is data indicating the cost required to introduce the automated warehouse AST 1 (in other words, the budget allowed for constructing the automated warehouse AST 1). The cost data I6 may also include data indicating the cost required to introduce (purchase, lease, etc.) the above-mentioned transport robot.

[0043] The processor 15 uses the above-mentioned input data to perform a process of designing the layout of the automated warehouse AST1 that satisfies the various conditions included in the input data (specifically, work plan data I1, performance index data I2, machine parameter data I3, and, if necessary, priority data I4, constraint data I5, and cost data I6) (i.e., a process of generating warehouse automation design data) (step S1).

[0044] The processor 15 inputs the warehouse automation design data generated in step S1 and generates a simulation model corresponding to this warehouse automation design data (step S2). The processor 15 uses the simulation model generated in step S2 to execute a simulation (virtual experiment) that recreates an automated warehouse corresponding to the warehouse automation design data, and calculates key performance indicators (KPIs) that can be achieved by this automated warehouse through this simulation. The processor 15 determines whether the key performance indicators (KPIs) calculated in step S2 satisfy the key performance indicators (KPIs) that the automated warehouse should satisfy (step S3). If the processor 15 determines that the key performance indicators (KPIs) calculated in step S2 satisfy the key performance indicators (KPIs) that the automated warehouse should satisfy, the processor 15 stores the warehouse automation design data O1 generated in step S1 in the memory 12 or outputs it to the external database 20.

[0045] 3. Layout generation method operation procedure Next, the operation procedure of the layout generation method according to this embodiment will be described with reference to Fig. 4 to Fig. 10. The layout generation method is executed, for example, by the calculation device 10 (see Fig. 2). Fig. 4 is a flowchart showing an example of the overall operation procedure of the calculation process for the layout design of the automated warehouse AST1 by the calculation device 10 in chronological order. First, the overall operation of the layout generation method according to this embodiment will be described with reference to Fig. 4, and then the detailed operation of each process will be described with reference to each of Figs. 5 to 10.

[0046] 4, the processor 15 executes a process of base layout design as a first layout in which a plurality of bases (an example of a first base) are arranged to primarily design the area and shape for configuring the automated warehouse AST1 (step St1). Details of the base layout design process will be described later with reference to FIGS. 5, 6A, and 6B. After the base layout design process of the automated warehouse AST1 is performed in step St1, the processor 15 executes a process of bin layout design as a second layout in which primarily design the placement locations and number of bins B1 (an example of a second base) that are stored on the shelves of the automated warehouse AST1 (see FIG. 1) and that store products stored by the automated warehouse AST1. Details of the bin layout design process will be described later with reference to FIGS. 7 and 8.

[0047] After the bin layout design process for the bin B1 is performed in step St2, the processor 15 executes a product layout optimization process as a third layout to optimize the placement location of the products (an example of a third base) to be stored in the bin B1 (step St3). Details of the product layout optimization process will be described later with reference to FIG. 9.

[0048] After the optimization of product placement in bin B1 is performed in step St3, the processor 15 executes resource design processing as a fourth placement to determine how many resources (e.g., transport robots such as AMRs, an example of a fourth base) should be introduced into the automated warehouse AST1 (step St4). The series of processing from step St1 to step St4 corresponds to the generation processing of warehouse automation design data shown in FIG.

[0049] The processor 15 generates a simulation model corresponding to the warehouse automation design data generated by the series of processes from step St1 to step St4 (step St5). Furthermore, the processor 15 uses the simulation model generated in step St5 to execute a simulation (virtual experiment) that reproduces an automated warehouse corresponding to the warehouse automation design data, and calculates key performance indicators (KPIs) that can be achieved by this automated warehouse through this simulation.

[0050] The processor 15 determines whether the key performance indicators (KPIs) calculated within a range not exceeding a predetermined number of trials satisfy the key performance indicators (KPIs) that the automated warehouse should satisfy (step St6). The number of trials is, for example, the number of repetitions of the base layout design in step St1. The number of trials may be specified in advance in the processing procedure of the program executed by the processor 15, or may be stored as data in the memory 12 and read out by the processor 15 when the program is executed. When the processor 15 determines that the key performance indicators (KPIs) calculated within a range not exceeding the predetermined number of trials satisfy the key performance indicators (KPIs) that the automated warehouse should satisfy, or when the processor 15 determines that the key performance indicators (KPIs) calculated within the range of the predetermined number of trials do not satisfy the key performance indicators (KPIs) that the automated warehouse should satisfy (step St6, YES), the processor 15 ends the processing of the layout generation method shown in FIG.

[0051] On the other hand, if the processor 15 determines that the performance index (KPI) calculated in step St5 does not satisfy the performance index (KPI) that the automated warehouse should satisfy within a predetermined number of trials (step St6, NO), the processor 15 determines whether the resources designed in step St4 can be redesigned based on the input data (step St7).If the processor 15 determines that the resources designed in step St4 can be redesigned (step St7, YES), the processor 15 executes a resource redesign process so that the result is different from the result of the resource design executed in the previous step St4 (step St4).

[0052] On the other hand, if the processor 15 determines that the resources designed in step St4 cannot be redesigned (step St7, NO), it determines whether the bin layout designed in step St2 can be redesigned based on the input data (step St8).If the processor 15 determines that the bin layout designed in step St2 can be redesigned (step St8, YES), it executes a process of redesigning the bin layout so that it differs from the result of the bin layout executed in the previous step St2 (step St2).

[0053] On the other hand, if the processor 15 determines that the bin layout designed in step St2 cannot be redesigned (step St8, NO), it determines based on the input data whether the base layout designed in step St1 can be redesigned (step St9). If the processor 15 determines that the base layout designed in step St1 can be redesigned (step St9, YES), it executes a process of redesigning the base layout so that it differs from the result of the base layout executed in the previous step St1 (step St1). Note that if the processor 15 determines that the base layout designed in step St1 cannot be redesigned (step St9, NO), it considers it impossible to generate warehouse automation design data and ends the processing of FIG. 4.

[0054] 4, the processor 15 attempts to generate warehouse automation design data by determining the base layout first and then sequentially determining the bin layout, product layout, and resource layout within the base layout, rather than simultaneously changing the parameters of all bases BS1 based on the input data. The processor 15 evaluates (determines) whether the performance index corresponding to the generated warehouse automation design data satisfies the key performance indicator (KPI) data I2 included in the input data. This enables the computing device 10 to quickly generate warehouse automation design data that satisfies the various conditions included in the input data.

[0055] Next, the details of the processing of step St1 in Fig. 4 will be described with reference to Fig. 5, Fig. 6A, and Fig. 6B. Fig. 5 is a flowchart showing a detailed example of the procedure for base layout design in step St1 in Fig. 4 in chronological order. Fig. 6A is a diagram showing a schematic example of the processing outline for warehouse area design in step St12 in Fig. 5. Fig. 6B is a diagram showing a schematic example of the processing outline for base layout design in step St13 in Fig. 5.

[0056] 5, the processor 15 determines whether the execution of the base layout design process is the first time (step St11). If the processor 15 determines that the execution of the base layout design process is the first time (step St11, YES), the processor 15 executes the warehouse area design process to design the warehouse area AR1, which is an area for physically arranging the automated warehouse AST1 (step St12).

[0057] On the other hand, when the processor 15 determines that the execution of the base layout design process is not the first time (step St11, NO), it determines based on the input data whether or not there is another base layout combination that is different from the current base layout combination and satisfies the input data (step St14). When the processor 15 determines that there is no other base layout combination that is different from the current base layout combination and satisfies the input data (step St14, NO), it executes the process of step St12 again (i.e., redesign to expand the warehouse area). When the processor 15 determines that there is another base layout combination that is different from the current base layout combination and satisfies the input data (step St14, YES), it executes the process of step St13 again (i.e., redesign to expand the base layout area).

[0058] Here, an outline of the warehouse area design process in step St12 of FIG. 5 will be described with reference to FIG. 6A.

[0059] In FIG. 6A, the results of the first to fourth warehouse area designs are shown in chronological order.

[0060] In the first warehouse area design, an example is shown in which only the free area r1, which has the largest area within the entire area AR0, is arranged to be used as the warehouse area.

[0061] In the second warehouse area design, an example is shown in which two areas of the total area AR0, namely, free area r1 and free area r2, which is the next largest area after free area r1, are expanded and arranged to be used as warehouse areas.

[0062] In the third warehouse area design, an example is shown in which three areas of the total area AR0 are expanded and arranged to be used as warehouse areas: vacant areas r1 and r2, and vacant area r3, which is the next largest area after vacant area r2.

[0063] In the fourth warehouse area design, an example is shown in which four areas of the total area AR0 are expanded and arranged to be used as warehouse areas: free areas r1, r2, r3, and free area r4, which is the next largest area after free area r3. The areas painted black within the total area AR0 in Figure 6A are areas that cannot be used as warehouses due to obstacles such as protruding walls.

[0064] 6A, if it is not possible to redesign the warehouse area on the same level (floor) within the entire allowable area AR0 of the automated warehouse AST1, the processor 15 similarly performs an expansion design on the next level (i.e., the level one level above) within a range that is less than the allowable level (floor) height of the automated warehouse AST1. Furthermore, similar expansion design on the next level (i.e., the level one level above) is not limited to the redesign of the warehouse area, but can also be applied to the redesign of the base layout and the redesign of the bin layout, which will be described below.

[0065] The processor 15 executes a base layout design process to select and arrange one or more bases (see FIG. 1) within the warehouse area designed in step St12 (step St13 in FIG. 5).

[0066] Here, an outline of the base layout design process in step St13 of FIG. 5 will be described with reference to FIG. 6B.

[0067] FIG. 6B shows the results of the first to fourth base placement designs in chronological order. Processor 15 selects bases based on performance index data I2 included in the input data, and determines the number of picking stations, resources such as AMRs, and elevators to be placed. Processor 15 selects a combination of bases to satisfy constraint data I5 included in the input data (e.g., constraint data specific to automated warehouses). For example, processor 15 determines that picking stations can only be placed on the edge of the area where bases can be placed.

[0068] In the first base placement design, a total of 12 bases are placed in the free area r1 allocated to the warehouse area obtained as a result of the first warehouse area design. Of the 12 bases, one picking station bs2 consisting of two bases is assigned to the end of the free area r1, and an area bs1 of 10 bases is assigned to the remaining part of the free area r1. In addition to shelves for storing bins B1, area bs1 may also be used to place resources such as elevators (see Figure 1) or transport robots such as AMRs, and so on.

[0069] In the second base layout design, in addition to the results of the first base layout design, a total of four bases are further placed in the free area r2 newly allocated to the warehouse area as the second warehouse area design. In other words, in addition to the results of the first base layout design, the area bs1 for four bases is allocated corresponding to the free area r2.

[0070] In the third base layout design, in addition to the results of the second base layout design, a total of two more bases are placed in the free area r3 newly allocated to the warehouse area as the third warehouse area design. In other words, in addition to the results of the second base layout design, the area bs1 for two bases is allocated corresponding to the free area r3.

[0071] In the fourth base layout design, in addition to the results of the third base layout design, a total of one more base is placed in the free area r4 newly allocated to the warehouse area as the fourth warehouse area design. In other words, in addition to the results of the third base layout design, the area bs1 of one base is allocated corresponding to the free area r4.

[0072] Next, the details of the processing of step St2 in Fig. 4 will be described with reference to Fig. 7 and Fig. 8. Fig. 7 is a flowchart showing in chronological order an example of the detailed procedure of the bin layout design in step St2 in Fig. 4. Fig. 8 is a diagram schematically showing an example of the outline of the processing of the bin layout design in step St23 in Fig. 7.

[0073] In FIG. 7, the processor 15 determines whether the bin layout design process is being executed for the first time (step St21). If the processor 15 determines that the bin layout design process is being executed for the first time (step St21, YES), it sets a placement constraint for placing the bins at the positions of the bases placed in step St13 of FIG. 5 (step St22). Here, for example, if the bin layout design is being executed for the first time, the processor 15 sets the placement constraint such that "the bins can reach the picking station directly." Furthermore, if this placement constraint cannot satisfy the performance index data I2 and the storage capacity of the automated warehouse AST1 is insufficient, the processor 15 sets placement constraints within the physically possible range, such as "the bins can reach the picking station within one picking operation" or "the bins can reach the picking station within two picking operations."

[0074] Note that "the bins can reach the picking station directly" means that when any bin B1 is moved to the picking station ST, the bin B1 can be moved to the picking station ST without moving any other bins B1.

[0075] "The bin can reach the picking station within one removal operation" means that when any bin B1 is moved to the picking station ST, another bin B1 is moved to clear the path to the picking station ST, thereby ensuring the path to the picking station ST for the bin B1.

[0076] "The bin can reach the picking station within two picking operations" means that two other bins B1 are moved to clear the path to the picking station ST, thereby ensuring a path for bin B1 to the picking station ST.

[0077] The processor 15 executes a bin placement design process (step St23) to place bins at the positions of the bases placed in step St13 of Fig. 5 so as to satisfy the placement constraints set in step St22. After step St23, the process of Fig. 7 by the processor 15 ends.

[0078] On the other hand, when the processor 15 determines that the execution of the bin layout design process is not the first time (step St21, NO), it determines based on the input data whether or not there is another bin layout combination that is different from the current bin layout combination and satisfies the input data (step St24). When the processor 15 determines that there is no other bin layout combination that is different from the current bin layout combination and satisfies the input data (step St24, NO), it executes the process of step St22 (i.e., re-setting the layout constraints of the bin layout). When the processor 15 determines that there is another bin layout combination that is different from the current bin layout combination and satisfies the input data (step St24, YES), it executes the process of step St23 (i.e., re-designing the bin layout).

[0079] Here, an outline of the bin layout design process in step St23 of FIG. 7 will be described with reference to FIG.

[0080] Figure 8 shows an example of the first and fourth bin placement designs when the placement constraint "the bins can reach the picking station directly" is imposed, and an example of the first and fourth bin placement designs when the placement constraint "the bins can reach the picking station within one removal operation" is imposed.

[0081] In the first bin layout design under the layout constraint that "bins can reach the picking station directly," multiple bins B1 (specifically, six bins) are arranged to surround picking station ST1, in comparison with the result of the first base layout design shown in Figure 6B. The arrangement of these bins B1 is such that the products stored in the bins B1 can reach the picking station ST1 directly. This shortens the time required for tasks such as replacing products from the bins B1 at picking station ST1.

[0082] In the fourth bin layout design under the layout constraint that "the bin can reach the picking station directly," bin B1 has not been newly placed from the results of the immediately preceding third bin layout design, i.e., bin B1 has not been newly placed from the results of the fourth base layout design shown in Figure 6B. In other words, with respect to the results of the fourth base layout design, it is not possible to newly place bin B1 that would satisfy the layout constraint that "the bin can reach the picking station directly."

[0083] Furthermore, in the first bin layout design under the layout constraint of "being able to reach the picking station within one picking operation," multiple bins (specifically, six) B1 are arranged around picking station ST1, and multiple bins (specifically, two) B1a are arranged at a greater distance from picking station ST1, compared to the results of the first base layout design shown in Figure 6B. Bin B1 is arranged so that the products stored in that bin can reach picking station ST1 directly, while bin B1a is arranged so that the products stored in that bin can reach picking station ST1 with a single picking operation. This shortens the time required for tasks such as replacing products from bins B1 and B1a at picking station ST1 while complying with the bin layout constraint.

[0084] Furthermore, in the fourth bin layout design under the layout constraint of "being able to reach the picking station within the range of one pick-up operation," bin B1 has not been newly placed from the results of the immediately preceding third bin layout design, i.e., bin B1 has not been newly placed from the results of the fourth base layout design shown in Figure 6B. In other words, with respect to the results of the fourth base layout design, it is not possible to newly place bin B1 that would satisfy the layout constraint of "being able to reach the picking station within the range of one pick-up operation."

[0085] Next, an example of the outline of the product layout optimization process in step St3 in Fig. 4 will be described with reference to Fig. 9. Fig. 9 is a diagram that schematically shows an example of the outline of the product layout optimization process in step St3 in Fig. 4. The example in Fig. 9 shows what products are stored in bin B1 as a result of the fourth bin layout design under the layout constraint that "the bins can reach the picking station directly."

[0086] Processor 15 determines that products with a high delivery (shipment) frequency are stored in the two bins Bhg1 located in the positions most accessible to picking station ST1 (i.e., the positions requiring the shortest time to reach picking station ST1). Processor 15 also determines that products with a medium delivery (shipment) frequency are stored in bin Bmd1 located in the position next most accessible to picking station ST1 (i.e., the position requiring the next shortest time to reach picking station ST1). Finally, processor 15 determines that products with a low delivery (shipment) frequency are stored in bin Blw1 located in the position least accessible to picking station ST1 (i.e., the position requiring the longest time to reach picking station ST1). In this way, based on the frequency of delivery (shipment) of a product, processor 15 determines that the product with a high delivery (shipment) frequency is placed in the bin closest to picking station ST1 in order of ease of access (i.e., the position requiring the shortest time to reach picking station ST1). This shortens the time required to transfer products from storage bins to shipping bins from picking station ST1.

[0087] Next, an example of the outline of the resource design process in step St4 of Fig. 4 will be described with reference to Fig. 10. Fig. 10 is a diagram that schematically shows an example of the outline of the resource design process in step St4 of Fig. 4. The example of Fig. 10 shows how many resources, such as transport robots, used to transport bin B1 itself will be allocated as a result of optimizing product placement in bin B1 shown in Fig. 9.

[0088] Based on input data (e.g., constraint data I5 and cost data I6), processor 15 determines how many resources can be input (introduced) that satisfy the input data for the product layout optimization processing results of step St3 in FIG. 4. Processor 15 executes resource design processing based on this determination result. In the example of FIG. 10, processor 15 determines the input (introduction) of resource RS1, consisting of a total of four AMRs, for the product layout optimization processing results corresponding to the entire area AR0. As a result, appropriate resources are input for transporting bin B1, and the processing capacity of automated warehouse AST1 is adaptively improved.

[0089] Next, an example of the conditions and results of the calculation processing for the layout design of an automated warehouse will be described with reference to Figs. 11 to 13. Fig. 11 is a diagram showing an example of conditions for the calculation processing for the layout design of an automated warehouse. Fig. 12 is a diagram showing a first example of the calculation processing result for the layout design of an automated warehouse. Fig. 13 is a diagram showing a second example of the calculation processing result for the layout design of an automated warehouse. Fig. 11 presents two different conditions (specifically, conditions 1 and 2) required for an automated warehouse. The conditions here correspond to the input data shown in Fig. 3.

[0090] The computing device 10 generates warehouse automation design data that satisfies both conditions 1 and 2. Fig. 12 shows an example of warehouse automation design data that satisfies condition 1. Fig. 13 shows an example of warehouse automation design data that satisfies condition 2.

[0091] Condition 1 corresponds to the key performance indicator (KPI) data I2, which states, "We want to keep implementation costs as low as possible. Processing capacity is a lower priority than storage capacity." In other words, as shown in the correspondence table between requirements I21 and priorities I41, in condition 1, "implementation costs" has the highest priority, "we want to increase storage capacity" has the second highest priority, and "we want to increase processing capacity" has the lowest priority. In addition, constraint data I51 for condition 1 indicates, "Construction costs must be less than 13 million yen, and the construction area must be less than 9 meters long, 11 meters wide, and 3 meters high."

[0092] On the other hand, condition 2 corresponds to the key performance indicator (KPI) data I2, which states, "We want to increase processing capacity as much as possible. Costs can be any amount as long as they are within 13 million yen." In other words, as shown in the correspondence table between requirements I22 and priorities I42, in condition 2, "We want to increase processing capacity" has the highest priority, "We want to increase storage capacity" has the second highest priority, and "We want to keep implementation costs down" has the lowest priority. Furthermore, constraint data I52 for condition 2 indicates, similar to constraint data I51 for condition 1, "Construction cost less than 13 million yen, construction area less than 9 meters in length, less than 11 meters in width, and less than 3 meters in height."

[0093] For example, according to warehouse automation design data generated by the computing device 10 according to this embodiment to satisfy condition 1 in FIG. 11, the automated warehouse has a three-story structure (see FIG. 12). Elevators EV1F1, EV2F1, and EV3F1, which are common to the first floor (1F), second floor (2F), and third floor (3F), are located in the approximate center of the warehouse area. Picking station ST2F1 is located on the second floor of the three-story structure. Bases BS1 and bins B1 are located throughout the remaining areas of the first to third floors. As resource RS2F1, approximately four AMRs are deployed (placed) on the second floor where picking station ST2F1 is located. This allows the computing device 10 to generate warehouse automation design data that satisfies each of the performance indicators of condition 1 (specifically, initial cost, storage capacity [number of bins], and processing capacity [orders / hour]).

[0094] For example, according to warehouse automation design data generated by the computing device 10 according to this embodiment so as to satisfy condition 2 in FIG. 11, the automated warehouse has a three-story structure (see FIG. 13). Two elevators (specifically, elevators EV1F2, EV2F2, and EV3F2, and elevators EV1F1, EV2F1, and EV3F1) that can be used commonly on the first floor (1F), second floor (2F), and third floor (3F) are located approximately in the center of the warehouse area. Two picking stations ST2F1 and ST2F2 are located adjacent to the second floor of the three-story structure. Bases BS1 and bins B1 are located throughout the rest of the first to third floors. As resource RS2F1, approximately four AMRs are deployed (placed) on the second floor where picking station ST2F1 is located. As resource RS2F2, approximately four AMRs are deployed (placed) on the second floor where picking station ST2F2 is located. As a result, the computing device 10 can generate warehouse automation design data that satisfies each of the performance indicators of Condition 2 (specifically, initial cost, storage capacity [number of bins], and processing capacity [orders / hour]).

[0095] Summary of the Disclosure The above description of the embodiments discloses technical concepts corresponding to the following items.

[0096] (Item 1) The layout generation method according to the present disclosure acquires input data including work plan data for work to be performed in an automated warehouse that can be configured by combining multiple bases, first performance index data indicating the goals of the automated warehouse, and constraint data for the automated warehouse; generates layout design data for the automated warehouse that is configured by arranging the multiple bases based on the input data; calculates second performance index data that indicates the performance index of the automated warehouse that corresponds to the layout design data based on the layout design data; and repeats the generation of the layout design data until the second performance index data satisfies the first performance index data. As a result, the layout generation method can generate an optimal layout for an automated warehouse that satisfies not only the constraints related to the automated warehouse but also the performance of the automated warehouse desired by the user.

[0097] (Item 2) In the layout generation method described in Item 1, in generating the layout design data, at least a first arrangement is performed in which a plurality of bases of the automated warehouse are arranged as first bases among the plurality of bases, a second arrangement is performed in which bins for storing products to be stored by the automated warehouse are arranged on some of the bases as second bases among the plurality of bases, and a third arrangement is performed in which products are arranged in the bins as third bases among the plurality of bases. As a result, the layout generation method allows the layout to be created in order of the elements that occupy the largest area, such as the base that forms the foundation of the automated warehouse, the bins that are placed on the base, and the products that are stored in the bins, thereby supporting efficient layout design.

[0098] (Item 3) In the layout generation method described in item 1 or 2, the input data further includes resource data including parameters of movable resources that move within the automated warehouse, and in generating the layout design data, a fourth arrangement is further performed in which the movable resources are linked to and assigned to a fourth base based on the first arrangement as a fourth base among the plurality of bases. As a result, the layout generation method makes it possible to appropriately arrange movable resources such as transport robots for transporting bins such as AMRs to picking stations, thereby helping to improve the processing capacity within the automated warehouse.

[0099] (Item 4) In the layout generation method described in any one of items 1 to 3, if the second performance index data does not satisfy the first performance index data during generation of the layout design data, the fourth arrangement is executed to reallocate the movable resources based on the resource data. As a result, according to the layout generation method, even if the warehouse automation design data once generated does not satisfy the predetermined performance indicators required for an automated warehouse, the warehouse automation design data can be generated efficiently by redesigning the number of movable resources to be placed, etc., starting with the movable resources that are easiest to redesign.

[0100] (Item 5) In the layout generation method described in any one of items 1 to 4, when the second performance index data does not satisfy the first performance index data and reallocation of the movable resources is not possible during generation of the layout design data, the second placement is executed to rearrange the bins. As a result, according to the layout generation method, if the warehouse automation design data once generated does not satisfy the predetermined performance indicators required for an automated warehouse and redesign of the movable resources is not possible, warehouse automation design data can be generated efficiently by redesigning the number and location of bins, which are the next easiest to redesign after the movable resources.

[0101] (Item 6) In the layout generation method described in any one of items 1 to 5, when the second performance index data does not satisfy the first performance index data in generating the layout design data and reallocation of the movable resources and rearrangement of the bins is not possible, the first arrangement is executed to rearrange the base. As a result, according to the layout generation method, if the warehouse automation design data once generated does not satisfy the predetermined performance indicators required for an automated warehouse and it becomes impossible to redesign the movable resources and bins, it is possible to efficiently generate warehouse automation design data by redesigning the number and location of bases that are next easiest to redesign after the movable resources and bins.

[0102] (Item 7) In the layout generation method according to any one of items 1 to 6, the input data further includes cost data on the cost required to introduce items corresponding to the plurality of bases. As a result, the layout generation method can efficiently generate warehouse automation design data that satisfies users within a limited budget for the introduction of a new automated warehouse or for renovation or other remodeling.

[0103] (Item 8) In the layout generation method described in any one of items 1 to 7, when there are multiple pieces of the first performance index data, the input data further includes priority data indicating the first performance index data with the highest priority among the multiple pieces of the first performance index data. As a result, the layout generation method can efficiently generate warehouse automation design data that is specialized and satisfactory for any one of the key performance indicator (KPI) data that should be prioritized when multiple key performance indicator (KPI) data are provided.

[0104] (Item 9) A layout generation device according to the present disclosure includes a processor and a memory, and the processor cooperates with the memory to acquire input data including work plan data for work to be performed in an automated warehouse that can be configured by combining multiple bases, first performance index data indicating goals for the automated warehouse, and constraint data for the automated warehouse, generates layout design data for the automated warehouse that is configured by arranging the multiple bases based on the input data, calculates second performance index data that indicates performance indexes for the automated warehouse that correspond to the layout design data based on the layout design data, and repeats generating the layout design data until the second performance index data satisfies the first performance index data. This allows the layout generation device to generate an optimal layout for an automated warehouse that satisfies not only the constraints related to the automated warehouse but also the performance of the automated warehouse desired by the user.

[0105] (Item 10) A program according to the present disclosure causes a layout generation device, which is a computer, to execute the following processes: acquiring input data including work plan data for work to be performed in an automated warehouse that can be configured by combining multiple bases, first performance index data indicating goals for the automated warehouse, and constraint data for the automated warehouse; generating layout design data for the automated warehouse configured by arranging the multiple bases based on the input data; calculating second performance index data indicating performance indexes for the automated warehouse that correspond to the layout design data based on the layout design data; and repeating the generation of the layout design data until the second performance index data satisfies the first performance index data. This allows the layout generation device to generate an optimal layout for an automated warehouse that satisfies not only the constraints related to the automated warehouse but also the performance of the automated warehouse desired by the user.

[0106] Although the embodiments have been described above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art can conceive of various modifications, alterations, substitutions, additions, deletions, and equivalents within the scope of the claims, and it is understood that these also fall within the technical scope of the present disclosure. Furthermore, the components in the above-described embodiments may be combined in any manner without departing from the spirit of the invention.

[0107] This application is based on a Japanese patent application (Patent Application No. 2024-017290) filed on February 7, 2024, the contents of which are incorporated herein by reference. [Industrial Applicability]

[0108] The technology disclosed herein is useful as a layout generation method, layout generation device, and program that generate an optimal layout for an automated warehouse that satisfies not only the constraints related to the automated warehouse but also the performance of the automated warehouse desired by a user. [Explanation of symbols]

[0109] 10 Computing equipment 11 Communication I / F 12 Memory 13 Input Devices 14 Display Devices 15 processors 16 Data Acquisition Section 17 Automated Warehouse Layout Design Department 18 Model Generation Unit 19 Performance Evaluation Department 20 External Databases 100 Layout Generation System

Claims

1. acquiring input data including work plan data for work to be performed in an automated warehouse that can be configured by combining a plurality of bases, first performance index data indicating a target for the automated warehouse, and constraint data for the automated warehouse; Based on the input data, layout design data for the automated warehouse configured by arranging the plurality of bases is generated by performing a first arrangement in which a plurality of bases of the automated warehouse are arranged as a first base among the plurality of bases, a second arrangement in which bins for storing products to be stored in the automated warehouse are arranged on some of the bases as a second base among the plurality of bases, and a third arrangement in which products are arranged in the bins as a third base among the plurality of bases, calculating second performance index data indicating a performance index of the automated warehouse corresponding to the layout design data based on the layout design data; repeating the generation of the layout design data until the second performance index data satisfies the first performance index data; Layout generation method.

2. The input data further includes resource data including parameters of movable resources that move within the automated warehouse; In generating the layout design data, performing a fourth allocation of the movable resources by linking them to a fourth base among the plurality of bases based on the first allocation; 2. The layout generation method of claim 1.

3. In generating the layout design data, If the second performance index data does not satisfy the first performance index data, the fourth allocation is performed to reallocate the movable resources based on the resource data.

3. The layout generating method according to claim 2.

4. In generating the layout design data, When the second performance index data does not satisfy the first performance index data and the reallocation of the movable resources is not possible, the second allocation is performed to reallocate the bins.

4. The layout generating method according to claim 3.

5. In generating the layout design data, When the second performance index data does not satisfy the first performance index data and the reallocation of the movable resources and the reallocation of the bins are impossible, the first reallocation is performed to reallocate the base.

5. The layout generating method according to claim 4.

6. The input data further includes cost data on the cost required to introduce the items corresponding to the plurality of bases.

2. The layout generation method of claim 1.

7. When there are a plurality of the first performance index data, the input data further includes priority data indicating the first performance index data with the highest priority among the plurality of the first performance index data.

2. The layout generation method of claim 1.

8. A processor and a memory, the processor cooperates with the memory; acquiring input data including work plan data for work to be performed in an automated warehouse that can be configured by combining a plurality of bases, first performance index data indicating a target for the automated warehouse, and constraint data for the automated warehouse; Based on the input data, layout design data for the automated warehouse configured by arranging the plurality of bases is generated by performing a first arrangement in which a plurality of bases of the automated warehouse are arranged as a first base among the plurality of bases, a second arrangement in which bins for storing products to be stored in the automated warehouse are arranged on some of the bases as a second base among the plurality of bases, and a third arrangement in which products are arranged in the bins as a third base among the plurality of bases, calculating second performance index data indicating a performance index of the automated warehouse corresponding to the layout design data based on the layout design data; repeating the generation of the layout design data until the second performance index data satisfies the first performance index data; Layout generator.

9. A layout generating device, which is a computer, A process of acquiring input data including work plan data for work to be performed in an automated warehouse that can be configured by combining a plurality of bases, first performance index data that indicates a target for the automated warehouse, and constraint data for the automated warehouse; a process of generating layout design data for the automated warehouse configured by arranging the plurality of bases based on the input data by performing a first arrangement of arranging a plurality of bases of the automated warehouse as a first base among the plurality of bases, a second arrangement of arranging bins for storing products to be stored in the automated warehouse on some of the bases as a second base among the plurality of bases, and a third arrangement of arranging products in the bins as a third base among the plurality of bases; a process of calculating second performance index data indicating a performance index of the automated warehouse corresponding to the layout design data based on the layout design data; a process of repeating generation of the layout design data until the second performance index data satisfies the first performance index data; program.

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