Simulation model generation method, simulation model generation program, and simulation model generation system

Abstract

To suppress a load on generation of a simulation model by efficiently collecting simulation information.SOLUTION: A simulation model generation method includes: executing by an arithmetic device data-communicably connected to a warehouse management system for managing an inventory state of articles stored in a warehouse; acquiring simulation information; and generating a simulation model for managing business in a simulation target warehouse based on the simulation information. The simulation information includes any one of at least first data to be acquired from a warehouse management system, second data generated by using the first data, third data based on data acquired from a related system other than the warehouse management system, and fourth data which is a predetermined standard value. When at least a portion of the information necessary for generating the simulation model is not included in any of the first data to the fourth data, shortage information indicating a shortage is output.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present disclosure relates to a simulation model generation method, a simulation model generation program, and a simulation model generation system. [Background technology]

[0002] Conventionally, a large number of items are managed in warehouses such as distribution centers for goods, and operations such as picking of items are performed according to request. Patent Document 1 discloses a configuration for optimizing pallet transport allocation by executing simulations in order to improve the performance of a guided vehicle system in an automated warehouse that receives and delivers goods. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2020-111455 Summary of the Invention [Problem to be solved by the invention]

[0004] A simulation model for managing warehouse operations is considered to be effective in optimizing warehouse operations such as picking. However, to generate a simulation model for managing warehouse operations, it is necessary to collect simulation information such as the warehouse layout, the shelves in the warehouse, and the quantity and type of goods, etc., depending on the warehouse to be simulated. Patent Document 1 does not mention how to efficiently collect simulation information.

[0005] The present disclosure aims to efficiently collect simulation information and reduce the load on generating a simulation model. [Means for solving the problem]

[0006] The present disclosure provides a simulation model generation method executed by a computing device connected to a warehouse management system for managing the inventory status of items stored in each of a plurality of warehouses so as to enable data communication, the simulation model generation method acquiring simulation information and generating a simulation model for managing operations in the warehouse to be simulated based on the simulation information, the simulation information including at least first data acquired from the warehouse management system, second data generated using the first data, third data based on data acquired from a related system other than the warehouse management system, and fourth data which is a predetermined standard value, and if at least a portion of the information required to generate the simulation model is not included in any of the first data to the fourth data, the simulation model generation method outputs missing information indicating this.

[0007] The present disclosure also provides a simulation model generation program that acquires simulation information in a computing device, which is a computer connected for data communication with a warehouse management system that manages the inventory status of items stored in each of a plurality of warehouses, and generates a simulation model for managing operations in the warehouse to be simulated based on the simulation information, wherein the simulation information includes at least first data acquired from the warehouse management system, second data generated using the first data, third data based on data acquired from a related system other than the warehouse management system, and fourth data that is a predetermined standard value, and if at least a portion of the information required to generate the simulation model is not included in any of the first data to the fourth data, outputs missing information to notify this fact.

[0008] The present disclosure also provides a simulation model generation system executed by a computing device connected to a warehouse management system capable of data communication with the warehouse management system that manages the inventory status of items stored in each of a plurality of warehouses, wherein the computing device acquires simulation information and generates a simulation model for managing operations in the warehouse to be simulated based on the simulation information, and the simulation information includes at least any of first data acquired from the warehouse management system, second data generated using the first data, third data based on data acquired from a related system other than the warehouse management system, and fourth data that is a predetermined standard value, and when at least a portion of the information required to generate the simulation model is not included in any of the first data to the fourth data, the simulation model generation system outputs missing information to notify this fact. [Effects of the Invention]

[0009] According to the present disclosure, it is possible to efficiently collect simulation information and reduce the load on generating a simulation model. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram showing a configuration example of a simulation model generation system according to an embodiment. [Figure 2] FIG. 1 is a block diagram showing an example of the configuration of a computing device according to an embodiment. [Figure 3] FIG. 1 is a diagram illustrating data types according to an embodiment. [Figure 4] 1 is a sequence diagram of a process of a simulation model generation system according to an embodiment; [Figure 5] FIG. 1 is a diagram showing an example of a use case and a required data type according to an embodiment. [Figure 6] FIG. 10 is a diagram showing an example of stages of a user simulation and the types of data required according to an embodiment. [Figure 7]1 is a table showing data before and after conversion processing by the arithmetic device according to an embodiment; [Figure 8] Schematic diagram showing a simulation model according to an embodiment. [Figure 9] Flowchart of processing of a warehouse management system according to an embodiment [Figure 10] Flowchart of data conversion processing according to an embodiment [Figure 11] Flowchart of slot information conversion process according to an embodiment [Figure 12] Flowchart of path information generation processing according to the embodiment [Figure 13] FIG. 1 is a schematic diagram illustrating a path information generation process according to an embodiment; [Figure 14] Flowchart of area information generation processing according to an embodiment [Figure 15] FIG. 1 is a schematic diagram for explaining a region information generation process according to an embodiment; [Figure 16] Flowchart of wall information generation processing according to an embodiment [Figure 17] FIG. 1 is a schematic diagram illustrating a wall information generation process according to an embodiment; [Figure 18] Flowchart of picklist generation processing according to an embodiment [Figure 19] Flowchart of inventory information generation process according to an embodiment [Figure 20] 1 is a flowchart of a simulation model generation and simulation execution process according to an embodiment; [Figure 21] Schematic diagram showing an example of a simulation result according to an embodiment. [Figure 22] Schematic diagram showing an example of a simulation result according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, with reference to the accompanying drawings as appropriate, detailed descriptions of embodiments specifically disclosing a simulation model generation method, a simulation model generation program, and a simulation model generation system 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 recited in the claims.

[0012] <Embodiment> [System Configuration] 1 is a block diagram showing an example configuration of a simulation model generation system 1 according to a first embodiment. The simulation model generation system 1 includes a calculation device 2 and at least one warehouse management system 3-1,...,3-s (s: an integer equal to or greater than 2). The simulation model generation system 1 is a system that supports consideration of business optimization by having the calculation device 2 automatically generate a simulation model for managing warehouse operations based on warehouse information stored in the warehouse management systems 3-1 to 3-s.

[0013] The arithmetic device 2 is configured using a general-purpose computer device (for example, a personal computer, a server computer). The arithmetic device 2 is connected to one or more warehouse management systems 3 so as to enable input and output of data. The arithmetic device 2 may be connectable to a user terminal (for example, a PC) (not shown).

[0014] The warehouse management system 3-1 is a system for managing the inventory status of items managed in a warehouse and the transport of items into and out of the warehouse. The warehouse management system 3-1 may also be referred to as a Warehouse Management System (hereinafter referred to as "WMS"). The warehouse management system 3-1 may be capable of managing one or more warehouses and may be connectable to warehouse personal computers (hereinafter referred to as "PCs") 4-1-1, ..., 4-1-m (m: an integer of 2 or greater) for warehouse management. Other warehouse management systems are similar to the warehouse management system 3-1. For example, the warehouse management system 3-s may be connectable to warehouse PCs 4-s-1, ..., 4-sn (n: an integer of 2 or greater).

[0015] Transportation and delivery management systems 31-1, ..., 31-s (s: integer equal to or greater than 2), which are related systems other than the warehouse management systems 3-1 to 3-s, are systems for managing means of transporting and delivering items managed in warehouses. For example, they manage when and which warehouse a shipment departs from, which items are transported, and when and which other warehouse it will arrive at. Transportation and delivery management system 31-1 may also be referred to as a Transport Management System (hereinafter referred to as "TMS"). In addition to the transportation and delivery management systems (TMS) 31-1, ..., 31-s, related systems may also include a management system for managing video footage taken inside a warehouse, a warehouse layout management system, a VSLAM (Visual Localization and Mapping) management system, or a worker management system for managing worker performance.

[0016] The warehouse PC 4-1-1 is installed, for example, in a warehouse (not shown) and records the inventory status of items managed in the warehouse. The warehouse PC 4-1-1 may record the inventory status in real time by receiving various data from a terminal such as a handheld terminal. The warehouse PC 4-1-1 is also connectable to the warehouse management system 3-1 and can transmit the inventory status of items managed in the warehouse to the warehouse management system 3-1. Other warehouse PCs are similar to the warehouse PC 4-1-1. For example, the warehouse PC 4-s-1 may be connectable to the warehouse management system 3-s. The warehouse PCs 4-1-1 to 4-1-m and the warehouse PCs 4-s-1 to 4-sn may be installed in different warehouses. In the following description, the warehouse management system 3-1 and warehouse PC 4-1-1 are used when the warehouse management system and warehouse PC need to be described individually, and the reference numerals are omitted when the warehouse management system and warehouse PC are described together.

[0017] 2 is a block diagram showing the hardware configuration of the arithmetic device 2 according to embodiment 1. The arithmetic device 2 includes a central processing unit (hereinafter referred to as "CPU") 5, a memory 6, a storage device 7, an input / output unit 8, a communication unit 9, and an external interface unit 10. The components of the arithmetic device 2 are communicatively connected via an internal bus 11.

[0018] The CPU 5 realizes various functions by reading and executing various data and programs stored in the memory 6 or the storage device 7. The CPU 5 may be another arithmetic circuit such as a Micro Processing Unit (hereinafter referred to as "MPU"), a Digital Signal Processor (hereinafter referred to as "DSP"), a Graphical Processing Unit (hereinafter referred to as "GPU"), or a Field Programmable Gate Array (hereinafter referred to as "FPGA"), or may be used in combination with other arithmetic circuits.

[0019] The memory 6 is configured using volatile / non-volatile storage devices such as Random Access Memory (hereinafter referred to as "RAM") and Read Only Memory (hereinafter referred to as "ROM"), and temporarily stores programs and data required to execute the operation of the arithmetic unit 2, as well as data or information generated during operation. The RAM is, for example, a work memory used when the arithmetic unit 2 is operating. The ROM stores and holds, in advance, programs and data for controlling the arithmetic unit 2, for example.

[0020] The storage device 7 is a storage area for storing and holding various data and programs, and is configured by, for example, a hard disk drive (hereinafter referred to as "HDD") or a solid state drive (hereinafter referred to as "SSD").

[0021] The input / output unit 8 receives instructions from the user via, for example, a keyboard and a mouse (not shown), etc. The input / output unit 8 also outputs various information via, for example, a display (not shown), etc.

[0022] The communication unit 9 communicates with an external device, such as a warehouse management system or a user terminal (not shown), via a network (not shown), to transmit and receive various data or signals. The communication unit 9 may support both wired and wireless communication. The communication method used by the communication unit 9 may be, for example, a Wide Area Network (hereinafter referred to as "WAN"), a Local Area Network (hereinafter referred to as "LAN"), Long Term Evolution (hereinafter referred to as "LTE"), mobile communication such as 5G, power line communication, short-range wireless communication such as Wi-Fi (registered trademark) and Bluetooth (registered trademark), or a combination of these.

[0023] The external interface unit 10 is an interface for transmitting and receiving data to and from an external device. The warehouse management system may also be realized with the same hardware configuration as the arithmetic device 2.

[0024] [Data type] The types of data used by the simulation model generation system 1 for generating a simulation model will be described with reference to Fig. 3. Fig. 3 is a diagram illustrating data types according to an embodiment.

[0025] The types of simulation data used by the simulation model generation system 1 to generate a simulation model include data obtained using data acquired from a warehouse management system and data that is not. Data obtained using data acquired from a warehouse management system and that can be used as is without the need for processing (calculation, calculation, etc.) is referred to as data A. Data obtained using data acquired from a warehouse management system and that cannot be used as is and that requires processing (calculation, calculation, etc.) is referred to as data B. In the case of data that cannot be generated using data acquired from the warehouse management system, data obtained from a related system other than the warehouse management system (for example, a transportation and delivery management system), or data newly generated using that data, is referred to as data C. In the case of a data type that cannot be used even with data acquired from a related system, data that is a predetermined fixed standard value is referred to as data D. Furthermore, in the case where the standard value cannot be used either, data obtained by interviewing a user or the like is referred to as data E.

[0026] [Processing Sequence] The processing sequence of the simulation model generation system 1 according to the first embodiment will be described with reference to Fig. 4. Fig. 4 is a sequence diagram of the processing of the simulation model generation system according to the embodiment. Each processing sequence is performed in cooperation with the arithmetic device 2 and the warehouse management system. However, some processing in the sequence may be performed based on a user operation.

[0027] When the calculation device 2 receives a request from a user (warehouse operator) to visualize a warehouse to be simulated, the calculation device 2 determines the requirements for the simulation (SIM) (step St1). At this time, if the target warehouse is clear, the calculation device 2 may also receive, for example, the name, address, and identification number, such as an ID, of the warehouse to be simulated in order to identify it. This input may be made directly to the calculation device 2 or from a user terminal (not shown). Here, it is assumed that a warehouse PC 4-1-1 is installed in the simulation target warehouse and that the simulation target warehouse is managed by a warehouse management system 3-1. Then, the calculation device 2 determines the requirements for the simulation. The requirements will be described in detail later, but include use cases, variables, and targets to be reproduced in the simulation. The information required as simulation information may be determined according to the specification of the simulation target warehouse received by user operation.

[0028] The arithmetic device 2 determines the type of data required to generate a simulation model based on the input of step St1 (step St2). The determination of the data type will be described later. Then, it determines whether the data from the warehouse management system is usable (step St3). That is, it determines whether the data is A data, B data, or any of C to E data in FIG. 3. If the data from the warehouse management system is usable (step St3: YES), it requests the necessary data from the warehouse management system and acquires the data.

[0029] The calculation device 2 then determines whether the data acquired from the warehouse management system needs to be processed (calculated) to obtain the data required for generating a simulation model (step St4). Data processing will be described later. If the data needs to be processed (step St4: YES), it is processed (step St5) and used as data B. If the data does not need to be processed (step St4: NO), it is used as data A. Then, the process returns to just before step St3.

[0030] If the data from the warehouse management system is not available (step St3: NO), it is determined whether data from the related system is available (step St6). That is, it is determined whether it is data C, D, or E in Figure 3. If the data from the related system is available (step St6: YES), the necessary data is requested from the related system and the data is acquired.

[0031] The calculation device 2 then determines whether processing (calculation) of the data acquired from the related system is necessary to obtain the data required for generating the simulation model (step St7). The data processing here is the same as that for data acquired from the warehouse management system. If data processing is necessary (step St7: YES), the data is processed (step St8) and used as C data. If data processing is not necessary (step St7: NO), the data is also used as C data. Then, the process returns to just before step St3.

[0032] Furthermore, if data from neither the warehouse management system nor the related systems is available (step St6: NO), it is determined whether standard data is available (step St9). If standard data is available (step St9: YES), the standard data is used as D data. Furthermore, if none of the warehouse management system data, related system data, or standard data is available (step St9: NO), it is used as E data. If there is necessary data for which the data type (A data, B data, ..., D data) has not been determined, the process from step St3 is repeated for that necessary data to determine the data type.

[0033] If there is necessary data whose data type is E data (step St10: YES), missing information notifying that fact is output. The missing information may be output by any output method, such as display on the input / output unit 8, or by voice. The missing information may include information indicating that it is necessary to inquire of the user of the simulation model about the answers to the missing information. Furthermore, when the missing information is output, questions to be inquired of the user of the simulation model may be output. In this case, an email may be automatically sent to the user, or a system may be created in which questions are automatically asked to the user when the missing information is output. Furthermore, the information required as simulation information may be determined according to the specification of the warehouse to be simulated received by user operation.

[0034] If there is no necessary data of the data type E data (step St10: NO), or if the specific content of the E data is determined by an inquiry to the user, etc., all necessary data is gathered, and a simulation model is automatically generated based on the collected data (step St11). When the generation of the simulation model is completed, the arithmetic device 2 notifies the user to that effect. The arithmetic device 2 may notify the user via the input / output unit 8, such as a display (not shown), for example.

[0035] When instructed by a user, the arithmetic unit 2 executes a simulation based on the generated simulation model.

[0036] When the executed simulation is completed, the arithmetic unit 2 outputs the simulation result. The arithmetic unit 2 may display the simulation result on a display (not shown), for example. The arithmetic unit 2 may also output the simulation result as a text file, for example.

[0037] In this way, among data A to E, data A should be used with the highest priority, followed by data B, data C, and data D, with data E having the lowest priority. However, depending on the use case, the priority may be changed, such as giving data C the highest priority.

[0038] In this way, a simulation model generation method executed by a computing device 2 communicably connected to a warehouse management system that manages the inventory status of items stored in each of multiple warehouses acquires simulation information (at least one of data A to E) and generates a simulation model for managing operations in the warehouse to be simulated based on the simulation information. The simulation information includes at least first data (data A) acquired from the warehouse management system, second data (data B) generated using the first data (data A), third data (data C) based on data acquired from a related system other than the warehouse management system (e.g., a transportation and delivery management system), and fourth data (data D) that is a predetermined standard value. If at least some of the information required to generate the simulation model is not included in the first to fourth data (data A to D), missing information indicating this is output (customer interview process). This minimizes inquiries to users to gather simulation information and reduces the burden on generating the simulation model.

[0039] Furthermore, a simulation model generation method executed by a computing device 2 communicably connected to a warehouse management system that manages the inventory status of items stored in each of multiple warehouses may acquire simulation information (at least one of data A to E), generate a simulation model for managing operations in a warehouse to be simulated based on the simulation information, and enable selection of a set of data required for the simulation information. At least a portion of the set of data required for the simulation information may be acquired from the warehouse management system. The set of data required for the simulation information may also be selected based on a use case of the simulation system. The simulation information may include at least first data (data A) acquired from the warehouse management system, second data (data B) generated using the first data (data A), third data (data C) based on data acquired from a related system other than the warehouse management system, or fourth data (data D) that is a predetermined standard value. This allows appropriate selection of the source and method of acquisition of simulation information required for various types of simulation models, thereby enabling efficient generation of simulation models.

[0040] Furthermore, a simulation model generation method executed by a computing device communicably connected to a warehouse management system that manages the inventory status of items stored in multiple warehouses acquires simulation information (at least one of data A to E) and generates a simulation model for managing operations in the warehouse to be simulated based on the simulation information. The simulation information includes first data (data A) acquired from the warehouse management system, second data (data B) generated using at least the first data (data A), third data (data C) based on data acquired from a related system other than the warehouse management system, and fourth data (data D) that is a predetermined standard value. If the first data (data A) overlaps with at least one of the second through fourth data (data B to D) for the same data type, the first data (data A) may be adopted. This allows for the generation of a more reliable simulation model by preferentially utilizing simulation information considered to be more reliable. The order of priority may be data A, data B, data C, and data D.

[0041] In addition, a simulation model generation method executed by a computing device connected for data communication with a warehouse management system that manages the inventory status of items stored in each of multiple warehouses may acquire simulation information (at least one of data A to E), generate a simulation model for managing operations in the warehouse to be simulated based on the simulation information, and enable the user to select whether to use variable values ​​(data A to C) or a predetermined standard value (data D) as the simulation information. This allows the use of simulation data according to the accuracy required and appropriate for each simulation model, and enables the generation of simulation models at an appropriate speed.

[0042] [Use case and required data] Next, an example of data required for each use case is described. FIG. 5 is a diagram illustrating an example of use cases and required data types according to an embodiment. As shown in FIG. 5, a simulation use case may be, for example, "optimizing the number of pickers in a warehouse where workers are primarily involved," and the desired outcome may be, for example, "finding the minimum number of people required to complete a series of picklists within X time." A set of data required for this purpose (here, a data set consisting of 10 pieces of data) is shown. In other words, the set of data required to generate a simulation model as simulation information can be selected based on at least one of the use case, variables, and the target to be reproduced in the simulation. The options for simulation information include at least the aforementioned data A to E.

[0043] Let's say one of the required data is shelf information, and it can be acquired as either data A or data C. In this case, data A, which is marked with a double circle in Figure 5, takes priority. That is, the priority order is applied as explained in Figure 4, and data A should be used with the highest priority, and data E should be given the lowest priority. The priority order of data A to E may be changed. That is, in this case, when data A overlaps with at least one of data B to D for the same data type, data A should be used with priority.

[0044] Furthermore, the related system when utilizing C data differs depending on the type of data required. In the case of a "waiting area (work start position)" or a "loading area (work end position)" that utilizes C data, the calculation device 2 can acquire the C data by linking with a warehouse layout management system or a VSLAM management system as a related system. Furthermore, depending on the type of data required, D data, which is a standard value, is utilized. In other words, whether the required data is a standard value or not depends on the required data, which is determined by the use case, variable factors, and the target to be reproduced in the simulation.

[0045] The above explanation was given using the example use case of "optimizing the number of pickers in a warehouse where people mainly work," but the same applies to the remaining five use cases in Fig. 5 and other use cases.

[0046] [Simulation steps and required data] Next, the stages of a simulation and the necessary data will be described. FIG. 6 is a diagram showing an example of a user's stage of a simulation and the types of necessary data according to an embodiment. Simulation users have different stages in their reasons for needing a simulation, such as the "unconsideration stage (e.g., not yet considering introducing a simulation)," the "initial investigation stage (wanting to know what can generally be achieved by introducing a simulation)," the "introduction consideration stage (wanting to know what can be achieved by introducing a simulation for a specific implementation target (a target to be reproduced in the simulation))," the "introduction preparation stage (wanting to clarify the required specifications for a specific implementation target)," and the "operation stage (when additional requests arise based on knowledge gained from previous operations)." The simulation model that can be presented to the user differs depending on the stage, as shown in FIG. 6. The type of data required for generating a simulation model also differs depending on the stage (fixed values ​​(data D) or other data (data A to C, E)). In other words, the usable data A to E differ depending on the stage. Therefore, it is recommended to generate a simulation using data (standard values) appropriate for the simulation stage.

[0047] [Warehouse Information] Next, we will explain how to process the data obtained from the warehouse management system. Figure 7 is a table diagram showing warehouse information (data A) before data conversion processing by the calculation device 2 and converted warehouse information (data B) after data conversion processing. The warehouse information obtained by the warehouse management system 3-1 is slot information for each slot that makes up all the slots in the warehouse to be simulated. In this specification, a slot refers to the smallest unit of storage space for items, separated by partitions or shelves on shelves installed in the warehouse. Therefore, one shelf may include multiple slots. Each slot in the warehouse is provided with slot information corresponding to that slot, regardless of whether or not an item is stored therein.

[0048] The slot information includes data such as a slot ID, slot position, slot size, pick position, pick order, and pick zone ID. The slot ID is an identifier for the slot, and a different slot ID is assigned to each slot. The slot position indicates the three-dimensional position of the slot in the warehouse and is expressed, for example, using three-dimensional coordinates. The slot size indicates the size of the slot and is expressed, for example, using the distance between two points in three-dimensional coordinate space. The pick position indicates the three-dimensional position when a worker picks an item stored in the slot and is expressed, for example, using three-dimensional coordinates. The pick order indicates the order in which a worker picks items stored in the slot and is expressed, for example, by a number. A worker performs work (e.g., picking an item placed in the slot) on slots that have been assigned the same pick zone ID.

[0049] In this specification, slot information is described as including a slot ID, slot position, slot size, pick position, pick order, and pick zone ID. However, the data structure and data name of the slot information may differ for each warehouse management system. For example, even if the warehouse management system 3-1 and the warehouse management system 3-s store the same type of information, the data structure and data name of the information stored by each system may be different. Because warehouse management systems are provided by various companies, the data format may differ for each warehouse management system. Similarly, even for each warehouse PC managed by the same warehouse management system, the data structure of the slot information for the warehouse managed by that warehouse PC may differ. Therefore, the data structure and data name of the slot information transmitted from the warehouse management system to the computing device 2 are not limited to the slot ID, slot position, slot size, pick position, pick order, and pick zone ID, as long as they include data equivalent to these.

[0050] The converted warehouse information obtained by the data processing executed in step St5 of FIG. 4 includes converted slot information, aisle information, wall information, area information, picklist, and inventory information. The slot information transmitted from the warehouse management system to the computing device 2 may have different data structures for each warehouse management system or warehouse PC. Therefore, when automatically generating a simulation model, the computing device 2 generalizes (in other words, standardizes) the information through data conversion processing. This makes it possible to automatically generate a simulation model based on the generalized information obtained from any of the warehouse management systems 3-1 to 3-s.

[0051] The converted slot information includes the converted slot ID, converted slot position, converted slot size, and converted pick position as data. The converted slot ID is an anonymized slot ID. The anonymization process prevents customer information, etc. from being obtained from the slot ID. An example of a converted slot ID is an integer value such as "00001." The converted slot position is the slot position modified for the automatic generation of the simulation model. The converted slot size is the slot size expressed in the distance unit system used in the simulation model. For example, the converted slot size is expressed in meters. The converted pick position is the pick position modified in accordance with the modification of the slot position to the converted slot position.

[0052] The aisle information includes data such as the aisle ID, start and end positions, aisle width, and whether or not there is a one-way restriction. Workers move through the aisles that exist within the warehouse to perform their work. The aisle ID is an identifier for the aisle. The start and end positions indicate the start and end points of the aisle and are expressed, for example, as two-dimensional coordinates. The aisle width indicates the width of the aisle. Whether or not there is a one-way restriction indicates whether the aisle is one-way.

[0053] The wall information includes data such as a wall ID, start and end point positions, wall height, and visibility. The wall ID is an identifier for a wall that exists within the warehouse. The start and end point positions indicate the positions of the ends corresponding to the horizontal start and end points of the wall, and are expressed, for example, in two-dimensional coordinates. The wall height indicates the height of the wall. The visibility indicates whether the wall is visible.

[0054] The area information further includes three pieces of information: a waiting area, a loading area, and a warehouse area, and each of these three pieces of information includes the start and end points as data. The warehouse area defines the area of ​​the entire warehouse to be simulated that is generated as a simulation model. The waiting area is an area where workers wait before starting work. The loading area is an area where workers perform loading work to ship one or more items picked by the worker from the warehouse to be simulated. The waiting area and loading area are each part of the warehouse area.

[0055] A pick list contains the following data: pick list ID, conversion slot ID, item ID, and number of pick items. Here, an item refers to an item stored in a slot. The pick list contains information about which item a worker should pick from which shelf (slot). Workers perform picking work based on the pick list. The pick list ID is the identifier of the pick list. The item ID is the identifier of the item. The number of pick items indicates the quantity of items to be picked.

[0056] The inventory information includes the conversion slot ID, item ID, and the number of inventory items. The number of inventory items indicates the number of items in stock before the simulation is run.

[0057] [Simulation model example] FIG. 8 shows a 3D model 30 of a warehouse generated in cyberspace based on the converted warehouse information. FIG. 8 is a schematic diagram illustrating a simulation model according to an embodiment. The 3D model 30 is a visualization of a warehouse to be simulated. The 3D model 30 includes multiple shelves 31, multiple aisles 32, a waiting area 33, a loading area 34, a warehouse area 35, walls 36-1, 36-2, 36-3, 36-4, and a worker 37. In the 3D model 30, the shelf 31 is generated based on slot information. The shelf 31 includes multiple slots, and items are stored in each slot based on inventory information. The aisle 32 is generated based on the aisle information. The waiting area 33, the loading area 34, and the warehouse area 35 are generated based on area information. The walls 36-1 to 36-4 are generated to surround the entire warehouse based on the wall information. The worker 37 works based on a picklist during the simulation. The worker 37 may be represented by a person, or may be represented by a material handling vehicle such as a forklift truck as shown in FIG. 8. The 3D model 30 shown in FIG. 8 is an example and is not limited to this. Furthermore, in this specification, a three-dimensional coordinate system consisting of an X-axis, a Y-axis, and a Z-axis is used for explanation, and the orientation of the three-dimensional coordinate system corresponds in each drawing. In each drawing, the direction of the arrow of the coordinate system shown in the drawing is positive, and the direction opposite to the arrow is negative. Note that the configuration of each axis is an example and is not limited to this.

[0058] [Warehouse Management System Processing] The processing flow of the warehouse management system according to the first embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart of the processing of the warehouse management system according to the embodiment. The warehouse management system receives an inquiry about the warehouse to be simulated from the computing device 2 (step St41).

[0059] The warehouse management system acquires slot IDs for the slots included in the warehouse to be simulated (step St42). The slot IDs may be assigned to the slots by the warehouse management system.

[0060] The warehouse management system acquires slot positions for slots included in the warehouse to be simulated (step St43). The slot position acquired here may be, for example, if the slot is a rectangular parallelepiped, the three-dimensional coordinate of the center of the slot, or the three-dimensional coordinate of one of the six vertices of the slot. Alternatively, it may be the three-dimensional coordinate of each of the six vertices of the slot. The position of the slot to be acquired as the slot position may be preset by the warehouse management system.

[0061] The warehouse management system acquires the slot sizes of the slots included in the warehouse to be simulated (step St44). The slot sizes may be predetermined according to the type of shelf, etc. For example, they may be predetermined based on the size of the shelf, the size of the shelf dividers, and the size of the shelf boards. The slot sizes may also be calculated based on the coordinates of the slot. For example, if the slot is a rectangular parallelepiped, the length of each side of the slot may be calculated based on the three-dimensional coordinates of the six vertices of the slot.

[0062] The warehouse management system acquires pick positions for slots included in the warehouse to be simulated (step St45). The pick positions may be predefined for the slots. Alternatively, the pick positions may be determined, for example, according to the slot positions. For example, a position that is a predetermined distance away from the slot position in the positive or negative direction of the Y axis may be determined as the pick position.

[0063] The warehouse management system acquires the pick order for the slots included in the warehouse to be simulated (step St46). The pick order is predefined for the slots.

[0064] The warehouse management system acquires pick zone IDs for slots included in the warehouse to be simulated (step St47). Pick zone IDs are predefined for slots. By processing steps St42 to St47, the warehouse management system can acquire slot information for each slot included in the warehouse to be simulated.

[0065] The warehouse management system excludes slot information whose data contains NULL (step St48). NULL data means that the data does not contain a value. Here, excluding means that the data is not sent to the calculation device 2. If at least one of the data of the slot ID, slot position, slot size, pick position, pick order, and pick zone ID of any slot is NULL, the slot information of that slot is excluded.

[0066] The warehouse management system executes the processes of steps St42 to St48 for all slots in the warehouse to be simulated, and transmits the slot information of all slots obtained as warehouse information to the calculation device 2 (step St49). Then, this processing flow ends.

[0067] [Data processing] The flow of data processing executed by the arithmetic device 2 according to the first embodiment will be described with reference to Fig. 10. Fig. 10 is a flowchart of the data conversion processing according to the embodiment. At the start of the processing flow shown in Fig. 10, the processing of step St49 of the warehouse management system shown in Fig. 9 has been completed. The arithmetic device 2 acquires warehouse information (see step St49 in Fig. 9) transmitted from the warehouse management system (step St51).

[0068] The arithmetic unit 2 converts the slot information for each slot constituting the warehouse information acquired in step St51, and generates converted slot information (step St52). Details of this step will be described later with reference to FIG.

[0069] The arithmetic unit 2 generates passage information of passages existing in the warehouse to be simulated based on the conversion slot information generated in step St52 (step St53). Details of this step will be described later with reference to FIGS.

[0070] The calculation device 2 generates area information for various areas existing in the warehouse to be simulated (step St54) based on the conversion slot information generated in step St52 and the passage information generated in step St53. Details of this process will be described later with reference to Figures 14 and 15.

[0071] The calculation device 2 generates wall information for one or more walls existing in the warehouse to be simulated based on the area information generated in step St54 (step St55). Details of this step will be described later with reference to FIGS. 16 and 17.

[0072] The calculation device 2 generates a pick list consisting of one or more slots to be picked by the worker in the warehouse to be simulated (step St56) based on the converted slot information generated in step St52. Details of this process will be described later with reference to FIG.

[0073] The calculation device 2 generates inventory information of the items stored in the slots that make up the pick list of the warehouse to be simulated based on the pick list generated in step St56 (step St57). Then, this processing flow ends. Details of this process will be described later using FIG.

[0074] (Slot information conversion) The flow of the slot information conversion process executed by the arithmetic device 2 according to the first embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart of the slot information conversion process according to the embodiment. At the start of the process flow shown in Fig. 11, the arithmetic device 2 has already acquired the warehouse information transmitted from the warehouse management system.

[0075] The calculation device 2 performs anonymization processing on the slot IDs in the slot information for each slot constituting the warehouse information acquired in step St51 (step St61). Through the anonymization processing, the slot IDs become converted slot IDs. The slot IDs may be converted to consecutive integer numbers such as "00001," "00002," and "00003."

[0076] The calculation device 2 converts data including distance units from the slot information for each slot constituting the warehouse information acquired in step St51 into the distance unit system used in the simulation model (see 3D model 30 in FIG. 8) (step St62). For example, if the slot size is expressed in inches and meters are used in the simulation model, the slot size units are converted to meters by the processing of step St62. As a result, the slot size becomes the converted slot size. At the completion of the processing of step St62, the slot information includes the converted slot ID, slot position, converted slot size, pick position, pick order, and pick zone ID.

[0077] The arithmetic unit 2 extracts only the slot information of the slots included in the pick zone in the warehouse to be simulated from the slot information for each slot constituting the warehouse information acquired in step St51 (step St63). For example, assume that the pick zone ID of the slot in the pick zone to be simulated is "0001." If the warehouse information transmitted from the warehouse management system includes slot information with a pick zone ID of "0001" and slot information with a pick zone ID of "0002," only the slot information with a pick zone ID of "0001" is extracted. "Extracted" means that the slot is handled in subsequent processing by the arithmetic unit 2. The pick zone to be simulated may be set in advance by a user or the like.

[0078] The arithmetic unit 2 sorts the slot information extracted in the process of step St63 in pick order (step St64). In the subsequent processes of the arithmetic unit 2, the slot information is sorted in pick order.

[0079] The arithmetic unit 2 corrects the slot positions to match the reference point in the simulation model (step St65). For example, when the origin of the three-dimensional coordinate system is the reference point, the arithmetic unit 2 corrects the slot positions of all the slots to be simulated so that the slot position of the slot that is the shortest distance from the origin among the slots to be simulated is located at the origin. For example, when the slot position of the slot that is the shortest distance from the origin has an X coordinate of 100, a Y coordinate of 200, and a Z coordinate of 0, the arithmetic unit 2 corrects the X coordinate of the slot positions of all the slots to be simulated to -100 and a Y coordinate of -200. As a result, the slot positions become converted slot positions.

[0080] The calculation device 2 also performs the same correction on the pick position as the correction on the slot position performed in step St65 (step St66). As in the example described in step St65, when the calculation device 2 corrects the X coordinate of the slot position to -100 and the Y coordinate to -200, it also corrects the X coordinate of the pick position to -100 and the Y coordinate to -200. As a result, the pick position becomes the converted pick position. Then, this processing flow ends.

[0081] When the processing from step St61 to step St66 is completed, the slot information includes a conversion slot ID, a conversion slot position, a conversion slot size, a conversion pick position, a pick order, and a pick zone ID. In the subsequent processing, the calculation device 2 generates information required for automatically generating a simulation model and executing a simulation based on the conversion slot information including the conversion slot ID, the conversion slot position, the conversion slot size, and the conversion pick position. Note that the conversion slot information is sorted in pick order.

[0082] The conversion slot information may be generated as, for example, a Comma Separated Values ​​(hereinafter referred to as "CSV") file. The CSV file may include data for each slot (each conversion slot ID).

[0083] (Aisle information generation) The path information generation process executed by the arithmetic device 2 according to the first embodiment will be described with reference to Figures 12 and 13. Figure 12 is a flowchart of the path information generation process.

[0084] The arithmetic unit 2 generates a passage ID (step St71). The passage ID may be a consecutive integer value such as "00001", "00002", or "00003".

[0085] The calculation device 2 sets the start and end positions of the aisle based on the pick order of the slot and the converted pick position acquired in step St66 (step St72). The start and end positions refer to the coordinates of the start and end points, respectively. FIG. 13 is a schematic diagram for explaining an example of generation of aisle information. An example of setting the start and end positions of an aisle will be explained using FIG. 13. Here, the start and end positions of the aisle connecting slot 81 and slot 82 shown in FIG. 13 are set. The aisle connecting slot 81 and slot 82 is an aisle through which a worker or the like can move to perform work in slot 81 and slot 82. The pick orders of slot 81 and slot 82 are consecutive. For example, the pick order of slot 81 is 1, and the pick order of slot 82 is 2.

[0086] In the example of FIG. 13 , the start point SP1 and end point EP1 of the aisle are set to the XY coordinates of the converted pick position of slot 81 and the XY coordinates of the converted pick position of slot 82, respectively. The converted pick position of slot 81 has an X coordinate of 10 and a Y coordinate of 10. The converted pick position of slot 82 has an X coordinate of 12 and a Y coordinate of 10. In this way, the start point is set based on the converted pick position of the slot with the earlier pick order among the consecutive slots in the pick order, and the end point is set based on the converted pick position of the slot with the later pick order. For example, the end point of the aisle with aisle ID "00001" may be at the same position as the start point of the aisle with aisle ID "00002." By connecting the aisles in this way, the aisles throughout the warehouse are generated. The aisles may be set in advance by a user or the like so that they are generated on an XY plane whose Z coordinate is equal to the Z coordinate of a reference point in the simulation model. The Z coordinate of the XY plane on which the aisles are generated may also be set in advance by a user or the like. The calculation device 2 associates the start and end points of the set passage with the passage ID generated in step St71.

[0087] The calculation device 2 sets the width of the passage based on the converted slot position acquired in step St65 and the start and end positions of the passage set in step St72 (step St73). The width of the passage may be set to, for example, the distance between the slots sandwiching the start or end point set in step St72. For example, in the example of FIG. 13, the distance L between slot 81 and slot 85 opposite slot 81 is set to the width of the passage. Here, the distance between slot 81 and slot 85 is equal to the distance between point 83 and point 84. Point 83 is one of the vertices of slot 81, and point 84 is one of the vertices of slot 85. Point 83 and point 84 are on the same XY plane. For example, if the X coordinate of point 83 is 9 and the Y coordinate is 11, and the X coordinate of point 84 is 9 and the Y coordinate of point 84 is 9, the distance between point 83 and point 84 is 2. In this case, the width of the passage may be set to 2 meters.

[0088] The calculation device 2 sets whether or not the passage has one-way restrictions for each passage generated by executing the processes of steps St71 to St73 (step St74). In a passage where one-way restrictions are set, the passage is one-way from the start point to the end point. For example, in the example of FIG. 13, if the passage consisting of the start point SP1 and the end point EP1 is one-way restricted, workers etc. can move from the start point SP1 to the end point EP1, but cannot move in the reverse direction. If the passage is not one-way restricted, workers etc. can move from the end point EP1 to the start point SP1.

[0089] The calculation device 2 deletes paths whose length is 0 from all paths generated by executing the processes of steps St71 to St74 (step St75). Here, length refers to the distance between the start point and the end point. For example, in the example of FIG. 13, the distance between the start point SP1 and the end point EP1 is 2. An example of a case where the length of a path is 0 is when the start point and the end point are set to the same position (more specifically, positions where the picking orientation is different but the X coordinate and Y coordinate are the same) based on the converted pick position and the pick order, such that the pick order of slot 81 is 1 and the pick order of slot 85 is 2. When the calculation device 2 completes the process of step St75, it ends this processing flow.

[0090] Unlike the example shown in FIG. 13, there may be cases where the path is set at a position where a worker cannot move on the straight line connecting the start point and the end point. For example, there may be a case where a slot exists on the straight line connecting the start point and the end point. In this case, a path is generated to avoid the slot. In this way, the length does not have to be the shortest distance between the start point and the end point.

[0091] The passage information may be generated as, for example, a CSV file, which may include data for each passage (each passage ID).

[0092] (Area information generation) The region information generation process executed by the arithmetic device 2 according to the first embodiment will be described with reference to Figures 14 and 15. Figure 14 is a flowchart of the region information generation process.

[0093] The calculation device 2 sets the start and end points of the waiting area (step St91). FIG. 15 is a schematic diagram illustrating an example of generating area information. For example, the calculation device 2 sets a start point SP2 and an end point EP2 as the start and end points of the waiting area, respectively. In this case, an area 101 inside a rectangle having opposite vertices, the start point SP2 and the end point EP2, may be defined as the waiting area. Note that the area 101 may also include the sides of the rectangle. For example, if the X coordinate of SP2 is 10 and the Y coordinate is 20, and the X coordinate of EP2 is 60 and the Y coordinate is 40, the XY plane from 10 to 60 in X coordinates and from 20 to 40 in Y coordinates is defined as the waiting area. The Z coordinate of the waiting area may be set in advance by a user or the like. For example, the waiting area may be set in advance as an area on the XY plane with a Z coordinate of 0, or the Z coordinate of the waiting area may be set in advance to be equal to the Z coordinate of the reference point of the simulation model. The same applies to the loading area and warehouse area described later.

[0094] The calculation device 2 sets the start and end positions of the loading area in the same manner as in the process of step St91 (step St92). By setting the start and end positions of the loading area, the loading area is defined.

[0095] The arithmetic unit 2 sets a path between the waiting area and the slot based on the conversion slot position acquired in step St65 and the waiting area defined in step St91 so that a worker or the like can move from the waiting area to the slot to be worked on to start work such as picking (step St93). The path may be set so as to connect the waiting area to the slot with the shortest distance from the waiting area, or so as to connect the waiting area to the slot that is first in the pick order. The path may be set by the series of processes shown in FIG. 15.

[0096] The computing device 2 sets a path between the loading area and the slots based on the converted slot position acquired in step St65 and the loading area defined in step St92 so that workers who have completed work such as picking can move to the loading area to prepare for shipment (step St94). The path may be set to connect the loading area with the slot that is the shortest distance from the loading area, or may be set to connect the loading area with the slot that is last in the pick order. The path may be set by the series of processes shown in FIG. 15.

[0097] The calculation device 2 sets the start and end positions of the warehouse area in the same manner as in the processing of step St91 (step St95). The warehouse area is an area that serves as the base for a simulation model generated in cyberspace. Therefore, the range of the X and Y coordinates that define the warehouse area includes slots, aisles, waiting areas, and loading areas. When the processing of step St95 is completed, the calculation device 2 ends this processing flow.

[0098] The area information may be generated, for example, as a CSV file. The CSV file may include the start and end points of the waiting area, loading area, and warehouse area. Furthermore, the data of the aisles set in the processes of steps St93 and St94 may be added to a file containing the aisle information (for example, a CSV file).

[0099] (Wall information generation) The wall information generation process executed by the arithmetic device 2 according to the first embodiment will be described with reference to Figures 16 and 17. Figure 16 is a flowchart of the wall information generation process.

[0100] The calculation device 2 generates a wall ID (step St201). The wall ID may be a consecutive integer value such as "00001," "00002," or "00003."

[0101] The calculation device 2 sets the start and end points of four walls surrounding the entire warehouse based on the warehouse area defined in step St95 (step St202). FIG. 17 is a schematic diagram for explaining an example of generating wall information. Here, area 211 is the warehouse area. The four vertices of area 211 are points 221, 222, 223, and 224. In this case, the start and end points of wall 231 may be set to points 221 and 222, respectively. The start and end points of wall 232 may be set to points 222 and 223, respectively. The start and end points of wall 233 may be set to points 223 and 224, respectively. The start and end points of wall 234 may be set to points 224 and 221, respectively. Note that points 221, 222, 223, and 224 are points on the same XY plane. The wall is defined by setting the start and end positions of the wall. For example, if the X coordinate of point 221 is 0 and the Y coordinate is 0, and the X coordinate of point 222 is 60 and the Y coordinate is 0, wall 231 is defined as an XZ plane with X coordinates from 0 to 60 and Y coordinate of 0. When setting the start and end positions of the wall, the Z coordinate of the wall does not need to be limited. The calculation device 2 links the set start and end positions of the wall to the wall ID generated in step St201.

[0102] The arithmetic device 2 sets the heights of the walls defined in step St202 (step St203). The arithmetic device 2 may set the height of the walls to, for example, 1 meter. In the example of FIG. 17, the heights of the walls 231, 232, 233, and 234 may be set to 1 meter. For example, the heights of the four walls may be set separately or collectively. The relationship between the height of the walls and the coordinates may be set in advance by a user or the like. For example, 1 meter may be set to correspond to a coordinate change amount of 1. Furthermore, setting the height of the walls may also set the Z coordinate of the walls. For example, if the height of the wall 231 is set to 1 meter, the wall 231 may be defined as an XZ plane with an X coordinate ranging from 0 to 60, a Y coordinate ranging from 0, and a Z coordinate ranging from 0 to 100. The Z coordinate of the bottom of the wall may be set to 0, or the Z coordinate of the reference point in the simulation model may be set to the Z coordinate of the bottom of the wall.

[0103] The calculation device 2 sets the visibility of the wall defined in step St202 (step St204). If the wall is set as visible, the user can visually recognize the wall in the generated simulation model. After completing the processing of step St204, the calculation device 2 ends this processing flow.

[0104] The wall information may be generated as, for example, a CSV file, which may include data on each of the four walls surrounding the entire warehouse.

[0105] (Picklist generation) 18 is a flowchart of the pick list generation process executed by the arithmetic device 2 according to Embodiment 1. The pick list is the minimum information required to execute a simulation using the generated simulation model.

[0106] The arithmetic unit 2 generates a picklist ID (step St301). The picklist ID may be a consecutive integer value such as "0001," "0002," or "0003."

[0107] The arithmetic unit 2 generates an item ID (step St302). The item ID may be a consecutive integer value such as "0001," "0002," or "0003." For example, the arithmetic unit 2 associates the item ID "0002" with the pick list ID "0001."

[0108] The arithmetic device 2 assigns a conversion slot ID to each pick list ID generated in step St301 (step St303). Here, the conversion slot IDs may be assigned randomly. By randomly assigning conversion slot IDs, optimization of warehouse operations can be considered by running a simulation. For example, the arithmetic device 2 assigns the conversion slot ID "00001" to the pick list ID "0001." In this case, since the pick list ID "0001" is linked to the item ID "0002," when the simulation is run, the item with the item ID "0002" will be picked from the slot with the conversion slot ID "00001."

[0109] The calculation device 2 sets the number of pick items for each pick list ID generated in step St301 (step St304). For example, the calculation device 2 sets the number of pick items to 10 corresponding to the pick list ID "0001". When the calculation device 2 completes the processing of step St304, it ends this processing flow.

[0110] A picklist is generated through the series of processes shown in Figure 18. One picklist contains one picklist ID, one conversion slot ID, one item ID, and one number of pick items. For example, if the picklist contains the picklist ID, conversion slot ID, item ID, and number of pick items as "0001," "00001," "0002," and 10, respectively, the picklist has the following meaning: That is, based on the picklist with picklist ID "0001," a worker or other person will pick 10 items with item ID "0002" stored in the slot with conversion slot ID "00001."

[0111] All generated picklists may be compiled into a picklist file, which may be, for example, a CSV file.

[0112] (Inventory information generation) FIG. 19 is a flowchart of the inventory information generation process executed by the arithmetic device 2 according to the first embodiment. The arithmetic device 2 generates inventory information based on the pick list generated by the series of processes shown in FIG. 18. This flow makes it possible to generate the number of items stored in each slot. In the explanation of this flow, inventory information is generated based on the pick list with pick list ID "0001" given as an example in the explanation of FIG. 18.

[0113] The arithmetic device 2 references the pick list ID corresponding to the conversion slot ID (step St401). For example, the arithmetic device 2 references the pick list ID "0001" corresponding to the conversion slot ID "00001". This allows the arithmetic device 2 to obtain the item IDs and the number of items included in the pick list with the pick list ID "0001".

[0114] The arithmetic unit 2 acquires an item ID corresponding to the pick list ID referenced in step St401 (step St402). For example, the arithmetic unit 2 acquires an item ID "0002" corresponding to the pick list ID "0001". The arithmetic unit 2 sets the acquired item ID as inventory information data.

[0115] The arithmetic device 2 sets the number of inventory items for each item ID acquired in step St402 (step St403). For example, the arithmetic device 2 sets the number of inventory items for the item with item ID "0002" to 10. When a simulation is performed according to the pick list with pick list ID "0001" given as an example in the description of FIG. 18, the number of inventory items for item ID "0002" stored in the slot with conversion slot ID "00001" is as follows: That is, the number of inventory items before the simulation is performed is 10, and 10 items are picked in the simulation, so the remaining number after the simulation is completed is 0. The arithmetic device 2 may set the number of inventory items to prevent errors due to insufficient inventory when the simulation is performed. For example, the number of inventory items for a certain conversion slot ID may be set in advance by the user so that it is equal to or less than the number of pick items for that conversion slot ID. When the processing of step St403 is completed, the arithmetic device 2 ends this processing flow.

[0116] The inventory information may be generated as a CSV file, for example, and the CSV file may include the inventory quantity for each slot (each conversion slot ID).

[0117] [Simulation model generation, simulation execution] 20 is a flowchart of a simulation model generation and simulation execution process executed by the arithmetic device 2 according to the first embodiment. At the start of this flow, the arithmetic device 2 has completed the series of processes shown in FIG. 20. That is, the data conversion process has been completed. In addition, the arithmetic device 2 has received an instruction from the user to automatically generate a simulation model.

[0118] The arithmetic unit 2 generates a warehouse layout based on the conversion slot information, passage information, wall information, and area information (step St501), thereby generating a 3D model of the warehouse in cyberspace (see FIG. 8).

[0119] The computing device 2 sets the initial inventory of the item stored in the slot based on the inventory information (step St502). Depending on the inventory information of the slot, nothing may be stored in the slot. Furthermore, depending on the inventory information and the pick list, nothing may be stored in the slot after the simulation is executed. The display mode of the slot generated in cyberspace may be set in advance so that the user can visually recognize that some item is stored in the slot. For example, a slot that stores an item may be displayed in a different color from a slot that does not store an item, or the number of items in stock may be displayed in the slot.

[0120] The arithmetic device 2 sets one or more pick lists to be followed by the worker or the like in the simulation (step St503). Here, the arithmetic device 2 may set the pick list to be simulated by reading a pick list file in which multiple pick lists are compiled.

[0121] When the automatic generation of the simulation model is completed, the arithmetic unit 2 notifies the user of this fact (step St504).

[0122] When receiving an instruction to execute a simulation from the user, the arithmetic device 2 executes the simulation (step St505). During the execution of the simulation, for example, the user may be able to check how a worker or the like moves or performs a picking operation on the simulation model.

[0123] When the simulation is completed, the calculation device 2 outputs the simulation result (step St506). Then, this processing flow ends. The output simulation result will be described later with reference to FIGS. 21 and 22.

[0124] [Example of simulation results] Fig. 21 is a schematic diagram showing an example of a simulation result according to the first embodiment. A window 600 shown in Fig. 21 is displayed on, for example, a display (not shown). A simulation model is displayed in the window 600. Also displayed in the window 600 are layout conditions 601, execution conditions 602, execution results 603, and a simulation execution button 604. Here, "SIM" means simulation. Note that the window 600 shown in Fig. 21 is merely an example of a simulation result, and is not intended to limit the output contents of the simulation result.

[0125] Layout conditions 601 indicate layout conditions. In the example of Fig. 21, slots are generated based on a CSV file called "slot.csv". Also, aisles are generated based on a CSV file called "aisle.csv". Also, regions are generated based on a CSV file called "region.csv". Also, walls are generated based on a CSV file called "wall.csv".

[0126] Execution conditions 602 indicate the execution conditions of the simulation. In the example of Fig. 21, the simulation is executed based on a CSV file called "picklist.csv". In addition, the initial inventory quantity of items stored in each slot is set based on the CSV file "stock.csv".

[0127] The execution result 603 indicates the result of the simulation. Here, the pick distance indicates the distance traveled by the worker in the simulation. The pick time indicates the time from when the worker starts the work to when the worker finishes the work in the simulation.

[0128] The user may execute the simulation by, for example, using a mouse (not shown) to click the simulation execution button 604. Alternatively, the user may execute the simulation by operating a keyboard (not shown) or the like.

[0129] 22 is a schematic diagram showing an example of a simulation result according to Embodiment 1. The calculation device 2 may output the simulation result as a text file 700 shown in FIG.

[0130] 22, a text file 700 contains a simulation execution date and time 701, a simulation execution condition 702, and a simulation execution result 703. Note that the text file 700 shown in FIG. 22 is merely an example of a simulation result, and is not intended to limit the output contents of the simulation result.

[0131] The simulation execution date and time 701 describes the date and time when a button for executing a simulation, such as the simulation execution button 604 shown in Fig. 21, was pressed. The simulation execution date and time 701 also describes the date and time when the simulation was completed.

[0132] The simulation execution conditions 702 describe the file for executing the simulation. In the example of FIG. 22, it is shown that the simulation was executed using the ALP file "***.alp." Note that the type of simulation execution file is not limited to this. Furthermore, the simulation execution conditions 702 describe the number of pick lists in addition to descriptions equivalent to the layout conditions 601 and execution conditions 602 shown in FIG. 21.

[0133] The simulation execution result 703 includes the total distance traveled by the worker in the simulation. The time from when the worker started to complete the task in the simulation is also included as the task time. Furthermore, the distance traveled and task time for each picklist, as well as the inventory status for each slot after the simulation are included.

[0134] <Other embodiments> In the above embodiment, a pick list with a pick list ID of "0001", a conversion slot ID of "00001", an item ID of "0002", and 10 pick items was used as an example. In this case, the item ID of a pick list different from the pick list may be "0002". For example, a pick list with a pick list ID of "0002", a conversion slot ID of "00002", an item ID of "0002", and 10 pick items may be generated. The maximum number of identical item IDs allowed to exist may be set in advance by a user, etc. This allows a simulation to be performed that takes into account the case where the same item is stored in multiple slots.

[0135] In the above embodiment, an example was shown in which a 3D model of a warehouse is generated in cyberspace by visualizing a simulation model. However, this is not limited to this example, and the calculation device 2 may generate a 3D model of a warehouse in cyberspace independently of generating a simulation model. In this case, the calculation device 2 may generate a 3D model of a warehouse based on, for example, conversion slot positions, conversion slot sizes, area information, and wall information excluding wall IDs. This makes it possible to consider, for example, the layout of a warehouse with a lower processing load than automatic generation of a simulation model.

[0136] The concept of the above embodiment may also be applied to factories, retail stores, and the like.

[0137] Summary of the Disclosure The above description of the first embodiment discloses the following techniques. (Item 1) A simulation model generation method executed by a calculation device (2) connected to a warehouse management system capable of data communication with the warehouse management system that manages the inventory status of items stored in each of a plurality of warehouses, comprising: Acquire simulation information (at least one of data A to E), and generate a simulation model for managing operations in the simulation target warehouse based on the simulation information; The simulation information includes at least any of first data (A data) acquired from the warehouse management system, second data (B data) generated using the first data (A data), third data (C data) based on data acquired from a related system other than the warehouse management system, and fourth data (D data) that is a predetermined standard value; If at least a part of the information required to generate the simulation model is not included in the first to fourth data, output missing information notifying the fact that the information is missing. Simulation model generation method. As a result, the simulation model generation method can efficiently collect simulation information and reduce the load on generating the simulation model.

[0138] (Item 2) the missing information includes information indicating that a query needs to be made to a user of the simulation model; Item 1. A simulation model generation method according to item 1. As a result, the simulation model generation method can collect simulation information more efficiently and reduce the load on generating the simulation model.

[0139] (Item 3) When the missing information is output, a question to be inquired of by a user of the simulation model is output. 3. The simulation model generation method according to item 1 or 2. As a result, the simulation model generation method can collect simulation information more efficiently and reduce the load on generating the simulation model.

[0140] (Item 4) The information required as the simulation information is determined in accordance with the designation of the warehouse to be simulated accepted by a user operation. 3. The simulation model generation method according to item 1 or 2. As a result, the simulation model generation method can efficiently and appropriately collect simulation information and reduce the load on generating the simulation model.

[0141] (Item 5) A computing device (2) is a computer connected to a warehouse management system capable of data communication, the warehouse management system managing the inventory status of items stored in each of a plurality of warehouses. A process of acquiring simulation information (at least one of data A to E); and generating a simulation model for managing operations in the simulation target warehouse based on the simulation information. The simulation information includes at least any of first data (A data) acquired from the warehouse management system, second data (B data) generated using the first data (A data), third data (C data) based on data acquired from a related system other than the warehouse management system, and fourth data (D data) that is a predetermined standard value; If at least a part of the information required to generate the simulation model is not included in the first to fourth data, a simulation model is generated that outputs missing information to notify the user that the information is missing. Simulation model generation program. As a result, the simulation model generation program can efficiently collect simulation information and reduce the load on generating the simulation model.

[0142] (Item 6) A simulation model generation system executed by a calculation device (2) connected to a warehouse management system capable of data communication with the warehouse management system, which manages the inventory status of items stored in each of a plurality of warehouses, The calculation device acquires simulation information (at least one of data A to E), and generates a simulation model for managing operations in the simulation target warehouse based on the simulation information; The simulation information includes at least any of first data (A data) acquired from the warehouse management system, second data (B data) generated using the first data (A data), third data (C data) based on data acquired from a related system other than the warehouse management system, and fourth data (D data) that is a predetermined standard value; If at least a part of the information required to generate the simulation model is not included in the first to fourth data, a simulation model is generated that outputs missing information to notify the user that the information is missing. Simulation model generation system. As a result, the simulation model generation system can efficiently collect simulation information and reduce the load on generating a simulation model. [Industrial Applicability]

[0143] The technology disclosed herein is useful as a simulation model generation method, a simulation model generation program, and a simulation model generation system that efficiently collects simulation information and reduces the load on the generation of a simulation model. [Explanation of symbols]

[0144] 1 Simulation model generation system 2 Arithmetic unit 3-1, 3-s warehouse management system 31-1, 31-s Transportation and Delivery Management System 4-1-1, 4-1-m, 4-s-1, 4-sn Warehouse PC 5 CPU 6. Memory 7 Storage device 8 Input / output section 9. Communications Department 10 External interface section 30 3D models 31 Shelf 32 Passage 33 Standby area 34 Loading area 35 Warehouse area 36-1, 36-2, 36-3, 36-4 Wall 37 Workers 600 windows 700 text files

Claims

1. A simulation model generation method executed by a computing device connected to a warehouse management system capable of data communication with the warehouse management system, which manages the inventory status of items stored in the warehouse, comprising: Acquire simulation information, and generate a simulation model for managing operations in a simulation target warehouse based on the simulation information; the simulation information includes at least any of first data acquired from the warehouse management system, second data generated using the first data, third data based on data acquired from a related system other than the warehouse management system, and fourth data that is a predetermined standard value; if at least a part of the information required to generate the simulation model is not included in any of the first data to the fourth data, outputting missing information notifying the user that the information is missing. Simulation model generation method.

2. the missing information includes information indicating that a query needs to be made to a user of the simulation model; The simulation model generation method according to claim 1 .

3. When the missing information is output, a question to be inquired of by a user of the simulation model is output. The simulation model generating method according to claim 1 or 2.

4. The information required as the simulation information is determined in accordance with the designation of the warehouse to be simulated accepted by a user operation. The simulation model generating method according to claim 1 or 2.

5. A computing device, which is a computer connected to a warehouse management system that manages the inventory status of goods stored in a warehouse, is provided. obtaining simulation information; and generating a simulation model for managing operations in a simulation target warehouse based on the simulation information. the simulation information includes at least any of first data acquired from the warehouse management system, second data generated using the first data, third data based on data acquired from a related system other than the warehouse management system, and fourth data that is a predetermined standard value; if at least a part of the information required to generate the simulation model is not included in any of the first data to the fourth data, outputting missing information notifying the user that the information is missing. Simulation model generation program.

6. A simulation model generation system executed by a computing device connected to a warehouse management system capable of data communication with the warehouse management system, which manages the inventory status of items stored in the warehouse, the computing device acquires simulation information, and generates a simulation model for managing operations in a simulation target warehouse based on the simulation information; the simulation information includes at least any of first data acquired from the warehouse management system, second data generated using the first data, third data based on data acquired from a related system other than the warehouse management system, and fourth data that is a predetermined standard value; if at least a part of the information required to generate the simulation model is not included in any of the first data to the fourth data, outputting missing information notifying the user that the information is missing. Simulation model generation system.

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