Information processing device, information processing method and program

Abstract

To improve the efficiency of a work of an entire system including a plurality of systems.SOLUTION: An information processing device includes a processing part.The processing part assigns each of a plurality of orders, each of which includes first identification information that identifies one or more types of articles, to one of a plurality of batches. The processing part calculates, for each of the plurality of batches, a first workload in a first system including a system that processes an article with first identification information included in the batch in a first unit, and a second workload in a second system including a system that processes the article with first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of articles processed in the first unit. The processing part modifies the orders included in the plurality of batches based on the first workload and the second workload.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] An embodiment of the present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Known methods for picking items in logistics warehouses and the like include the total picking method and the single picking method. The total picking method reduces the number of pickings by consolidating multiple items for multiple delivery destinations and picking them together. In this case, a downstream sorting system sorts multiple items by delivery destination. The single picking method picks items by delivery destination, and the picked items can be shipped as is, meaning sorting is not required.

[0003] As described above, in the total picking method, the picking system that performs the picking processes items in aggregated units (aggregated units), while the sorting system processes parts as individual units (individual units). [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 5825348 Summary of the Invention [Problem to be solved by the invention]

[0005] Conventional technology does not take into account the differences in the units of item processing used by each of multiple systems (e.g., picking systems, sorting systems), which can result in a decrease in the efficiency of work performed by the entire system, including multiple systems.

[0006] An object of the present invention is to provide an information processing device, an information processing method, and a program that can improve the efficiency of work in an entire system including a plurality of systems. [Means for solving the problem]

[0007] An information processing device according to an embodiment includes a processing unit. The processing unit assigns each of a plurality of orders, each of which includes first identification information identifying one or more types of items, to one of a plurality of batches. For each of the plurality of batches, the processing unit calculates a first workload in a first system including a system for processing items having the first identification information included in the batch in a first unit, and a second workload in a second system including a system for processing items having the first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of items processed in the first unit. The processing unit changes the orders included in the plurality of batches based on the first workload and the second workload. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a block diagram of a logistics system according to an embodiment. [Figure 2] FIG. 1 is a block diagram of an information processing apparatus according to an embodiment. [Figure 3] FIG. 10 is a diagram showing an example of a table definition of shipping order information. [Figure 4] FIG. 10 is a diagram showing an example of a table definition of detailed information. [Figure 5] FIG. 10 is a diagram showing an example of a table definition of item master information. [Figure 6] FIG. 10 is a diagram showing an example of a table definition of picking station information. [Figure 7] FIG. 10 is a diagram showing an example of a table definition of sorter master information. [Figure 8] FIG. 10 is a diagram showing an example of a table definition of work entity master information. [Figure 9] FIG. 10 is a diagram showing an example of a table definition of total picking conversion information. [Figure 10] FIG. 10 is a diagram showing an example of a table definition for total picking workload information. [Figure 11] 10 is a flowchart of information processing according to an embodiment. [Figure 12] FIG. 1 is a diagram for explaining an example of information processing according to an embodiment. [Figure 13] FIG. 1 is a hardware configuration diagram of an information processing apparatus according to an embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Preferred embodiments of an information processing apparatus according to the present invention will be described in detail below with reference to the accompanying drawings.

[0010] In the following, a logistics system including a picking system and a sorting system (hereinafter referred to as a logistics system DS) will be described as an example. The systems to which the embodiments can be applied are not limited to such logistics systems, and may be other systems including multiple systems that process target items in different units.

[0011] The following is an overview of the processing flow in the logistics system DS. In the logistics system DS, for example, processing in each system is executed in the following procedure. (S1) Information on multiple shipping orders is acquired. Each shipping order includes information on one or more types of items. (S2) Create a batch of items according to the batch size of the sorter (a device that sorts items) equipped in the sorting system and the number of shipping orders acquired. The batch size is the number of shipping orders that the sorter can process. (S3) The shipping orders to be assigned to each batch are determined so that shipping orders containing the same type of items are included in the same batch and so that each shipping order can be shipped by its processing deadline. (S4) Each system (picking system, sorting system) performs its work so that the batch containing the determined shipping order is processed as a unit.

[0012] The above function (S3) makes it possible to pick items of the same type in aggregate units, which improves the efficiency of transportation and picking by consolidating items. It also makes it possible to complete processing by the processing deadline for each shipping order (delivery date adherence).

[0013] The consolidation effect corresponds to the improvement in work efficiency by consolidating items of the same type from shipping orders assigned to each batch. For example, a transport system that transports items for picking can retrieve and transport items in aggregate units from the inventory of items stored in a storage system. As a result, the greater the number of items included in an aggregate unit, the fewer the number of transports, and the shorter the lead time. Similarly, picking workers can pick items in aggregate units. Therefore, the greater the number of items included in an aggregate unit, the fewer the number of picks, and the shorter the lead time.

[0014] The number of items included in an aggregation unit may or may not be a fixed value. For example, if the task is performed by a person (worker), the worker can pick two or more items at a time, but not more than the upper limit. In such cases, the number of items included in an aggregation unit can be variable. The upper limit depends on the size of the items and the number of items stored in the container (shelf, etc.) that stores the items to be picked.

[0015] On the other hand, automatic picking by robots often involves picking items by grasping them one by one (individual unit). For this reason, in robotic picking, the lead time often depends on the quantity of items in individual units (hereinafter also referred to as individual items) (hereinafter also referred to as the number of individual items), rather than the number of items included in the aggregate unit. Similarly, sorters used in the sorting process often move items one by one and store them in containers (such as carts) corresponding to the shipping order. For this reason, the lead time often depends on the number of individual items.

[0016] In the logistics system DS, for example, the workers who perform the picking pick items in aggregate units, while the sorting system sorts the picked items individually. Therefore, unless the workload in each system is adjusted taking into account the unit of processing of these items (hereinafter referred to as the work unit), it may not be possible to improve the work efficiency of the logistics system DS as a whole. For example, if the shipping orders to be assigned to each batch are determined without considering the work unit, there may be an imbalance in the workload between batches, causing delays between the picking process and the sorting process. This delay may result in a decrease in shipping efficiency or may cause the sorter to stop.

[0017] Furthermore, each system may be composed of multiple subsystems with different work units. For example, a picking system may include a subsystem in which humans (operators) perform picking in aggregate units, and a subsystem in which picking robots perform picking in individual units. In such cases, it is desirable to adjust the workload of each subsystem, taking into account the differences in the work units between the multiple subsystems.

[0018] For example, as part of the promotion of white goods logistics, the introduction of picking robots is progressing to reduce the number of workers in warehouses. Picking by picking robots differs from picking by humans (workers) in that the types of items they can process (items designated as processing targets) are limited, and items are processed individually. In a logistics system (DS) that includes multiple subsystems with different work units, such as picking robots and workers, if work instructions are not issued taking into account the differences in the work units of the two, there is a risk of imbalances in the amount of work, leading to reduced work efficiency.

[0019] In this embodiment, the following functions are mainly used to improve the work efficiency of the entire system including multiple systems. (F1) Change the allocation of shipping orders to each batch so that the amount of work is balanced across multiple batches, both in aggregate and individual work units (batch balancing function). (F2) In the case of a system that includes multiple subsystems with different work units, the amount of work is distributed to each work entity so that the amount of work according to the work unit of each work entity is leveled for each batch (work entity leveling function).

[0020] If a system including multiple subsystems with different task units is not used, the function (F2) above does not need to be provided. If (F2) is provided, for example, it becomes possible to level out the workload between workers and robots, taking into account differences in task units, that is, to optimize cooperation between people (workers) and robots.

[0021] Fig. 1 is a block diagram showing an example of the configuration of a logistics system DS according to an embodiment. As shown in Fig. 1, the logistics system DS includes an information processing system 100, a warehouse management system 200, a storage system 300, a transport system 400, a plurality of picking systems 501a, 501b, 502a, and 502b, and a plurality of sorting systems 600a and 600b.

[0022] Storage system 300 is a system for storing multiple items to be shipped. Storage system 300 is, for example, a logistics warehouse that is designed to process shipments using a total picking method. Storage system 300 is composed of shelves and stockers that store multiple items.

[0023] The transport system 400 is a system that takes out and transports items according to shipping orders for each delivery destination from the storage system 300. The transport system 400 is configured by, for example, a shelf transport robot (AGV) and an high-rise rack robot (ACR).

[0024] Picking systems 501a, 501b, 502a, and 502b are systems that pick the required number of items from among the items transported by the transport system 400. Picking systems 501a, 501b, 502a, and 502b correspond to system SYS1 (first system) that includes a system that processes items in work unit U1 (first unit).

[0025] 1 corresponds to a system including multiple subsystems with different task units. For example, picking systems 501a and 501b correspond to subsystem SS1 (first subsystem) that processes items in task unit U1. Picking systems 502a and 502b correspond to subsystem SS2 (second subsystem) that processes items in task unit U3 (third unit) with a number of items different from the number of items processed in task unit U1. In the example of FIG. 1, task unit U1 is an aggregate unit, and task unit U3 is an individual unit.

[0026] In FIG. 1, picking systems 501a and 501b are workers who pick items in aggregate units (task units U1). Picking systems 502a and 502b are picking robots that pick items in individual units (task units U3). Picking systems 501a and 501b are referred to as picking system 501 when there is no need to distinguish between them. Picking systems 502a and 502b are referred to as picking system 502 when there is no need to distinguish between them.

[0027] Sorting system 600a sorts the items picked by picking system 501a or 502a by delivery destination and shipping order and ships them in batches. Sorting system 600b sorts the items picked by picking system 501b or 502b by delivery destination and shipping order and delivers them in batches. Sorting systems 600a and 600b are configured, for example, with a sorter. Sorting systems 600a and 600b are referred to as sorting system 600 when there is no need to distinguish between them.

[0028] Sorting system 600 corresponds to system SYS2 (second system) that includes a system that processes items in a work unit U2 (second unit) with a number of items different from the number of items processed in work unit U1. In the example of Figure 1, work unit U2 is an individual unit.

[0029] Although FIG. 1 shows an example in which there are two pairs of a sorting system 600 and two picking systems 501 and 502, the number of pairs may be one, or three or more. In this embodiment, processing such as allocation of shipping orders to batches is performed for each pair. The following mainly describes processing for one pair. Similar processing is also applied to the other pairs.

[0030] Furthermore, the number of picking systems 501 and the number of picking systems 502 included in each group may be two or more. Furthermore, the picking systems 501 and 502 do not have to be a worker and a picking robot, respectively, and may be any combination of picking systems as long as the task units are different from each other.

[0031] The warehouse management system 200 is a system that communicates with each system / device within the logistics system DS and manages information on the entire logistics system DS. The warehouse management system 200 transmits, for example, item information, which is information about items, and work information about work in each system, to the information processing device 100, and causes the information processing device 100 to execute processing. Details of the item information and work information will be described later.

[0032] The information processing device 100 is a device (order management system) that manages shipping orders, such as determining shipping orders for each batch processed in each system, using item information and work information acquired from the warehouse management system 200. For example, the information processing device 100 performs the above functions (F1) and (F2).

[0033] The information processing device 100 outputs output information including information on shipping orders for each batch to the warehouse management system 200. The warehouse management system 200 uses the output information to output work instructions for the picking systems 501 and 502 and the sorting system 600. The work instructions for the picking systems 501 and 502 are, for example, lists of aggregated items by work entity and by batch. The work instructions for the sorting system 600 are, for example, a shipping order list by batch.

[0034] The information processing device 100 includes a processing unit 110 and a storage unit 120. The configurations of the processing unit 110 and the storage unit 120 will be described in further detail with reference to Fig. 2. Fig. 2 is a block diagram showing an example of the configuration of the information processing device 100 according to the embodiment.

[0035] The storage unit 120 stores various types of information used by the information processing device 100. For example, the storage unit 120 stores item information and work information acquired from the warehouse management system 200, as well as output information to be output to the warehouse management system 200.

[0036] 2, the item information includes shipping order information 121, detail information 122, and item master information 123. The work information includes picking station information 124, sorter master information 125, and work entity master information 126. The output information includes total picking conversion information 127 and total picking workload information 128. Below, an example of the data structure of each piece of information stored in the storage unit 120 will be described.

[0037] FIG. 3 is a diagram showing an example of a table definition of shipping order information 121. The first line shows the names of the items included in the information (shipping order information 121), the second line shows a description of each item, the third line shows the data type of each item, and the fourth line shows whether each item is a primary key (PK). The same applies to the following FIGS. 4 to 10. Although FIGS. 3 to 10 show examples of data being represented in table format, the data structure is not limited to table format and may be in any format. For example, each piece of information may be stored in a format such as a CSV file or a JSON file.

[0038] As shown in Fig. 3, shipping order information 121 includes a shipping order ID and a processing deadline. In shipping order information 121, the shipping order ID is set as a primary key (PK). The shipping order ID is identification information that identifies a shipping order. The processing deadline indicates the deadline (cutoff date and time) for shipping the shipping order.

[0039] Fig. 4 is a diagram showing an example of a table definition of the detail information 122. As shown in Fig. 4, the detail information 122 includes a shipping order ID, a detail ID, an item name, and a quantity. In the detail information 122, the shipping order ID and the detail ID are set as primary keys.

[0040] The detail ID is identification information that identifies the details included in the shipping order. Details are determined for each type of item ordered. Therefore, the number of details is the number of types of items ordered. The item name is the name of the item corresponding to the detail. The item name corresponds to identification information that identifies the item. The quantity is the number of items ordered.

[0041] Of the detailed information 122, information corresponding to one shipping order ID corresponds to one order including an item name (first identification information) that identifies one or more types of items.

[0042] Fig. 5 is a diagram showing an example of a table definition of the item master information 123. As shown in Fig. 5, the item master information 123 includes an item name and an automatic processing possible flag. In the item master information 123, the item name is set as a primary key.

[0043] The automatic processing flag is set to "True" if the item can be processed by a picking robot, and "False" if it cannot. The automatic processing flag can be interpreted as information indicating whether the item is designated as an item to be processed by a picking robot.

[0044] Fig. 6 is a diagram showing an example of a table definition of the picking station information 124. As shown in Fig. 6, the picking station information 124 includes a station ID, a work entity ID, an operation status flag, and a sorter ID. In the picking station information 124, the station ID is set as a primary key.

[0045] The station ID is identification information that identifies a picking station. A picking station represents a location where a picking task is performed by a picking task entity (such as a worker or a picking robot). For example, a task entity is assigned to one of the picking stations (also known as logging in) and performs picking tasks at the assigned picking station.

[0046] The work subject ID is identification information that identifies a work subject (who is logged in) assigned to the station identified by the station ID. The operation status flag is set to "True" if the station is in operation (the work subject is working on it), and is set to "False" if the station is not in operation (is idle).

[0047] The sorter ID is identification information that identifies the sorter connected to the picking station. As shown in Fig. 1, there is an N:1 correspondence relationship (N is an integer equal to or greater than 1) between the picking station (picking system) and the sorter (sorting system). This correspondence relationship is defined in the picking station information 124.

[0048] Fig. 7 is a diagram showing an example of a table definition of the sorter master information 125. As shown in Fig. 7, the sorter master information 125 includes a sorter ID and a batch size. In the sorter master information 125, the sorter ID is set as a primary key.

[0049] The batch size is the number of shipping orders dispensed from the sorter at one time. The batch size depends on, for example, the capacity of the container (dispensing cart) into which the items are dispensed. For this reason, the batch size for each sorter (sorter ID) is registered in the sorter master information 125.

[0050] Fig. 8 is a diagram showing an example of a table definition of the work subject master information 126. As shown in Fig. 8, the work subject master information 126 includes a work subject ID, a robot flag, and productivity. In the work subject master information 126, the work subject ID is set as a primary key.

[0051] The robot flag is set to "True" if the task subject is a picking robot, and "False" if the task subject is not a picking robot (e.g., a worker).

[0052] Productivity indicates the productivity of the work performed by the worker, and is, for example, the quantity that can be picked per hour. Note that the quantity is the quantity in aggregate units when the worker is a worker, and the quantity is the quantity in individual units (number of individual items) when the worker is a picking robot.

[0053] 9 is a diagram showing an example of a table definition of the total picking conversion information 127. As shown in FIG. 9, the total picking conversion information 127 includes a shipping order ID, a detail ID, a batch ID, a consolidated item ID, a station ID, and a sorter ID. In the total picking conversion information 127, the shipping order ID and the detail ID are set as primary keys.

[0054] The batch ID is the batch ID of the batch assigned to the shipping order ID by the processing unit 110. The aggregated item ID is identification information that identifies the aggregated item. The aggregated item corresponds to a unit that aggregates items of the same type included in the batch assigned to the shipping order ID. The station ID is the station ID of the picking station assigned to the batch with the corresponding batch ID. The sorter ID is the sorter ID of the sorter corresponding to the picking station with the station ID.

[0055] 10 is a diagram showing an example of a table definition of the total picking workload information 128. As shown in Fig. 10, the total picking workload information 128 includes a batch ID, an aggregated item ID, a quantity, a workload, a station ID, and a sorter ID. In the total picking workload information 128, the batch ID and the aggregated item ID are set as primary keys.

[0056] The quantity represents the number of individual items contained in the aggregated item identified by the aggregated item ID. The workload is the time required for the picking work. If the task entity to which the aggregated items are allocated is a worker, the workload is calculated, for example, by 1 / (productivity) x 60. If the task entity to which the aggregated items are allocated is a picking robot, the workload is calculated, for example, by (quantity) / (productivity) x 60.

[0057] The total picking workload information 128 corresponds to supplementary information used for confirming or evaluating the processing results by the information processing device 100 (processing unit 110). The total picking workload information 128 is calculated using, for example, the total picking conversion information 127 (FIG. 9) and input information including item information and workload information (FIGS. 3 to 8).

[0058] The storage unit 120 can be configured from any commonly used storage medium, such as a flash memory, a memory card, a RAM (Random Access Memory), an HDD (Hard Disk Drive), or an optical disk.

[0059] Some or all of the information stored in storage unit 120 may be stored in physically different storage media, or may be stored in different storage areas of the same physically identical storage medium.

[0060] Returning to the explanation of Fig. 2, the processing unit 110 includes a creating unit 111, an allocating unit 112, a calculating unit 113, a changing unit 114, a distributing unit 115, and an output control unit .

[0061] The creation unit 111 creates multiple batches for allocating shipping orders by referring to the acquired item information and work information. For example, the creation unit 111 creates multiple batches by using the shipping order processing deadline included in the shipping order information 121 and the batch size included in the sorter master information 125.

[0062] First, the creation unit 111 calculates the number of batches required to allocate the multiple shipping orders identified by the shipping order IDs included in the shipping order information 121. For example, the creation unit 111 calculates the number of required batches as an integer value obtained by dividing the number of shipping orders (shipping order IDs) by the batch size and rounding up the result. The creation unit 111 creates the calculated number of batches, assigns a batch ID to each batch, and assigns a sequence number in the order of dispensing.

[0063] The creation unit 111 also sets an upper limit for the processing deadline for each batch. For example, the creation unit 111 sorts the shipping orders in order of earliest processing deadline, and sets the processing deadlines of shipping orders in an order corresponding to a multiple of the batch size, in order of earliest, as the upper limit for the processing deadline of the batch with the smallest dispensing order. The method for setting the upper limit is not limited to this, and any method may be used. For example, the creation unit 111 may set an upper limit specified by a user or the like using an input screen.

[0064] Each batch cannot be assigned to shipping orders whose processing deadline is later than the upper limit. This makes it possible to meet the delivery deadline for each shipping order.

[0065] The allocation unit 112 performs batch allocation to allocate each of a plurality of orders to one of a plurality of batches. For example, the allocation unit 112 performs batch allocation so as to maximize the aggregation effect of the total picking method, while taking into consideration that the shipping orders have processing deadlines within the upper limit (are allocable).

[0066] The allocation unit 112 first determines batch candidates to be allocated based on the processing deadlines of multiple orders. For example, the allocation unit 112 determines batches with upper limits set equal to or greater than the processing deadlines of the orders as batch candidates to which the orders are to be allocated. The allocation unit 112 determines the batch to which the multiple orders are to be allocated by repeating the process of determining batch candidates so that the determined candidates include as many orders containing the same item as possible.

[0067] For example, the allocation unit 112 calculates the aggregation effect for each of the determined batch candidates. The allocation unit 112 calculates the aggregation effect by, for example, (number of details) / (number of aggregated items). The number of details is the total number of details included in the batch candidate. The number of aggregated items corresponds to the number of aggregated items when items of the same type included in the batch candidate are aggregated to form an aggregated item.

[0068] For example, suppose that multiple shipping orders containing five details as shown below are assigned to a batch candidate. Note that items M1, M3, and M5 each represent a different type of item. 5 units of item M1 5 units of item M3 Five items M5 10 units of item M3 Five items M5

[0069] Any item with multiple quantities can be aggregated into an aggregated item. In the above example, items M1, M3, and M5 are aggregated into three aggregated items. Therefore, the number of aggregated items is 3, and the aggregation effect is calculated as 5 / 3.

[0070] The allocation unit 112 repeats the process (simulation) of determining batch candidates to allocate to each order and calculating the aggregation effect, for example, until the upper limit of the number of repetitions is reached. The batch candidates to allocate are, for example, randomly determined from batches with upper limits set equal to or greater than the order processing deadlines. When the upper limit of the number of repetitions is reached, the allocation unit 112 determines the candidate with the greatest aggregation effect as the batch to which multiple orders are allocated.

[0071] Batch allocation is not limited to the method of repeating simulations as described above, and any other method may be used. For example, the allocation unit 112 may use a clustering method to define the distance between two shipping orders as the inverse of the aggregation effect, and repeatedly group shipping orders that are close to each other to form batches hierarchically. For example, the distance may be defined so that the closer the types of items are, the smaller the distance becomes.

[0072] The allocation unit 112 may perform batch allocation using mathematical programming (combinatorial optimization). For example, the allocation unit 112 may allocate a binary variable x that takes the value 1 if shipping order i is allocated to batch k and takes the value 0 otherwise. ik The allocation unit 112 defines a model using x to optimize the aggregation effect by using a mathematical programming solver or a combinatorial optimization algorithm. ik Batch allocation is performed by calculating

[0073] An example of a model used by the allocation unit 112 will be described below. For example, the model is based on the following conditions shown in equations (1) to (4), and is expressed as equation (5): jk Minimize the sum of x ik This is a model that seeks to

number

number

number

number

number

[0074] The variables used in each formula are defined below. x ik : 1 if outbound delivery order i is assigned to batch k, 0 otherwise y jk : 1 if item j is included in batch k, 0 otherwise I: Set of shipping orders i J: A set of items j K: set of batch k K i : A set of batch k whose upper limit is equal to or exceeds the deadline for processing of shipping order i (note that K i (The bar in represents the complement) B: Batch size c ij :Quantity of item j in shipping order i

[0075] Equation (1) represents the selection of batch k, which is the upper limit of the deadline for shipping order i or more. Equation (2) represents the number of shipping orders included in the batch is less than or equal to the batch size. Equation (3) represents the equation for the aggregated item variable, where y = 1 when quantity x > 0. Equation (5) represents the equation for minimizing the number of aggregated items.

[0076] In this embodiment, the allocation of shipping orders to each batch is then changed by the batch leveling function (F1 above). The calculation unit 113 and the change unit 114 execute a function equivalent to the batch leveling function.

[0077] The calculation unit 113 calculates a workload W1 (first workload) and a workload W2 (second workload) for each of the batches obtained by batch allocation.

[0078] Workload W1 is the workload when processing orders included in a batch in system SYS1 (e.g., picking systems 501 and 502) that includes a system (e.g., picking system 501) that processes in work unit U1 (e.g., aggregate unit). Workload W2 is the workload when processing orders included in a batch in system SYS2 (e.g., sorting system 600) that includes a system that processes in work unit U2 (e.g., individual unit).

[0079] For example, the calculation unit 113 calculates the workload W1 by dividing the number of task units U1 included in the batch by the number of task units U1 processed by the system SYS1 per unit time. The calculation unit 113 also calculates the workload W2 by dividing the number of task units U2 included in the batch by the number of task units U2 processed by the system SYS2 per unit time.

[0080] If task unit U1 is an aggregate unit, the number of task units U1 included in the batch corresponds to the number of aggregated items included in the batch. If task unit U2 is an individual unit, the number of task units U2 included in the batch corresponds to the number of individual items included in the batch. The number of individual items can be calculated using, for example, the quantity included in the detailed information 122.

[0081] If the system includes multiple subsystems, the calculation unit 113 further calculates, for each of the multiple batches, a workload W3 (third workload) and a workload W4 (fourth workload), which are the workloads of each of the multiple subsystems. The workload W3 is the workload when the orders included in the batch are processed by the subsystem SS1 (e.g., picking system 501) that processes in task unit U1 (e.g., aggregate unit). The workload W4 is the workload when the orders included in the batch are processed by the subsystem SS2 (e.g., picking system 502) that processes in task unit U3 (e.g., individual unit).

[0082] The modification unit 114 modifies the batch allocation results so as to equalize the calculated workloads W1 and W2 for each task unit. For example, the modification unit 114 modifies the orders included in the multiple batches so as to equalize the workloads W1 and W2 among the multiple batches.

[0083] The change unit 114 executes an exchange process to exchange, for example, one or more orders included in a batch B1 (first batch) included in the multiple batches with one or more orders included in a batch B2 (second batch) included in the multiple batches. The change unit 114 executes the exchange process to change the orders included in the multiple batches so that the difference in the amount of work W1 between the batch B1 and the batch B2 and the difference in the amount of work W2 between the batch B1 and the batch B2 are reduced when the exchange process is executed.

[0084] In this way, the change unit 114 selects two batches from multiple batches, extracts one shipping order from each of the two selected batches, and calculates the effect of exchanging them (hereinafter, the exchange effect). As described above, the exchange effect includes the difference in the amount of work W1 (e.g., the difference in the amount of work per aggregate unit) and the difference in the amount of work W2 (e.g., the difference in the amount of work per individual unit). The exchange effect is an index whose value increases as these differences decrease. In other words, performing an exchange process that increases the exchange effect is equivalent to leveling out the amount of work W1 and the amount of work W2 among multiple batches.

[0085] The exchange process may reduce the aggregation effect, so the exchange effect may further include an indicator whose value increases as the reduction in the aggregation effect in each batch decreases.

[0086] If the exchange effect satisfies the condition, the change unit 114 outputs the result of the exchange process as a modified batch allocation result. The condition may be, for example, that the exchange effect is greater than a threshold value. If the exchange effect does not satisfy the condition, the change unit 114 may repeatedly execute the exchange process until the exchange effect satisfies the condition. The number of batches and shipping orders to be exchanged is not limited to two, and may be three or more.

[0087] Any method may be used to select a plurality of batches to be exchanged and to select shipping orders from the selected batches, but for example, the following method may be used. · Random selection. Selecting multiple batches or shipment orders with large differences in the number of individual or aggregate items.

[0088] In the case of a system including a plurality of subsystems with different task units, the task leveling function (F2 above) is executed. The allocator 115 executes a function equivalent to the task leveling function.

[0089] The allocator 115 allocates the items included in each batch to a plurality of subsystems (for example, subsystem SS1, subsystem SS2) so that the workload W3 and workload W4 are equalized for each of the plurality of batches.

[0090] For example, the allocating unit 115 determines the allocation of aggregated items to workers in each batch based on the results of the current batch allocation. First, the allocating unit 115 aggregates details of the same items in each batch to create an aggregated unit, and calculates the workload when the aggregated units are allocated to each worker. For example, the allocating unit 115 calculates the workload by using the total quantity in the aggregated unit and the productivity of the worker (the number of items that can be processed per hour) as follows: workload (minutes) = 1 / (productivity) × 60 if the worker is a worker, or workload (minutes) = (quantity) / (productivity) × 60 if the worker is a picking robot. The allocating unit 115 determines the allocation of aggregated items based on the calculated workload so that the workload (minutes) for each worker is equalized. The productivity used to calculate the workload can be obtained, for example, from the worker master information 126.

[0091] In the following, an example will be described in which the multiple subsystems are a subsystem SS1 (e.g., picking system 501) that processes items in a task unit U1 and a subsystem SS2 (e.g., picking system 502) that processes items in a task unit U3. Also, an example will be described in which task unit U1 is an aggregate unit and task unit U3 is an individual unit, i.e., the number of items processed in task unit U3 is smaller than the number of items processed in task unit U1.

[0092] The allocating unit 115 allocates the items taking into consideration the conditions of the aggregated items that the picking robots can process. As an allocation method, for example, first allocating all aggregated items that the picking robots can process to the picking robots, allocating the remaining aggregated items to workers, and then, if the workload of the picking robots is greater than the workload of the workers, re-allocating the aggregated items to the workers in order of priority, thereby leveling out the workload.

[0093] That is, the allocating unit 115 first allocates item M1 (first item) included in the batch to subsystem SS1, excluding item M2 (second item) that is designated as the processing target for subsystem SS2, and then allocates item M2 to subsystem SS2. After that, if the workload W4 is greater than the workload W3, the allocating unit 115 reallocates some of item M2 to subsystem SS1. Whether a picking robot can process an item can be determined, for example, by the automatic processing capability flag in the item master information 123.

[0094] The allocation method is not limited to the above, and any other method may be used as long as it allocates items in a way that equalizes the workload of each worker. For example, the allocation unit 115 may use a method that obtains a more equalized result by changing the allocation of items between the picking robots and the workers and repeating the simulation.

[0095] The allocating unit 115 may perform allocation using mathematical optimization (combinatorial optimization). For example, the allocating unit 115 uses a binary variable Z that takes the value 1 when allocating the aggregated item n to the work entity m and takes the value 0 otherwise. nm The allocating unit 115 defines a model using Z that optimizes the effect of leveling by using a mathematical programming solver or a combinatorial optimization algorithm. nm By calculating the above, the task is allocated to the task subject.

[0096] An example of a model used by the allocating unit 115 will be described below. For example, the model is based on the following conditions shown in the following equations (6) to (8), as expressed by equation (9): k Z that minimizes the sum of nm This is a model that seeks to

number

number

number

number

[0097] The variables used in each formula are defined below. z nm: 1 if aggregate item n is assigned to work entity m, 0 otherwise N k : Set of aggregate items n in batch k M: A set of m workers a nm : Time required for aggregated item n to be picked by worker m

[0098] Equation (6) indicates that aggregated item n is assigned to one of the work agents m. Equation (7) indicates that the picking time of the work agent with the longest total picking time among all work agents m is within the batch completion time. Equation (9) indicates that the batch completion time t k represents the equation for minimizing

[0099] The output control unit 116 controls the output of various information used in the information processing device 100. For example, the output control unit 116 outputs output information (first output information) including the batch ID of the batch to which the order is assigned for each of a plurality of orders to the warehouse management system 200. This output information is, for example, total picking conversion information 127 shown in FIG. 9. The output control unit 116 may also output total picking workload information 128 shown in FIG. 10 as the output information.

[0100] Each unit included in the processing unit 110 (creation unit 111, allocation unit 112, calculation unit 113, change unit 114, distribution unit 115, and output control unit 116) is realized, for example, by one or more processors. For example, each of the above units may be realized by having a processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit) execute a program, i.e., by software. Each of the above units may be realized by a processor such as a dedicated IC (Integrated Circuit), i.e., by hardware. Each of the above units may be realized by a combination of software and hardware. When multiple processors are used, each processor may realize one of the units, or two or more of the units.

[0101] Furthermore, the information processing device 100 may be physically configured as one device or may be physically configured as multiple devices. For example, the information processing device 100 may be constructed in a cloud environment. Furthermore, each unit within the information processing device 100 may be distributed across multiple devices.

[0102] Next, a description will be given of information processing by the information processing apparatus 100 according to the embodiment. Fig. 11 is a flowchart showing an example of information processing according to the embodiment.

[0103] The creation unit 111 creates multiple batches based on the deadlines and batch sizes of the shipping orders (step S101). The allocation unit 112 executes batch allocation to allocate each of the multiple shipping orders to one of the batches (step S102).

[0104] Thereafter, by repeating steps S103 to S106, the batch leveling function (F1) and the work entity leveling function (F2) are executed.

[0105] First, the calculation unit 113 calculates a workload W1 (first workload) and a workload W2 (second workload) for each of the multiple batches obtained by batch allocation (step S103). The change unit 114 changes the order to be allocated to the batch so as to equalize the workload between the batches (step S104). The allocation unit 115 allocates the items included in the batch to multiple work entities (subsystems) so as to equalize the workload W3 and workload W4 for each of the multiple batches (step S105).

[0106] The processing unit 110 determines whether the termination condition for the batch allocation calculation is satisfied (step S106). If the termination condition is not satisfied (step S106: No), the process returns to step S103 and is repeated. If the termination condition is satisfied (step S106: Yes), the output control unit 116 outputs output information such as the total picking conversion information 127 (step S107), and ends the information processing.

[0107] The termination condition is, for example, one of the following conditions: The number of iterations exceeds the predetermined maximum. In step S104, the allocation was not changed. The improvement in the amount of work, number of aggregated items, or number of individual items per batch is below the predetermined minimum improvement amount.

[0108] The parameters such as the maximum number and the minimum improvement amount may be set in any manner, but for example, they are set by the following method. Registered in a setting file stored in the storage unit 120 or the like and read when the processing unit 110 starts processing. Registered as an environment variable of the OS (operating system) used in the information processing device 100 and read when the processing unit 110 starts processing. Passed as an argument to the execution command of the program that implements the processing unit 110.

[0109] Next, an example of information processing (order management) according to this embodiment will be described with reference to Fig. 12. Fig. 12 is a diagram for explaining an example of information processing according to this embodiment. Fig. 12 shows an example of the results of processing performed to level out the workload.

[0110] In the example of FIG. 12, three shipping orders with shipping order IDs "Order O1," "Order O2," and "Order O3" are entered as multiple shipping orders included in the shipping order information 121. The processing deadlines for each order are "12:00," "15:00," and "16:00." Note that for simplicity of explanation, the year, month, day, and seconds have been omitted. Also, the batch size of the sorter equipped in the sorting system 600 is assumed to be 2.

[0111] Each shipping order shall also include the following details: Order O1: Quantity of item M1 is 5, quantity of item M3 is 5, quantity of item M5 is 5 Order O2: 10 units of item M2, 10 units of item M3, and 10 units of item M4 Order O3: Quantity of item M3 is 10, quantity of item M5 is 5

[0112] The creation unit 111 creates a batch for allocating three shipping orders. Since the number of shipping orders is three, two batches (3 / 2=1.5, rounded up to the nearest whole number) are created. Although not shown in FIG. 12, it is assumed that the upper limit of the processing deadline for each batch is set to a time after 16:00 (for example, 17:00). The batch IDs of the two batches are "Batch B1" and "Batch B2," respectively.

[0113] The three orders are assigned to one of two batches with batch IDs "Batch B1" and "Batch B2." In the example of Figure 12, orders O1 and O3 are assigned to batch B1, and order O2 is assigned to batch B2.

[0114] In this case, within each batch, the items are aggregated as follows: Batch B1: 3 aggregated items corresponding to items M1, M3, and M5 Batch B2: 3 aggregated items corresponding to items M2, M3, and M4

[0115] Also, the number of individual items in each batch is as follows: Batch B1: 30 units (5 units of item M1, 15 units of item M3, 10 units of item M5) Batch B2: 30 units (10 units of item M2, 10 units of item M3, and 10 units of item M4)

[0116] Since the number of aggregated items (3 items) and the number of individual items (30 items) in the two batches are the same, the workload between the batches is leveled.

[0117] Assume that the productivity of the worker and the robot is 2 pieces / minute (aggregate unit) and 12 pieces / minute (individual unit), respectively. In this case, as shown in Figure 12, the worker's workload is 60 seconds and the robot's workload is 50 seconds.

[0118] For example, suppose that for batch B1, the tasks of item M3 and item M5 are swapped. In this case, the workload of the worker is 60 seconds (2 x 60 / 2), and the workload of the robot is 75 seconds (15 x 60 / 12). Compared to this case, in the example of FIG. 12, the difference in workload is smaller (10 seconds), and the time to complete batch processing is also shorter. In other words, in the example of FIG. 12, the workload between the worker and the robot is leveled out.

[0119] So far, we have explained an example in which the multiple systems with different task units are a picking system and a sorting system. However, the multiple systems with different task units are not limited to this and may be any other combination of systems. For example, the multiple systems may be a sorting system that processes items individually and a loading system that loads multiple sorted shipping orders into a unit (aggregate unit) onto a vehicle or the like for delivery to the shipping destination.

[0120] Although the above description mainly focuses on an example in which task unit U1 is an aggregate unit, task unit U2 is an individual unit, and task unit U3 is an individual unit, the combination of units is not limited to this. As long as the numbers of items to be processed are different, task units U1 and U2 may be combined in any way. Furthermore, as long as the numbers of items to be processed are different, task units U1 and U3 may be combined in any way. For example, suppose that subsystem SS1 is a picking robot that picks items in units of m (m is an integer greater than or equal to 1), and subsystem SS2 is a picking system that picks items in units of n (n is an integer greater than or equal to 1 such that m ≠ n). In this case, task unit U1 may be an aggregate unit that aggregates m items, and task unit U3 may be an aggregate unit that aggregates n items.

[0121] In this way, the information processing apparatus according to the embodiment can improve the efficiency of work in the entire system including a plurality of systems.

[0122] Next, the hardware configuration of the information processing apparatus according to the embodiment will be described with reference to Fig. 13. Fig. 13 is an explanatory diagram illustrating an example of the hardware configuration of the information processing apparatus according to the embodiment.

[0123] The information processing device of the embodiment includes a control device such as a CPU (Central Processing Unit) 51, a storage device such as a ROM (Read Only Memory) 52 and a RAM (Random Access Memory) 53, a communication I / F 54 that connects to a network and communicates, and a bus 61 that connects each part.

[0124] The programs executed by the information processing apparatus according to the embodiment are provided in advance in the ROM 52 or the like.

[0125] The program executed by the information processing device of the embodiment may be configured to be provided as a computer program product by being recorded in an installable or executable format on a computer-readable recording medium such as a CD-ROM (Compact Disk Read Only Memory), a flexible disk (FD), a CD-R (Compact Disk Recordable), or a DVD (Digital Versatile Disk).

[0126] Furthermore, the program executed by the information processing apparatus of the embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the program executed by the information processing apparatus of the embodiment may be provided or distributed via a network such as the Internet.

[0127] The programs executed by the information processing device of the embodiment can cause a computer to function as each of the above-mentioned parts of the information processing device. In this computer, the CPU 51 can read the programs from a computer-readable storage medium onto a main storage device and execute them.

[0128] A configuration example of the embodiment will be described below. (Configuration example 1) assigning each of a plurality of orders including first identification information identifying one or more types of items to one of a plurality of batches; For each of the plurality of batches, a first workload in a first system including a system for processing the items having the first identification information included in the batch in a first unit, and a second workload in a second system including a system for processing the items having the first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of items processed in the first unit, are calculated; modifying the orders included in the plurality of batches based on the first amount of work and the second amount of work; Processing section An information processing device comprising: (Configuration example 2) The processing unit changing the orders included in the plurality of batches so that the first amount of work and the second amount of work are equalized among the plurality of batches; The information processing device according to configuration example 1. (Configuration example 3) The processing unit changing the orders included in the plurality of batches by executing an exchange process in which one or more of the orders included in a first batch, which is included in the plurality of batches, are exchanged with one or more of the orders included in a second batch, which is included in the plurality of batches, so that a difference in the first workload between the first batch and the second batch and a difference in the second workload between the first batch and the second batch become smaller; The information processing device according to configuration example 1. (Configuration Example 4) the first system includes a first subsystem that processes the items with the first identification information included in the batch in the first unit, and a second subsystem that processes the items with the first identification information included in the batch in a third unit, the third unit being a unit of a number different from the number of items processed in the first unit; The processing unit calculating, for each of the plurality of batches, a third workload in the first subsystem and a fourth workload in the second subsystem when the articles having the first identification information included in the batch are allocated to the first subsystem and the second subsystem for processing; for each of the plurality of batches, the articles having the first identification information included in the batch are allocated to the first subsystem and the second subsystem based on the third workload and the fourth workload; The information processing device according to any one of configuration examples 1 to 3. (Configuration Example 5) The number of articles processed in the third unit is smaller than the number of articles processed in the first unit; The processing unit Among the items having the first identification information included in the batch, first items other than second items specified as processing targets of the second subsystem are allocated to the first subsystem, and the second items are allocated to the second subsystem; When the fourth amount of work is greater than the third amount of work, reallocating a portion of the second items to the first subsystem. The information processing device according to configuration example 4. (Configuration Example 6) the first subsystem is a system that picks the items with the first identification information included in the batch in the first unit, the second subsystem is a system that picks the items with the first identification information included in the batch in the third unit; The information processing device according to configuration example 4. (Configuration Example 7) The processing unit calculating the first workload by dividing the number of the first units included in the batch by the number of the first units processed by the first system per unit time; calculating the second workload by dividing the number of the second units included in the batch by the number of the second units processed by the second system per unit time; The information processing device according to any one of configuration examples 1 to 6. (Configuration Example 8) the first system is a picking system that picks items in the first unit, The second system is a sorting system that sorts the items picked in the first unit by the picking system in the second unit. The information processing device according to any one of configuration examples 1 to 6. (Configuration Example 9) The processing unit determining candidates for a batch to be allocated based on the processing deadlines of the plurality of orders, and repeating the process of determining the candidates so that the candidates include as many orders as possible that have the same first identification information, thereby determining a batch to which the plurality of orders are allocated; The information processing device according to any one of configuration examples 1 to 8. (Configuration Example 10) The processing unit outputting first output information including second identification information for identifying a batch to which the order is assigned, for each of the plurality of orders; The information processing device according to any one of configuration examples 1 to 9. (Configuration Example 11) An information processing method executed by an information processing device, Allocating each of a plurality of orders, each of which includes first identification information identifying one or more types of items, to one of a plurality of batches; calculating, for each of the plurality of batches, a first workload in a first system including a system for processing the items with the first identification information included in the batch in a first unit, and a second workload in a second system including a system for processing the items with the first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of items processed in the first unit; modifying the orders included in the plurality of batches based on the first amount of work and the second amount of work; An information processing method including: (Configuration Example 12) On the computer, Allocating each of a plurality of orders, each of which includes first identification information identifying one or more types of items, to one of a plurality of batches; calculating, for each of the plurality of batches, a first workload in a first system including a system for processing the items with the first identification information included in the batch in a first unit, and a second workload in a second system including a system for processing the items with the first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of items processed in the first unit; modifying the orders included in the plurality of batches based on the first amount of work and the second amount of work; A program to execute.

[0129] Although several embodiments of the present invention have been described, these embodiments are presented as examples and are not intended to limit the scope of the invention. These novel embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and their modifications are included within the scope and spirit of the invention, and are also included in the scope of the invention and its equivalents as defined in the claims. [Explanation of symbols]

[0130] 100 Information processing device 110 Processing section 111 Creation Department 112 Allocation Section 113 Calculation Unit 114 Changes 115 Sorting section 116 Output control section 120 Storage section 121 Shipping Order Information 122 Detail information 123 Item Master Information 124 Picking Station Information 125 Sorter Master Information 126 Work entity master information 127 Total Picking Conversion Information 128 Total picking workload information 200 Warehouse Management System 300 Storage System 400 Conveyor System 600 Sorting System

Claims

1. assigning each of a plurality of orders, each of which includes first identification information identifying one or more types of items, to one of a plurality of batches; For each of the plurality of batches, a first workload in a first system including a system for processing the items having the first identification information included in the batch in a first unit, and a second workload in a second system including a system for processing the items having the first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of items processed in the first unit, are calculated; modifying the orders included in the plurality of batches based on the first amount of work and the second amount of work; Processing section An information processing device comprising:

2. The processing unit changing the orders included in the plurality of batches so that the first workload and the second workload are equalized among the plurality of batches; The information processing device according to claim 1 .

3. The processing unit changing the orders included in the plurality of batches by executing an exchange process in which one or more of the orders included in a first batch, which is included in the plurality of batches, are exchanged with one or more of the orders included in a second batch, which is included in the plurality of batches, so that a difference in the first workload between the first batch and the second batch and a difference in the second workload between the first batch and the second batch become smaller; The information processing device according to claim 1 .

4. the first system includes a first subsystem that processes the items with the first identification information included in the batch in the first unit, and a second subsystem that processes the items with the first identification information included in the batch in a third unit, the third unit being a unit of a number different from the number of items processed in the first unit; The processing unit calculating, for each of the plurality of batches, a third workload in the first subsystem and a fourth workload in the second subsystem when the articles having the first identification information included in the batch are allocated to the first subsystem and the second subsystem for processing; for each of the plurality of batches, the articles having the first identification information included in the batch are allocated to the first subsystem and the second subsystem based on the third workload and the fourth workload; The information processing device according to claim 1 .

5. The number of articles processed in the third unit is smaller than the number of articles processed in the first unit; The processing unit Among the items with the first identification information included in the batch, first items other than second items specified as processing targets of the second subsystem are allocated to the first subsystem, and the second items are allocated to the second subsystem; When the fourth workload is greater than the third workload, a portion of the second items is reallocated to the first subsystem. The information processing device according to claim 4 .

6. the first subsystem is a system that picks the items with the first identification information included in the batch in the first unit, the second subsystem is a system that picks the items with the first identification information included in the batch in the third unit; The information processing device according to claim 4 .

7. The processing unit calculating the first workload by dividing the number of the first units included in the batch by the number of the first units processed by the first system per unit time; calculating the second workload by dividing the number of the second units included in the batch by the number of the second units processed by the second system per unit time; The information processing device according to claim 1 .

8. the first system is a picking system that picks items in the first unit, the second system is a sorting system that sorts the items picked by the picking system in the first unit in the second unit; The information processing device according to claim 1 .

9. The processing unit determining candidates for a batch to be allocated based on the processing deadlines of the plurality of orders, and repeating the process of determining the candidates so that the candidates include as many orders as possible that have the same first identification information, thereby determining a batch to which the plurality of orders are allocated; The information processing device according to claim 1 .

10. The processing unit outputting first output information including second identification information for identifying a batch to which the order is assigned, for each of the plurality of orders; The information processing device according to claim 1 .

11. An information processing method executed by an information processing device, assigning each of a plurality of orders, each of which includes first identification information identifying one or more types of items, to one of a plurality of batches; calculating, for each of the plurality of batches, a first workload in a first system including a system for processing the items having the first identification information included in the batch in a first unit, and a second workload in a second system including a system for processing the items having the first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of items processed in the first unit; modifying the orders included in the plurality of batches based on the first amount of work and the second amount of work; An information processing method including:

12. On the computer, assigning each of a plurality of orders, each of which includes first identification information identifying one or more types of items, to one of a plurality of batches; calculating, for each of the plurality of batches, a first workload in a first system including a system for processing the items having the first identification information included in the batch in a first unit, and a second workload in a second system including a system for processing the items having the first identification information included in the batch in a second unit, the second unit being a unit of a number different from the number of items processed in the first unit; modifying the orders included in the plurality of batches based on the first amount of work and the second amount of work; A program to execute.

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