Performance estimation method for automated warehouse, performance estimation device for automated warehouse, and program

Abstract

This performance estimation method comprises: acquiring customer information including a required specification and a floor drawing of an automated warehouse; generating, on the basis of the customer information, a calculation map for calculating performance of the automated warehouse; setting, on the basis of the customer information and the calculation map, a simulation condition that includes information on an arbitrary order and that is for evaluating the performance of the automated warehouse; executing a simulation by using the calculation map and the simulation condition; and outputting, to a display device on the basis of an execution result of the simulation, an estimation result of the performance of the automated warehouse including a processing time of an order to be processed by the automated warehouse.

Description

Method for estimating performance of automated warehouse, apparatus for estimating performance of automated warehouse, and program

[0001] The present disclosure relates to a method for estimating the performance of an automated warehouse, an apparatus for estimating the performance of an automated warehouse, and a program.

[0002] Patent Document 1 discloses a warehouse management system provided with a host controller for managing the operation of a warehouse and a warehouse design device for designing the layout of the warehouse and the work flow of operations such as incoming and outgoing goods. The warehouse design device simulates work instructions or incoming and outgoing instructions based on the designed layout and work flow, and when a satisfactory result is obtained, it sends the designed layout and work flow to the host controller.

[0003] Japanese Patent Application Laid-Open No. 2008-94553

[0004] When designing an automated warehouse or considering changes to the layout of an automated warehouse, the performance of the automated warehouse is estimated, and based on the estimation results, the automated warehouse to be introduced is designed or the layout of the automated warehouse is changed. When estimating the performance of an automated warehouse, for example, information related to inventory is often virtually set, which may result in a large difference between the performance at the time of estimation and the performance at the time of introduction or change.

[0005] The present disclosure has been devised in view of the above-described conventional situation, and aims to estimate the performance of an automated warehouse with higher accuracy.

[0006] The present disclosure provides a method for estimating the performance of an automated warehouse, which includes obtaining customer information including requirements specifications and floor plans of a new automated warehouse, generating a calculation map for calculating the performance of the new automated warehouse based on the customer information, setting simulation conditions including information on any order for evaluating the performance of the new automated warehouse based on the customer information and the calculation map, executing the simulation using the calculation map and the simulation conditions, and outputting an estimation result of the performance of the new automated warehouse including the processing time of the order processed by the new automated warehouse to a display device based on the execution result of the simulation.

[0007] Furthermore, this disclosure provides an automated warehouse performance estimation device comprising a processor and a memory, wherein the processor, in cooperation with the memory, acquires customer information including the requirements specifications and floor plans of a new automated warehouse; generates a calculation map for calculating the performance of the new automated warehouse based on the customer information; sets simulation conditions including information on arbitrary orders for evaluating the performance of the new automated warehouse based on the customer information and the calculation map; executes the simulation using the calculation map and the simulation conditions; and outputs an estimated result of the performance of the new automated warehouse, including the processing time of the orders processed by the new automated warehouse, to a display device based on the results of the simulation.

[0008] Furthermore, this disclosure provides a program for causing a computing device to acquire customer information including the requirements specifications and floor plans of a new automated warehouse; to generate a calculation map for calculating the performance of the new automated warehouse based on the customer information; to set simulation conditions including information on arbitrary orders for evaluating the performance of the new automated warehouse based on the customer information and the calculation map; to execute the simulation using the calculation map and the simulation conditions; and to output an estimated result of the performance of the new automated warehouse, including the processing time of the orders processed by the new automated warehouse, to a display device based on the results of the simulation.

[0009] Furthermore, any combination of the above components, as well as any conversion of the expressions of this disclosure between methods, apparatus, systems, storage media, computer programs, etc., are also valid as aspects of this disclosure.

[0010] According to this disclosure, the performance of automated warehouses can be estimated with greater accuracy.

[0011] Block diagram showing an example configuration of the estimation device according to Embodiment 1 Flowchart showing the performance estimation process of an automated warehouse by the estimation device according to Embodiment 1 Schematic diagram for explaining information for the performance estimation process of an automated warehouse according to Embodiment 1 Schematic diagram for explaining the calculation map according to Embodiment 1 Schematic diagram for explaining the simulation screen according to Embodiment 1 Graph diagram showing an example output of the estimation device according to Embodiment 1 Table diagram showing an example output of the estimation device according to Embodiment 1

[0012] The embodiments will be described in detail below, with reference to the drawings as appropriate. However, unnecessary details may be omitted. For example, detailed explanations of already well-known matters or redundant explanations of substantially identical configurations may be omitted. This is to avoid the following explanation becoming unnecessarily verbose and to facilitate understanding for those skilled in the art. The accompanying drawings and the following explanation are provided to enable those skilled in the art to fully understand this disclosure and are not intended to limit the subject matter described in the claims.

[0013] (Embodiment 1) [Device Configuration] Figure 1 is a block diagram showing an example configuration of the estimation device 10 according to Embodiment 1. The estimation device 10 is a device for estimating the performance of an automated warehouse. The estimation device 10 estimates the performance of the automated warehouse with high accuracy by performing a simulation. The estimation device 10 may be a general-purpose computer device such as a Personal Computer (hereinafter referred to as "PC") or a server computer. Hereinafter, the estimation device 10 may be referred to as the calculation device. Note that the configuration shown in Figure 1 is just one example, and one part may be divided into multiple parts, or multiple parts may be combined into one.

[0014] The estimation device 10 comprises a processor 11, memory 12, communication device 13, input device 14, external interface device 15, and display device 16. Each component is configured to communicate via an internal interface device 17.

[0015] The processor 11 may be configured using, for example, a Central Processing Unit (hereinafter referred to as "CPU"), a Graphical Processing Unit (hereinafter referred to as "GPU"), a Micro Processing Unit (hereinafter referred to as "MPU"), a Digital Signal Processor (hereinafter referred to as "DSE"), or a Field Programmable Gate Array (hereinafter referred to as "FPGA"). The processor 11 realizes various functions by reading and executing various data and programs held in the memory 12.

[0016] Memory 12 is a storage unit for storing various data and programs. Memory 12 may consist of volatile / non-volatile storage devices such as Random Access Memory (hereinafter referred to as "RAM"), Read Only Memory (hereinafter referred to as "ROM"), and Hard Disk Drive (hereinafter referred to as "HDD").

[0017] The communication device 13 is an interface for communicating with external devices via a network. The communication standards supported by the communication device 13 are not particularly limited and may support either wired or wireless communication standards. Furthermore, the communication device 13 may support multiple communication standards. Therefore, the network used by the communication device 13 may be composed of a combination of networks using multiple communication standards.

[0018] The input device 14 receives operations and instructions from a user, for example, who is conducting sales in an automated warehouse. The input device 14 may consist of a mouse, keyboard, touch panel display, etc.

[0019] The external interface device 15 is an interface for sending and receiving data with an external device.

[0020] The display device 16 displays various user interfaces to the user. The display device 16 may consist of a liquid crystal display, a touch panel display, or the like.

[0021] For example, a user that sells automated warehouses may conduct business negotiations with customers considering purchasing an automated warehouse according to the following phases. The first phase is the proposal phase, in which the user interviews the customer about their requirements for the automated warehouse and provides the customer with an estimated performance of the automated warehouse based on the information gathered. The next phase after the proposal phase is the design phase, in which the user, using the estimated performance of the automated warehouse from the proposal phase as a reference, interviews the customer for more specific information and estimates the performance of the automated warehouse with greater accuracy. In the design phase, for example, the performance of the automated warehouse may be estimated with greater accuracy by using the operational results of a warehouse or automated warehouse owned by the customer, or by using simulations. The next phase after the design phase is the operation phase, in which the actual site of the installed automated warehouse is reproduced in a virtual space using a digital twin, and plans are formulated using simulations. The next phase after the operation phase is the change phase, in which the user provides customers considering layout changes to the installed automated warehouse with an estimated performance of the modified automated warehouse obtained from simulations using the operational results of the automated warehouse, and proposes changes.

[0022] The following explanation illustrates an example in which the estimation device 10 performs a simulation to estimate the performance of an automated warehouse after its introduction, when a customer who owns a warehouse is introducing a new automated warehouse. If the user can obtain requirements specifications other than operational performance data from the customer, the estimation device 10 can estimate the performance of the automated warehouse based on these requirements specifications. This is, for example, the estimation of the automated warehouse's performance in the proposal phase described above. If the user can obtain operational performance data from the customer in addition to requirements specifications from the customer, the estimation device 10 can use the operational performance data to estimate the performance of the automated warehouse with greater accuracy. This is, for example, the estimation of the automated warehouse's performance in the design phase described above.

[0023] [Flowchart] Figure 2 is a flowchart showing the performance estimation process of an automated warehouse by the estimation device 10 according to Embodiment 1. Each process in the flowchart shown in Figure 2 is executed by the processor 11 of the estimation device 10. At the start of the flowchart shown in Figure 2, the user has already obtained customer information, including the requirements specifications for the automated warehouse, by interviewing the customer.

[0024] The processor 11 acquires customer information based on user operation (step St 100). Customer information includes information obtained by the user from the customer, such as the requirements specifications and floor plans of the automated warehouse being considered for new installation, and includes information used to estimate the performance of the automated warehouse. Specific examples of customer information will be described later with reference to Figure 3.

[0025] The processor 11 generates a calculation map for calculating the performance of the automated warehouse based on the customer information obtained in step St 100 (step St 101). Details of the calculation map will be described later with reference to Figure 4.

[0026] The processor 11 sets the simulation conditions for evaluating the performance of the automated warehouse based on the customer information obtained in step St 100 and the calculation map generated in step St 101 (step St 102). Specific examples of the simulation conditions will be described later with reference to Figure 3.

[0027] Processor 11 sets the conditions necessary for the simulation that were not set in step St102, i.e., the missing conditions (step St103). For example, if the customer information obtained by the user from the customer is insufficient, even if processor 11 sets the simulation conditions based on the customer information, there may be some missing conditions for the simulation. In this case, processor 11 may automatically set the missing conditions for the simulation. For example, processor 11 may virtually set the missing conditions based on conditions that have been set in the past. Specifically, if there are missing conditions, processor 11 may set the condition that is set most frequently as the simulation condition. Alternatively, processor 11 may output a message to the display device 16 if there are missing conditions. Then, based on the user's actions after confirming the missing information, processor 11 may set the missing conditions.

[0028] The processor 11 executes a simulation (step St 104) based on the calculation map generated in step St 101 and the simulation conditions set in step St 102, which include the conditions set in step St 103. The simulation may be, for example, a reproduction of order processing in an automated warehouse, where "order" means operations such as issuing or receiving goods in the automated warehouse. In this specification, "goods" includes merchandise and cargo, and these terms may be interpreted interchangeably. By executing the simulation, the processor 11 can estimate the performance of the automated warehouse. Examples of automated warehouse performance include the processing time of orders handled by the automated warehouse, the cost of introducing the automated warehouse, or the maintenance costs if an automated warehouse is introduced. For example, the processor 11 can obtain information on the order processing time by reproducing the order processing by the automated warehouse through simulation. Then, the processor 11 can estimate the maintenance costs of the automated warehouse based on the order processing time information, etc.

[0029] The progress of the ongoing simulation may be output to a display device 16, for example, so that it can be viewed by the user. An example of the simulation screen will be shown later with reference to Figure 5.

[0030] The processor 11 organizes and outputs the estimated performance results of the automated warehouse (step St 105). The processor 11 may output the estimated results to, for example, the display device 16, or to an external device not shown. Specific examples of the outputted estimated results will be described later with reference to Figures 6 and 7.

[0031] The processor 11 determines whether the estimated result output in step St105 is acceptable (step St106). For example, the processor 11 may determine whether the estimated result is acceptable based on user input. For example, if a customer who has checked the estimated result output on the display device 16 is negative about the estimated result, the user may input via the input device 14 that there is a problem with the estimated result. Alternatively, the processor 11 may determine whether there is a problem with the estimated result based on customer information acquired in step St100. For example, if the processor 11 has acquired information on the maintenance costs of the automated warehouse desired by the customer in step St100, and determines that the maintenance costs included in the estimated result exceed the customer's desired costs, it may further determine that there is a problem with the estimated result. In this case, the processor 11 may also calculate how much the estimated maintenance costs exceed the desired costs and output the calculation result.

[0032] If the processor 11 determines that the estimated result is acceptable (step St106: YES), it terminates this processing flow.

[0033] If the processor 11 determines that there is a problem with the estimated result (step St106: NO), it adjusts the simulation conditions, etc. (step St107). For example, the processor 11 may display a user interface on the display device 16 for inputting new customer information, adjusting the generated calculation map, or adjusting the set simulation conditions. The processor 11 may then accept input of new customer information, adjust the generated calculation map, or adjust the set simulation conditions based on user operation. After processing in step St109, the processor 11 returns to step St100, step St101, step St102, or step St103 and repeats the process. For example, if new customer information is input, the processor 11 may return to step St100. Or, for example, if there is a change in the floor plan, the processor 11 may return to step St101. Or, for example, if there is an adjustment to the simulation conditions, the processor 11 may return to step St102. Alternatively, for example, if insufficient simulation conditions are input, the processor 11 may return to step St103. Then, the processor 11 runs the simulation again based on the adjusted simulation conditions, etc., and estimates the performance of the automated warehouse.

[0034] In this way, the estimation device 10 can estimate the performance of an automated warehouse by setting simulation conditions based on information obtained from the customer and performing a simulation that reproduces the order processing by the automated warehouse. If the user can obtain past work performance data from the customer for the warehouse owned by the customer, the estimation device 10 can set simulation conditions based on the past work performance data. This makes the reproduction of the order processing by the automated warehouse in the simulation more accurate, and the estimation device 10 can estimate the performance of the automated warehouse with high accuracy. Work performance data at the warehouse includes, for example, the order processing time at that warehouse.

[0035] [Information Flow] Figure 3 is a schematic diagram illustrating the information used for estimating the performance of the automated warehouse according to Embodiment 1.

[0036] Customer information includes, for example, floor plans, warehouse performance, budget, warehouse type, operational history of existing automated warehouses or warehouses, and information on items handled. Floor plans refer to drawings showing the floors, or rooms, of the automated warehouse. Warehouse performance, budget, and warehouse type are the requirements specifications for the automated warehouse. Warehouse performance refers to information indicating the number of orders that the automated warehouse can process in a given time. Warehouse type refers to information indicating the type of automated warehouse, which may vary depending on the manufacturer. Note that the requirements specifications for the automated warehouse may include information other than warehouse performance, budget, and warehouse type. Information on operational history of existing automated warehouses or warehouses and information on items handled are customer information that can be obtained from customers who already own automated warehouses or warehouses. Therefore, information on operational history of existing automated warehouses or warehouses and information on items handled cannot be obtained from customers who do not own either automated warehouses or warehouses. Operational history of automated warehouses or warehouses includes information on order processing time in the automated warehouse or warehouse, information on items received and shipped in the past, and may further include other information. Handling item information refers to information about items handled in existing automated warehouses or warehouses, in other words, information about inventory items that are received or shipped.

[0037] This section provides specific examples of information about outsourced items included in work performance data. One example of outsourced item information is a series of pieces of information indicating that a specific part necessary for manufacturing a product has been outsourced. This series of information may include the name of the product that uses the part, and the serial number of the product's manufacture. Furthermore, this series of information, which can be used as simulation conditions, may include information indicating how many of each part are stored in each bin, information indicating how many parts are needed (in other words, the number of picks), the location where the bins are stored (i.e., shelf information), and information about the destination of the parts.

[0038] From the floor plan included in the customer information, a calculation map is generated to calculate the performance of the automated warehouse. The calculation map includes information on the direction of travel of the transport equipment that transports goods within the automated warehouse, as well as the possible locations for transport equipment, elevators, stations, etc. Details will be described later with reference to Figure 4. Transport equipment is equipment that transports bins in which goods are stored. Examples of transport equipment include Automatic Guided Vehicle (hereinafter referred to as "AGV") and Autonomous Mobile Robot (hereinafter referred to as "AMR"). At the station, a worker or work robot performs the task of moving items to be shipped from storage bins to shipping bins, in other words, picking. In the following description, "worker" means a worker or work robot.

[0039] Simulation conditions are set based on customer information and calculation maps. The simulation conditions include information on incoming goods, outgoing goods, inventory lists, shelf lists, bin arrangements, station performance, elevator performance, conveying equipment performance, and plate sizes, as well as order information set based on this information and route information. Incoming goods information is information on items being received. Outgoing goods information is information on items being outgoing. The estimation device 10 can set incoming goods information and outgoing goods information based on information on items that have been received and items that have been outgoing in the past, which is included in the work record.

[0040] The inventory list contains information about the inventory of items stored in the automated warehouse. The shelf list contains information about the shelves where the bins are stored. The bin placement information indicates which shelf each bin is stored on. The estimation device 10 can determine which items are stored in the automated warehouse by setting the incoming and outgoing inventory information. Therefore, the estimation device 10 can set the inventory list, shelf list, and bin placement information based on the set incoming and outgoing inventory information.

[0041] Station performance refers to the number of orders, or in other words, the number of bins, that a station can process per predetermined time. The estimation device 10 can calculate the number of orders that an existing automated warehouse or warehouse can process per predetermined time based on the information on the processing time of orders in the automated warehouse or warehouse included in the work performance. Based on the calculation results, the estimation device 10 can set the station performance.

[0042] Elevator performance refers to information indicating the elevator's performance, such as its load capacity. Conveyor equipment performance refers to information indicating the conveyor equipment's performance, such as its maximum speed, acceleration, and the time required to change direction. Plate size refers to information indicating the size of the plates. Plates are laid on the floor of the automated warehouse and divide the floor area of ​​the automated warehouse. Since the information on elevator performance, conveyor equipment performance, and plate size is detailed aspects of the automated warehouse design, it may not be obtainable from the customer. On the other hand, it is highly likely that the user possesses this information. If the user possesses this information, they may input it into the estimation device 10.

[0043] The order information indicates the type of order, for example, whether the order is a work instruction to issue goods or a work instruction to issue goods. The order information also indicates which bins are assigned to the order, which transport equipment is assigned to the multiple tasks that make up the order, which station processes the order, and the number of items to be picked from the bins. If the order is a work instruction to issue goods, the tasks that make up the order may include, for example, a task to transport the bins containing the goods to the station, a task to transport the bins for issue to the station, a task to move the goods by picking, a task to transport the bins that are no longer needed after picking to outside the station, and a task to transport the bins containing all the items to be issued for issue. Note that the picking task is assigned to a worker, not to transport equipment. The estimation device 10 may set the order information based on the receiving information, issuing information, inventory list, shelf list, bin arrangement, and station performance. The estimation device 10 may, for example, set the number of transport equipment units to be operated in the simulation based on user input. Route information is information indicating what route the transport equipment will choose to travel. Specifically, it is information indicating whether the transport equipment will choose the route that minimizes the travel distance, or whether the transport equipment will choose a route specified in advance by the user. The estimation device 10 can set the route information based on a calculation map.

[0044] These simulation conditions may be automatically set based on customer information and a calculation map, or may be set by user operations. The user may make a preset setting for the estimation device 10 so that the simulation conditions are automatically set based on the customer information and the calculation map. Further, the estimation device 10 may display a user interface screen for setting on the display device 16 so that the user can manually set the simulation conditions. For example, when the customer information necessary for automatically setting the simulation conditions cannot be obtained and the estimation device 10 cannot acquire the information, there may be a case where the estimation device 10 cannot set some of the simulation conditions. In this case, the estimation device 10 may virtually set the simulation conditions, or may display the above-described user interface screen for setting on the display device 16 and notify the user that manual setting is necessary.

[0045] For example, simulation conditions such as order information and route information may be arbitrarily set so that the simulation desired by the user is executed. The simulation desired by the user may be, for example, a simulation in which the total travel distance of the transport equipment is the shortest, a simulation in which the total travel time of the transport equipment is the shortest, or a simulation using a specified number of transport equipment designated by the user.

[0046] Based on the calculation map and a plurality of simulation conditions, an automated warehouse for simulation is generated on a three-dimensional virtual space. Then, based on the simulation conditions and the virtual space, the simulation is executed. As a result, the state of order processing is reproduced in the automated warehouse generated on the virtual space.

[0047] Note that in this embodiment, a discrete simulation technique may be used. For example, the estimation device 10 may perform a discrete simulation based on an event-driven calculation method. Under the event-driven calculation method, changes in the system are captured for each event, and the state of the system is updated only at the timing when an event occurs. As a result, instead of constantly tracking the behavior of the entire system, calculations are performed when important events occur, enabling efficient simulation. For example, when the estimation device 10 simulates a case where a plurality of transport devices (e.g., AGVs) process tasks related to the transport of articles in an automated warehouse, it may apply a discrete simulation technique based on an event-driven calculation method. Thereby, the estimation device 10 can individually track the movement path (travel route) of the transport device and the arrival time to a specific position such as a station, and update the simulation for each event when each transport device reaches a specific position.

[0048] Thus, since the estimation device 10 can track events that occur discretely by discrete simulation, it can simulate in detail the problems in the actual operation of an automated warehouse considering congestion between a plurality of transport devices or competition at intersections.

[0049] As a result of the execution of the simulation, for example, information such as the processing time of orders processed by the automated warehouse can be obtained. Based on such a result of the execution of the simulation, the estimation device 10 can estimate the performance of the automated warehouse. In other words, the estimation device 10 can evaluate the performance of the automated warehouse. As an estimation result of the performance of the automated warehouse, in addition to the processing time of the orders processed by the above-described automated warehouse, for example, estimates of warehouse performance, introduction costs (initial costs), and maintenance costs (operation costs), the operating rates of workers, stations, or transport devices, and inventory information after order processing, etc. can be mentioned.

[0050] [Calculation Map] Next, referring to FIG. 4, the data configuration of the calculation map and the like will be described. FIG. 4 is a schematic diagram for explaining the calculation map according to Embodiment 1.

[0051] Figure 4 shows a calculation map M1 corresponding to a portion of the automated warehouse area R1 (see Figure 5). For the sake of simplicity, the explanation focuses on a portion of the automated warehouse area R1, but the calculation map may be generated to represent the entire automated warehouse. In the calculation map M1, the automated warehouse area R1 is divided into a mesh. In this case, each mesh may be generated to correspond to each plate laid on the floor of the automated warehouse, or the mesh may be generated based on a size predetermined by the user.

[0052] In the calculation map M1, the mesh corresponding to the walls of the automated warehouse is set to "0". In addition, the placement of shelves in the automated warehouse, the placement of transport equipment such as garages where transport equipment waits, the possible placement locations of bins, the placement locations of stations, the placement locations of elevators, and the direction of travel of transport equipment are set for each mesh. In the calculation map M1, "E" indicates the location of the elevator, and "W" indicates the location of the worker. Since bins are stored on shelves, the placement locations of shelves can also be the possible placement locations of bins.

[0053] The generation of a calculation map allows for the setting of route information for transport equipment. Furthermore, based on the calculation map and multiple simulation conditions, the automated warehouse to be simulated is generated in a virtual space. The progress of the simulation may be visually displayed on the display device 16. Referring to Figure 5, the simulation screen output to and displayed on the display device 16 will be described.

[0054] [Example of Simulation Screen] Figure 5 is a schematic diagram illustrating the simulation screen G1 according to Embodiment 1. The simulation screen G1 is displayed on the display device 16. The user can check the progress of the simulation by viewing the simulation screen G1. Although the simulation screen G1 shown in Figure 5 displays the automated warehouse in two dimensions, the display device 16 may display the automated warehouse in three dimensions.

[0055] In the example shown in Figure 5, the simulation screen G1 displays the first floor (F1), second floor (F2), and third floor (F3) of the automated warehouse. The simulation reproduces, for example, the process of a worker 21 picking items at station 20. The simulation also reproduces, for example, the process of a conveying device 22 transporting bottles. The second and third floors of the automated warehouse are the back rooms, where shelves 23 for storing bottles containing goods and shelves 24 for storing empty bottles are located. The simulation screen G1 may also display the simulation execution speed, the elapsed time since the simulation started, etc. The simulation screen G1 may also display the operating rates of multiple stations, etc. Note that the configuration of the simulation screen G1 shown in Figure 5 is just an example, and further elements may be added to or omitted from the simulation screen. For example, each floor of the automated warehouse may be divided and displayed on a different screen. Furthermore, conveying devices traveling for receiving goods and conveying devices traveling for shipping goods may be distinguished, for example, by color-coding the conveying devices.

[0056] [Example of estimated performance results for an automated warehouse] Next, an example of estimated performance results for an automated warehouse will be explained with reference to Figures 6 and 7. Figure 6 is a graph showing an example of the output of the estimation device 10 according to Embodiment 1.

[0057] The graph shown in Figure 6 shows the processing time required for an order during the planning phase on the vertical axis and the processing time taken during the simulation on the horizontal axis. If the processing time required for an order during the planning phase is equal to the processing time taken during the simulation, the order is plotted as a point on the straight line of characteristic 50. Orders whose processing time during the simulation is longer than the processing time during the planning phase are plotted to the right of the straight line of characteristic 50. Orders whose processing time during the simulation is longer than the processing time during the planning phase are plotted to the left of the straight line of characteristic 50.

[0058] The estimation device 10 can reproduce the order processing by the automated warehouse by running a simulation. The estimation device 10 can then obtain information on the time taken to process the orders during the simulation. Based on the time taken to process the orders during the simulation and the estimated time required for order processing at the planning stage, which was obtained in advance based on user operations, the estimation device 10 can generate a graph like the one shown in Figure 6 and output it to the display device 16 or the like. By checking the output graph, the user or customer can, for example, understand that the order processing is taking longer than planned.

[0059] Figure 7 is a table diagram showing an example of the output of the estimation device 10 according to Embodiment 1. The table diagram in Figure 7 allows for a comparison of the maintenance costs of an existing warehouse and a newly introduced automated warehouse.

[0060] The estimation device 10 can calculate location costs (e.g., rent) based on the area of ​​the newly installed automated warehouse. Furthermore, by running a simulation, the estimation device 10 can obtain information on the processing time of orders handled by the automated warehouse. This allows the estimation device 10 to determine, for example, the daily working hours of the workers in the automated warehouse. Based on the number of workers and their working hours, the estimation device 10 can then calculate labor costs. In addition, the estimation device 10 can calculate the system inspection costs for the automated warehouse. The estimation device 10 may determine the system inspection costs for the automated warehouse, for example, as follows: That is, by running a simulation, the estimation device 10 can obtain information such as warehouse performance, station performance, and the number of bins that the conveying equipment can transport per predetermined time. Based on this information, the estimation device 10 can calculate the number of conveying equipment units required for the newly installed automated warehouse. Based on the number of conveying equipment units, the estimation device 10 can calculate the inspection costs for the conveying equipment. Thus, the estimation device 10 may calculate the system inspection cost of the automated warehouse by calculating the inspection cost for each piece of equipment and machinery that constitutes the automated warehouse system. Various costs for the maintenance and management of existing warehouses may be entered into the estimation device 10 in advance by a user who has interviewed a customer, for example, or the estimation device 10 may calculate them. For example, the labor costs of an existing warehouse can be calculated by the estimation device 10 based on the order processing time at the existing warehouse, which is included in the work record.

[0061] In the example shown in Figure 7, the monthly maintenance cost of a newly installed automated warehouse is 5 million yen cheaper than the monthly maintenance cost of an existing warehouse. Furthermore, the initial cost required for the new automated warehouse is 200 million yen. Therefore, the customer can recoup the initial cost after 40 months of use. By reviewing the output table, the customer can obtain information to determine, for example, whether or not there are any cost issues with the new automated warehouse installation.

[0062] Note that the output examples shown in Figures 6 and 7 are just examples, and the estimation device 10 may output the estimation results in a format other than graph or table format, or it may output information other than the information shown in Figures 6 or 7. Furthermore, the type of information and output format that the estimation device 10 outputs may be set in advance by the user.

[0063] (Modification of Embodiment 1) Embodiment 1 described above shows an example in which the estimation device 10 performs a simulation to estimate the performance of an automated warehouse after its introduction when a customer who owns a warehouse newly introduces the automated warehouse. However, it is not limited to this, and the estimation device 10 may also perform a simulation to estimate the performance of an automated warehouse after a design change when a customer who owns an automated warehouse changes the design of the automated warehouse.

[0064] Furthermore, the estimation device 10 may estimate the performance of the automated warehouse based on a calculation map and various simulation conditions without performing a simulation. In this case, the accuracy of the estimation result may be lower than when a simulation is performed, but it is possible to obtain the estimation result more easily.

[0065] (Summary of Embodiment 1) The following technology is disclosed based on the description of Embodiment 1 above. The components etc. in the above Embodiment 1 are examples, but are not limited to these.

[0066] (Technology 1) The method for estimating the performance of an automated warehouse involves acquiring customer information including the requirements specifications and floor plans of a new automated warehouse, generating a calculation map (e.g., calculation map M1) for calculating the performance of the new automated warehouse based on the customer information, setting simulation conditions including information on arbitrary orders for evaluating the performance of the new automated warehouse based on the customer information and the calculation map, executing a simulation using the calculation map and the simulation conditions, and outputting an estimated result of the performance of the new automated warehouse, including the processing time of orders handled by the new automated warehouse, to a display device (e.g., display device 16) based on the results of the simulation.

[0067] As a result, the automated warehouse performance estimation method according to Embodiment 1 can perform simulations of the operation of a new automated warehouse using simulation conditions set based on customer information. This makes it possible to estimate the performance of an automated warehouse with higher accuracy compared to, for example, estimating the performance of an automated warehouse without performing simulations.

[0068] (Technology 2) In the automated warehouse performance estimation method described in Technology 1, customer information further includes work performance including order processing time in an existing automated warehouse or warehouse, and the simulation conditions include an inventory list of goods to be stored in the new automated warehouse, goods receiving information, goods shipping information, bin placement information for storing goods, and a list of shelves for storing bins, and the automated warehouse performance estimation method may set the inventory list, goods receiving information, shipping information, bin placement information, and shelf list based on work performance.

[0069] As a result, the automated warehouse performance estimation method according to Embodiment 1 can set simulation conditions based on the operational performance of an existing automated warehouse or warehouse, making it possible to estimate the performance of the automated warehouse with greater accuracy.

[0070] (Technology 3) The method for estimating the performance of an automated warehouse described in Technology 2 may involve assigning one or more bins to an order, assigning multiple tasks constituting the order to one or more transport devices that transport the bins, and then estimating the performance of the new automated warehouse by reproducing the order processing by the new automated warehouse through simulation.

[0071] As a result, the method for estimating the performance of the automated warehouse according to Embodiment 1 can reproduce, by performing a simulation, how conveying equipment transports bins related to an order in order to process that order, and how tasks constituting that order are processed.

[0072] (Technology 4) The method for estimating the performance of an automated warehouse described in Technology 2 or 3 may compare the costs required for the maintenance of an existing automated warehouse or warehouse with the costs required for the maintenance of a new automated warehouse, and output the results of this comparison.

[0073] This allows users to compare the costs of maintaining an automated warehouse or existing warehouse with the costs of maintaining a new automated warehouse.

[0074] (Technology 5) The method for estimating the performance of an automated warehouse described in any one of Techniques 1 to 4 may further output the progress of the simulation to a display device.

[0075] This allows users to check the progress of the simulation.

[0076] (Technical 6) The automated warehouse performance estimation device comprises a processor and memory. The processor, in cooperation with the memory, acquires customer information including the requirements and floor plans of a new automated warehouse and the operational performance of an existing automated warehouse or warehouse. Based on the customer information, it generates a calculation map for calculating the performance of the new automated warehouse. Based on the customer information and the calculation map, it sets simulation conditions for evaluating the performance of the new automated warehouse. It executes a simulation using the calculation map and the simulation conditions, and based on the results of the simulation, it outputs an evaluation result of the performance of the new automated warehouse, including the processing time of orders that the new automated warehouse will handle.

[0077] As a result, the automated warehouse performance estimation device can achieve the same effect as in Technology 1.

[0078] (Technical 7) The program causes the computing unit to acquire customer information including the requirements specifications and floor plans for the new automated warehouse, and the work performance of the existing automated warehouse or warehouse; generates a calculation map for calculating the performance of the new automated warehouse based on the customer information; sets simulation conditions for evaluating the performance of the new automated warehouse based on the customer information and the calculation map; executes the simulation using the calculation map and the simulation conditions; and outputs an evaluation result of the performance of the new automated warehouse, including the processing time of orders handled by the new automated warehouse, based on the results of the simulation.

[0079] This allows the program to achieve the same effect as Technique 1.

[0080] While embodiments have been described above with reference to the attached drawings, this disclosure is not limited to such examples. It is clear to those skilled in the art that various modifications, alterations, substitutions, additions, deletions, and equivalents can be conceived within the scope of the claims, and these are also understood to fall within the technical scope of this disclosure. Furthermore, the components of the embodiments described above can be combined in any way without departing from the spirit of the invention.

[0081] This application is based on a Japanese patent application (JP 2024-198326) filed on November 13, 2024, the contents of which are incorporated by reference within this application.

[0082] The technology disclosed herein is useful as a method for estimating the performance of an automated warehouse, an automated warehouse performance estimation device, and a program.

[0083] 10. Estimation device 11. Processor 12. Memory 13. Communication device 14. Input device 15. External interface device 16. Display device 17. Internal interface device

Claims

1. A method for estimating the performance of an automated warehouse, comprising: acquiring customer information including the requirements specifications and floor plans of a new automated warehouse; generating a calculation map for calculating the performance of the new automated warehouse based on the customer information; setting simulation conditions including information on arbitrary orders for evaluating the performance of the new automated warehouse based on the customer information and the calculation map; executing the simulation using the calculation map and the simulation conditions; and outputting an estimated result of the performance of the new automated warehouse, including the processing time of the orders processed by the new automated warehouse, to a display device based on the results of the simulation.

2. The customer information further includes work performance including order processing time in an existing automated warehouse or warehouse, the simulation conditions include an inventory list of items to be stored in the new automated warehouse, receiving information for the items, shipping information for the items, arrangement information for bins storing the items, and a list of shelves storing the bins, and the inventory list, receiving information, shipping information, bin arrangement information, and shelf list are set based on the work performance, the method for estimating the performance of an automated warehouse according to claim 1.

3. A method for estimating the performance of an automated warehouse according to claim 2, comprising: assigning one or more bins to the order; assigning a plurality of tasks constituting the order to one or more transport devices that transport the bins; and estimating the performance of the new automated warehouse by reproducing the processing of the order by the new automated warehouse through the simulation.

4. A method for estimating the performance of an automated warehouse according to claim 2, comprising comparing the costs required for the maintenance of the existing automated warehouse or warehouse with the costs required for the maintenance of the new automated warehouse, and outputting the results of the comparison.

5. The method for estimating the performance of an automated warehouse according to claim 1, further comprising outputting the progress of the simulation to a display device.

6. An automated warehouse performance estimation device comprising a processor and memory, wherein the processor, in cooperation with the memory, acquires customer information including the requirements specifications and floor plans of a new automated warehouse; generates a calculation map for calculating the performance of the new automated warehouse based on the customer information; sets simulation conditions including information on arbitrary orders for evaluating the performance of the new automated warehouse based on the customer information and the calculation map; executes the simulation using the calculation map and the simulation conditions; and outputs an estimated result of the performance of the new automated warehouse, including the processing time of the orders processed by the new automated warehouse, to a display device based on the results of the simulation execution.

7. A program for causing a computing device to acquire customer information including the requirements specifications and floor plans of a new automated warehouse; to generate a calculation map for calculating the performance of the new automated warehouse based on the customer information; to set simulation conditions including information on arbitrary orders for evaluating the performance of the new automated warehouse based on the customer information and the calculation map; to execute the simulation using the calculation map and the simulation conditions; and to output an estimated result of the performance of the new automated warehouse, including the processing time of the orders processed by the new automated warehouse, to a display device based on the results of the simulation.

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