Method, apparatus and program for processing information

Abstract

To make it possible to improve the average value of processability of each operator and prevent the ability from abruptly lowering, and to shorten the absolute operation time of each operator in long-term perspectives.SOLUTION: A method for processing information according to an embodiment, to be executed by a processor of an apparatus for processing information, includes: creating picking-operation data related to a picking operation for picking means to pick an article based on an order list acquired from an external system; executing shaping processing on the picking-operation data; and predicting processability of the picking means for the picking operation based on the picking-operation data shaping-processed.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] In recent years, in order to make picking work more efficient in logistics warehouses and the like, a system has been introduced in which automated guided vehicles (AGVs) are used to transport shelves containing items to multiple picking stations (PSs). At each picking station, a picking means such as a worker or a robot picks items from the shelves transported by the AGV. In order to maximize the throughput of the entire picking work process using this system, it is necessary to maximize the throughput of each PS while leveling out the work completion times between multiple PSs that process work in parallel.

[0003] Here, the throughput of each PS depends on the shelf waiting time, the hit rate (the number of tasks simultaneously performed on one shelf), and the task time required for each picking task.

[0004] In order to improve the throughput of each PS, it is necessary to reduce the waiting time at the shelves and improve the hit rate, which can be achieved by optimizing the AGV operation plan and the order processing order. On the other hand, in order to further improve the throughput, it is necessary to reduce the absolute work time of workers.

[0005] For example, Patent Document 1 discloses a technique for predicting the time required for a task by a worker, making the worker aware of the time as a target time, and improving the efficiency of picking work. Patent Document 1 also discloses a technique for predicting the time required for an assigned task and presenting it to each worker as a target time as a method for shortening the work time of each worker. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2023-005770 A Summary of the Invention [Problem to be solved by the invention]

[0007] There is a problem that measures to shorten the time required for each task are not necessarily effective for all workers. Furthermore, measures that only encourage the shortening of task times will make workers tired sooner, which will lead to a decrease in worker efficiency and a decrease in throughput in the long term.

[0008] The present invention has been made in light of the above-mentioned circumstances, and has as its object to provide a technique which can improve the average processing ability of each worker and prevent a sudden drop in ability, while also making it possible to shorten the absolute working time of each worker from a long-term perspective. [Means for solving the problem]

[0009] An information processing method executed by a processor of an information processing device according to an embodiment includes creating picking work data relating to a picking work in which a picking means picks an item based on an order list obtained from an external system, performing a shaping process on the picking work data, and predicting the processing capacity of the picking means for the picking work based on the shaping-processed picking work data. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram conceptually illustrating an example of the configuration of a picking system according to an embodiment. [Diagram 2] FIG. 2 is a block diagram illustrating an example of the configuration of the picking system. [Diagram 3] FIG. 3 is a block diagram illustrating an example of the configuration of a host management device in the picking system according to the embodiment. [Figure 4] FIG. 4 is a block diagram showing an example of the configuration of an AGV in the picking system according to the embodiment. [Diagram 5] FIG. 5 is a diagram illustrating an example of functions of a higher-level management device in the picking system according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of a process in which the work data creation unit creates a list of picking work data. [Figure 7] FIG. 7 is a diagram for explaining an example of a process in which the data reforming unit reforms picking operation data. [Figure 8] FIG. 8 is a diagram for explaining an example of the processing performed by the processing capacity prediction unit and the work planning unit. [Figure 9] FIG. 9 is a flowchart for explaining an example of the operation of the upper management device in a retrieval operation of an item in the picking system according to the embodiment. [Figure 10] FIG. 10 shows an example of the target effect of each picking means (operator) and the measures to be implemented to achieve that effect. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, the information processing method, the information processing device, and the information processing program will be described in detail with reference to the drawings. In the following embodiments, the parts with the same numbers perform the same operations, and the repeated description will be omitted. For example, when there are a plurality of identical or similar elements, a common symbol may be used to describe each element without distinguishing between them, and a subnumber may be used in addition to the common symbol to describe each element with distinction between them.

[0012] In the following description, the description A or B means at least one of A or B, and A, B, or C means at least one of A, B, or C. Furthermore, the description A and B also means at least one of A and B, and A, B, and C mean at least one of A, B, and C.

[0013] First, a picking system according to an embodiment is a system included in a logistics system installed in a logistics center or a warehouse, and is a system for picking items from shelves. The picking system transports shelves to a picking station using an automated guided vehicle (AGV). The picking system picks items from shelves at the picking station (PS) and controls a picking operation to sort the picked items into designated trays. The picking system causes picking means such as a worker or a robot to pick items from the shelves.

[0014] FIG. 1 is a diagram conceptually illustrating an example of the configuration of a picking system 100 according to an embodiment. FIG. 2 is a block diagram showing an example of the configuration of the picking system 100. 1 and 2, the picking system 100 includes a plurality of picking stations P (three in the example of FIG. 1), an upper level management device 1, a network 2, an external system 3, an AGV 7, and an AGV shelf 8. The picking station P includes a tray 10, a work management unit 112, and a picking means 113. The network 2 is connected to the upper level management device 1, the AGV 7, and the work management unit 112. The upper level management device 1 is connected to the external system 3.

[0015] The external system 3 transmits an order list indicating the items to be picked to the upper management device 1. The external system 3 can be realized by one or more computers. For example, the external system 3 may include a warehouse management system (WMS) that is responsible for managing the entry and exit of items or inventory management.

[0016] The host management device 1 (information processing device) manages information related to items stored in the warehouse. For example, the host management device 1 stores item management information indicating items stored on each AGV shelf 8. The host management device 1 also acquires an order list indicating items to be picked from an external system 3. The host management device 1 transports the AGV shelf 8 to each picking station P based on the order list. The host management device 1 instructs picking means waiting at the picking station P to perform the picking work. Furthermore, the host management device 1 acquires information related to the processing of items at each picking station P.

[0017] A warehouse control system (WCS) for controlling equipment in the warehouse may be provided between the host management device 1 and the work management unit 112 and the AGV 7. Some of the functions of the host management device 1, which will be described later, may be performed by the WMS or WCS.

[0018] The network 2 relays communications between the upper management device 1, the AGV 7, and the work management unit 112. For example, the network 2 is a local area network (LAN). The AGV 7 may be connected to the network 2 wirelessly.

[0019] The AGV 7 transports the AGV shelf 8 to the picking station P. The AGV 7 operates based on control signals from the higher-level management device 1 or the work management unit 112. For example, the AGV 7 travels toward a designated loading position and lifts up the AGV shelf 8 at the designated loading position. The AGV 7 travels toward a designated unloading position and unloads the AGV shelf 8 at the designated unloading position (for example, a specified picking station P). In addition, after the picking work at the picking station P is completed, the AGV 7 returns the AGV shelf 8 to the item storage area.

[0020] The AGV shelf 8 is disposed in an item storage area. The AGV shelf 8 is a shelf that stores items. For example, the AGV shelf 8 stands upright on four pillars. The height below the shelf of the AGV shelf 8 (height from the floor to the bottom of the shelf) is higher than the height of the AGV 7. This allows the AGV 7 to slip under the shelf of the AGV shelf 8. After slipping under the shelf, the AGV 7 uses a pusher to lift the AGV shelf 8 to a position where the tips of the pillars are a few centimeters above the floor, and travels with the AGV shelf 8 lifted. In this way, the AGV 7 transports the AGV shelf 8.

[0021] Furthermore, shelf identification information that can be read by a fixed camera or a mobile camera, etc. may be attached to the AGV shelf 8. Item identification information that can be read by a fixed camera or a mobile camera, etc. may also be attached to the items. For example, the shelf identification information and item identification information are bar codes or two-dimensional codes. Note that the picking system 100 may include multiple readers that read the shelf identification information and item identification information, in addition to the fixed camera or mobile camera.

[0022] 1, the picking station P is disposed in a retrieval work area. The picking station P receives an AGV shelf 8 transported by an AGV 7. The picking station P picks up an article from the received AGV shelf 8.

[0023] At the picking station P, trays 10 corresponding to each piece of allocated order information are prepared. At the picking station P, picked items are placed on the trays 10. At the picking station P, trays 10 corresponding to each piece of allocated order information are prepared, and when all the necessary items are present in the tray 10, it is ejected from the picking station P and a new empty tray is replenished. The tray 10 ejected with all the necessary items is sent to the subsequent process in the warehousing work area, where it is packed, sorted, and loaded.

[0024] The work management unit 112 manages the picking work at the picking station P. The work management unit 112 includes a display unit and an operation unit. For example, the work management unit 112 includes a desktop PC, a notebook PC, or a tablet PC. The work management unit 112 displays information indicating the items to be picked on the display unit in accordance with control from the upper management device 1. The work management unit 112 also accepts input of an operation indicating the items that have been picked from a worker as the picking means 113. The work management unit 112 transmits information indicating the input operation to the upper management device 1.

[0025] For example, a digital assort system (DAS) is used as the work management unit 112. The DAS as the work management unit 112 scans the barcode of an item picked from a shelf by the picking means 113, and lights up a lamp corresponding to the tray into which the scanned item is to be sorted. When the work management unit 112 finishes sorting the items onto a tray, the worker presses a switch at the position of the tray, completing the work, and creates a work log showing the work results (work performance) such as the work time. After creating the work log, the work management unit 112 supplies the created work log to the upper management device 1.

[0026] The picking means 113 picks up an item from the AGV shelf 8 in accordance with an instruction from the upper management device 1. In this embodiment, the picking means 113 is an operator. Note that, as shown in FIG. 1 and other figures, only an operator is shown as the picking means 113, but it goes without saying that the picking means 113 may include both an operator and a picking robot.

[0027] The picking means 113 as an operator visually checks the items displayed on the work management unit 112 and picks the items. The picking means 113 puts the picked items into the tray 10. When the picking means 113 puts the items into the tray 10, it inputs an operation to the work management unit 112 indicating the items for which picking has been completed.

[0028] The picking station P may be equipped with a camera for monitoring the operation of the picking means 113. The start and end of the work of the picking means 113 may be determined based on images captured by the camera. In addition, the presence or absence of interrupt processing or abnormality during work may be determined, and the information may be added to the work log.

[0029] Next, the configuration of the host management device 1 in the picking system 100 according to the embodiment will be described. FIG. 3 is a block diagram showing an example of the configuration of the upper management device 1 in the picking system 100 according to the embodiment. The upper management device 1 is configured with one or more computers. For example, the upper management device 1 includes a processor 11, a ROM 12, a RAM 13, an auxiliary storage device 14, and a communication interface 15.

[0030] The processor 11, the ROM 12, the RAM 13, the auxiliary storage device 14, and the communication interface 15 are connected to one another via a data bus or an interface. The processor 11 has a function of controlling the overall operation of the upper level management device 1. The processor 11 may include an internal cache and various interfaces. The processor 11 realizes various processes by executing programs stored in advance in the internal memory, the ROM 12, or the auxiliary storage device 14.

[0031] For example, the processor 11 is a central processing unit (CPU). The processor 11 may be realized by hardware such as a large scale integration (LSI), an application specific integrated circuit (ASIC), or a field programmable gate array (FPGA).

[0032] The ROM 12 is a non-transitory computer-readable storage medium and stores the above-mentioned programs. The ROM 12 also stores data or various setting values ​​used by the processor 11 when performing various processes. The RAM 13 is a memory used for reading and writing data.

[0033] The RAM 13 is used as a so-called work area for storing data that is temporarily used when the processor 11 performs various processes.

[0034] The auxiliary storage device 14 is a non-transitory computer-readable storage medium, and may store the above-mentioned programs. The auxiliary storage device 14 also stores data used by the processor 11 in performing various processes, data generated by the processes in the processor 11, various setting values, and the like.

[0035] The auxiliary storage device (storage device) 14 pre-stores item management information indicating items stored on each AGV shelf 8. For example, the item management information stores a shelf code indicating the AGV shelf 8 and an item code indicating the item stored on the AGV shelf 8 in association with each other.

[0036] The upper management device 1 may be transferred with the above program stored in the ROM 12 or the auxiliary storage device 14, or may be transferred without storing the above program. In the latter case, the upper management device 1 reads the above program stored in a removable storage medium such as an optical disk or a semiconductor memory, and writes the read program to the auxiliary storage device 14. Alternatively, the upper management device 1 downloads the above program via the network 2 or the like, and writes the downloaded program to the auxiliary storage device 14.

[0037] The communication interface 15 is an interface for transmitting and receiving data to and from various devices. The communication interface 15 is connected to the AGV 7, the work management unit 112, and the like. The communication interface 15 also acquires an order list and the like from the external system 3 and the like. For example, the communication interface 15 supports a LAN (local area network) connection and the like. The communication interface 15 may also be configured to include an interface for transmitting and receiving data to and from the external system 3, an interface for transmitting and receiving data to and from the AGV 7, and an interface for transmitting and receiving data to and from the work management unit 112.

[0038] For example, the upper management device 1 may obtain a new order list from the WMS via the communication interface 15 and the network 2. In addition, the upper management device 1 may transmit the formulated work plan data to the WCS and execute the work instructions to the AGV 7 or the picking means 113 through the WCS.

[0039] Next, the configuration of the AGV 7 in the picking system 100 according to the embodiment will be described. FIG. 4 is a block diagram showing an example of the configuration of the AGV 7 in the picking system 100 according to the embodiment. The AGV 7 includes a processor 71, a ROM 72, a RAM 73, an auxiliary storage device 74, a communication interface 75, a drive unit 76, a sensor 77, a battery 78, a charging mechanism 79, and tires 70.

[0040] The processor 71 has a function of controlling the overall operation of the AGV 7. The processor 71 may include an internal cache and various interfaces. The processor 71 executes programs stored in advance in the internal memory, the ROM 72, or the auxiliary storage device 74 to realize various processes.

[0041] For example, the processor 71 is a CPU. The processor 71 may be realized by hardware such as an LSI, an ASIC, or an FPGA. The processor 71 performs processes such as calculations and controls required for operations such as acceleration, deceleration, stopping, direction changes, and loading and unloading from the AGV shelf 8. The processor 71 executes a program stored in the ROM 72 or the like based on a control signal from the upper management device 1 or the work management unit 112, etc., to generate drive signals and output them to each unit.

[0042] For example, the upper management device 1 or the work management unit 112 transmits a control signal to move the AGV 7 from the current position to a first position (the position of the target AGV shelf 8) and from the first position to a second position (the position of the target picking station P). The upper management device 1 or the work management unit 112 also transmits a control signal to move the AGV 7 from the second position to the first position. The processor 71 of the AGV 7 outputs a drive signal in response to the control signal transmitted from the upper management device 1 or the work management unit 112. As a result, the AGV 7 moves from the current position to the first position, moves from the first position to the second position, and moves from the second position to the first position. The processor 71 also outputs a drive signal in response to an instruction to load and unload the AGV shelf 8 contained in the control signal transmitted from the upper management device 1 or the work management unit 112. As a result, the AGV 7 lifts the AGV shelf 8 by the pusher and lowers the lifted AGV shelf 8.

[0043] The ROM 72 is a non-transitory computer-readable storage medium, and stores the above-mentioned programs. The ROM 72 also stores data or various setting values ​​used by the processor 71 when performing various processes. The RAM 73 is a memory used for reading and writing data. The RAM 73 is used as a so-called work area for storing data temporarily used by the processor 71 when performing various processes.

[0044] The auxiliary storage device 74 is a non-transitory computer-readable storage medium, and may store the above-mentioned programs. The auxiliary storage device 74 also stores data used by the processor 71 in performing various processes, data generated by the processes in the processor 71, various setting values, and the like.

[0045] The communication interface 75 is an interface for transmitting and receiving data to and from the higher level management device 1 or the work management unit 112 via a wireless LAN access point, etc. For example, the communication interface 75 supports wireless LAN connection.

[0046] The driving unit 76 is a motor or the like, and rotates or stops the motor based on a driving signal output from the processor 71. The power of the motor is transmitted to the tires 70 and then to the steering mechanism. The AGV 7 moves to a target position by the power from the motor.

[0047] Furthermore, with the AGV 7 submerged under the AGV shelf 8, the drive unit 76 rotates the motor (forward rotation) based on the drive signal output from the processor 71. The power from this motor raises the pusher, lifting the AGV shelf 8. Furthermore, after the AGV 7 reaches the destination position, the drive unit 76 rotates the motor (reverse rotation) based on the drive signal output from the processor 71. The power from this motor lowers the pusher, lowering the AGV shelf 8 to the floor.

[0048] The sensor 77 is a plurality of reflection sensors. Each reflection sensor is attached around the AGV 7. Each reflection sensor irradiates a laser beam, detects the time from when the laser beam is irradiated until the laser beam is reflected by an object and returns, detects the distance to the object based on the detected time, and notifies the processor 71 of a detection signal.

[0049] The processor 71 outputs a control signal for controlling the travel of the AGV 7 based on a detection signal from the sensor 77. For example, the processor 71 outputs a control signal such as deceleration or stop to avoid collision with an object based on a detection signal from the sensor 77. Note that a camera may be provided in addition to the sensor 77, and the camera may capture an image of the surroundings and output the captured image to the processor 71. In this case, the processor 71 analyzes the captured image and outputs a control signal such as deceleration or stop to avoid collision with an object.

[0050] The battery 78 supplies the necessary power to the drive unit 76 etc. The charging mechanism 79 is a mechanism that connects a charging station and the battery 78, and the battery 78 is charged with power supplied from the charging station etc. via the charging mechanism 79.

[0051] Next, functions of the upper level management device 1 in the picking system 100 according to the embodiment will be described. FIG. 5 is a diagram showing an example of functions of the upper level management device 1 in the picking system 100 according to the embodiment. The host management device 1 has a database 121 provided in a storage device such as the internal memory of the processor 11, the ROM 12, or the auxiliary storage device 14. The database 121 as a storage device stores various types of data. The data stored in the database 121 is output to the outside of the host management device 1 via the communication interface 15. In addition, data input to the host management device 1 via the communication interface 15 is saved in the database 121.

[0052] The various types of data stored in database 121 include order lists obtained from external system 3, item data in the warehouse, picking means data, AGV data, model data, work plan data, order lists, and formatted data formatted based on work performance.

[0053] The item data is data related to the items to be picked, such as the item ID, the number, weight, volume, shape, material, storage shelf ID, and storage position within the shelf.

[0054] The picking means data is data related to the picking means. When the picking means 113 is a person (worker), the picking means data is person attribute data. Examples of the person attribute data as the picking means data include the worker ID, age, sex, height, exercise experience, years of employment, employment type, and working duration.

[0055] The AGV data is data related to the AGV 7. The AGV data includes, for example, the device ID, the number of years of use, the charge rate, and the status (standby, in use, returning).

[0056] The formatted data is generated by formatting picking work data related to the picking work. The formatted data is generated whenever an order list or a work log is obtained, and is stored in the database 121.

[0057] The work log is data related to the work results for the instructed picking work. For example, the work log is data in which data collected from the work management unit 112 is assigned to each picking work unit (item ID, number of items picked, item storage position in the shelf, tray position to which the items are inserted). In this case, the data collected from the work management unit 112 is data such as the worker ID, work time (actual value), interrupt processing, and the presence or absence of abnormality. The work log may also include data in which data collected from the AGV is assigned to each transport work unit (transported shelf ID, initial shelf position, transport destination picking station ID). In this case, the data collected from the AGV 7 is data such as the equipment ID, position at the start of the work, movement route, presence or absence of collision avoidance action, movement distance, power consumption, transport time, etc.

[0058] 5, the upper management device 1 has a task data creation unit 101, a data shaping unit 102, a processing capacity prediction unit 103, a task planning unit 104, and a measure setting condition determination unit 105. The task data creation unit 101, the data shaping unit 102, the processing capacity prediction unit 103, the task planning unit 104, and the measure setting condition determination unit 105 are functions that are realized by the processor 11 executing a program stored in a storage device such as the internal memory of the processor 11, the ROM 12, or the auxiliary storage device 14.

[0059] The upper level management device 1 of the embodiment stores in a storage device such as a ROM or an auxiliary memory device 14, as programs executed by the processor 11, such as a program for creating picking work data from an order list, a program for formatting picking work data, a program for predicting the processing capacity of the picking means 113, a program for making work plans, and a program for determining policy setting conditions.

[0060] The processor 11 functions as the operation data creation unit 101 by executing a program that creates picking operation data from the order list. The operation data creation unit 101 creates a list of picking operation data related to the operation content to be performed at each picking station P (i.e., performed by each picking means) based on the order list acquired from the external system 3 and the inventory data stored in the database 121. The picking operation data is data including operation attribute data such as the number of items to be picked, weight, volume, storage position of the items on the shelf, and position of the tray 10 into which the items are inserted.

[0061] The processor 11 functions as a data shaping unit 102 by executing a program for shaping the picking work data. The data shaping unit 102 performs shaping processing on the picking work data to be used for predicting the processing capacity of the picking means 113 and for work planning, based on the picking work data created by the work data creation unit 101 and data in which a work log is added to the picking work data. Here, the shaping processing includes linking the picking work data with picking means data, action data, workload data, etc., and preprocessing such as variable conversion and scaling for various data.

[0062] The processor 11 executes a program for predicting processing capacity, thereby functioning as a processing capacity prediction unit 103. The processing capacity prediction unit 103 generates data on the processing capacity of each picking means 113 for each picking task to be performed, based on the shaped picking task data, and outputs the generated data to a task planning unit 104, which will be described later.

[0063] The processor 11 executes a program for carrying out work planning, thereby functioning as a work planning unit 104. The work planning unit 104 formulates work plans for work allocation to each picking means 113, measures to be applied, and the AGV 7 to be used for shelf transport, based on the processing capacity data of the picking means 113 output by the processing capacity prediction unit 103 and data such as the operation status in the warehouse.

[0064] The processor 11 executes a program for determining the action setting conditions, thereby functioning as the action setting condition determination unit 105. The action setting condition determination unit 105 determines the conditions of the action to be set next based on the performance value of the processing capacity or fatigue level in the work log.

[0065] Next, the process executed by the work data creation unit 101, which is a function of the higher level management device 1, will be described. The host management device 1 acquires an order list from the external system 3. The host management device 1 may also acquire inventory data in a warehouse, shipping time, transport truck operation data, and the like from the external system 3. The host management device 1 stores the acquired data in the database 121.

[0066] Order lists are typically obtained in batches determined based on shipping times and truck constraints. Reordering of orders or changes to work allocations are performed within these batches.

[0067] Depending on the progress of work at each picking station P, shelf call interference or waiting for work at the picking station P may occur. To avoid this, the upper level management device 1 may change the execution order (shelf call order) within the range of assigned work even after allocating work to the picking station P. If it is still difficult to avoid this or if a major change in the plan is required from the perspective of work leveling, the upper level management device 1 may change the assigned picking station P for work that has not yet undergone shelf call among the assigned work.

[0068] The range or timing of operations for which the assigned picking station P can be changed differs depending on the number of trays 10 provided in the picking station P or the management method thereof. When trays 10 are replenished in each picking station P with order IDs and tray IDs linked in advance, the order of operations corresponding to the replenished trays 10 can be changed, but the assignment destination cannot be changed to another picking station P. When order IDs and tray IDs are linked in each picking station P and can be changed up until just before the operation, the upper management device 1 can change the plan over a wider range.

[0069] The work data creation unit 101 creates attributes X1, X2, ..., X3 related to the items and picking work based on the acquired order list and the inventory data stored in the database 121. n Here, n is an arbitrary positive integer representing the number of attributes. That is, the operation data creation unit 101 creates picking operation data related to the picking operation in which the picking means 113 picks up an item based on the order list and the inventory data.

[0070] The attributes of an item are data including the weight and volume of the item, the shelf ID where the item is stored, the storage position within the shelf, the storage state (whether the cardboard box is opened or unopened), etc. Furthermore, the attributes of a picking operation are data including the number of items picked, the position of the tray 10 into which the item is inserted, whether a step stool is used, etc. Note that the position of the tray 10 into which the item is inserted or whether a step stool is used is assigned at the time of confirmation.

[0071] FIG. 6 is a diagram for explaining an example of a process in which the work data creation unit 101 creates picking work data. In the example of Figure 6, there are tasks with task numbers (task IDs) from "1" to "D", and attributes X related to items and picking tasks are assigned to each task. For example, X1 is the number of items to be picked, X2 is the storage position on the shelf, and X n indicates the tray position where the item is inserted.

[0072] Furthermore, when creating the picking work data, the work data creation unit 101 may rearrange the picking work so that picking work that can be performed simultaneously in one shelf call is grouped together, and group multiple picking work together as a work unit to be assigned to the picking means 113. In this case, the work data creation unit 101 links the shelf to be called for each grouped work unit.

[0073] There are two ways to sort and organize the picking tasks. The first is to sort the items stored in the called shelf. A If multiple items are listed in the order information, the same item I A The second is to pick up multiple items I and place them in multiple trays 10. A ,I B If they are stored together on the shelf you called, different items I A ,I B You can also pick them all together from the same shelf. You can also combine the above two methods.

[0074] Next, a process of shaping picking operation data by the data shaping unit 102, which is a function of the upper level management device 1, will be described. For example, the data reforming unit 102 converts the attributes Y1, Y2, ..., Y m , measures Z1,Z2,…,Z l , workload W, the processing capacity T of the picking means 113, etc., and pre-processing of each data string. Here, m and l are any positive integers that represent the number of attributes and the number of measures of the picking means 113, respectively. That is, the data reforming unit 102 executes a reforming process on the picking work data.

[0075] Attributes Y1, Y2, ..., Y of the picking means 113 m For example, the information includes the worker ID, age, sex, height, exercise experience, years of employment, employment type, the duration of work that has elapsed since the start of work at the current time, fatigue level, etc.

[0076] Here, the fatigue level may be estimated based on the pulse and body movement measured by wearing a wristband sensor by the worker. Alternatively, the fatigue level may be estimated based on the captured work actions taken by a camera installed in the picking station P. Alternatively, the fatigue level may be estimated based on the performance of the processing capacity collected as a work log.

[0077] Measures Z1,Z2,…,Z l These include the presentation of information via the work management unit 112, changes to the work to be assigned, and constraints on the workload W. For example, when a measure that displays a target work time corresponds to Z1, implementing this measure is represented as Z1=1, and not implementing it is represented as Z1=0.

[0078] Measures for presenting information include those related to the target work time and the estimated time for completing the work. For example, when you want to increase the pace of the worker, present a target work time faster than the current pace or the expected time for completing the work at the current pace. When you want to decrease the pace, present a target work time slower than the current pace.

[0079] Further, measures related to information presentation include presenting information to support the picking work that the worker should perform, presenting characters, playing music, presenting the amount of incentive, presenting the ranking of the workers, etc.

[0080] The measure for changing task allocation involves quantifying the load of picking work based on task attributes, and when a worker is working at a slow pace or their processing ability is reduced due to fatigue, a less demanding task is assigned to that worker, and a more demanding task is assigned to a worker who is working at a faster pace than expected or who is rushing too fast.

[0081] The workload W is a numerical value that represents the physical load when performing, for example, picking work. The workload is calculated by the attributes X1, X2, ..., X n and attributes Y1, Y2, ..., Y m In addition, data with preset values ​​may be prepared and the corresponding values ​​may be read in. In addition, attributes X1, X2, ..., X related to past items and picking work may be n , attributes Y1, Y2, ..., Y m A model for estimating the load may be prepared by analyzing the relationship between the actual fatigue level and the load.

[0082] The workload W will be higher, for example, if an item stored at a high place cannot be picked without using a step stool. Also, the farther the tray 10 into which the item is to be placed is located from the picking position, the higher the workload W will be. Alternatively, the greater the number or weight of the items, the higher the workload W will be.

[0083] Conversely, for example, if the items are stored at waist height and can be picked without using a step stool, the workload W will be lower. Also, the closer the tray 10 into which the items are to be inserted is to the picking position, the lower the workload W will be. Or, the smaller the number or weight of the items, the lower the workload W will be.

[0084] The constraint on the workload W included in the policy refers to a policy that limits the allocation to tasks with a small workload W or tasks with a large workload W. If you want to slow down the work pace of a specific worker, for example, set a constraint on the workload W by a policy such that W<0.3 as shown in Figure 8.

[0085] The processing capacity T of the picking means 113 is, for example, the work time required for the picking work.

[0086] The operation time may be calculated, for example, by using a digital sorting system as the operation management unit 112, from the difference between the arrival time of the AGV 7 and the time when a switch located at the position of the destination tray 10 is pressed. Alternatively, the upper level management device 1 may determine the start and end times of the picking operation from images captured by a camera installed at the picking station P, and calculate the operation time.

[0087] The upper level management device 1 may determine whether there was an interruption or an abnormality during work from the camera image as work results, and may add the information to the work log as flag data. The upper level management device 1 may perform various data processing or analysis except for the data with the flag.

[0088] The preprocessing for each data sequence is, for example, variable transformation or scaling.

[0089] Information regarding the storage location of the item and the location of the destination tray 10 is managed using letters and numbers, such as A1 or B21, as shown in Fig. 6. However, as this does not provide meaningful information for data processing or analysis, the data reforming unit 102 implements methods such as converting the information into dummy variables (binary values ​​of 0 or 1) or converting the information into continuous values ​​based on equipment information of the facility.

[0090] When the range of values ​​that can be taken by variables in the shaped picking operation data is different, the data shaping unit 102 executes a scaling process. For example, a process is performed to normalize the value of each variable to a specified range. For example, the process of normalizing to the range of [0, 1] is executed using the following formula 1. Here, x (i) is the i-th sample of the data x, and min and x max are the minimum and maximum values ​​of data x, respectively, and x norm (i) is the normalized variable.

[0091] x norm (i) =(x (i) -x min ) / (x max -x min ) (Formula 1)

[0092] FIG. 7 is a diagram for explaining an example of a process in which the data reforming unit 102 reforms the picking operation data. The shaped picking work data shown in FIG. 7 shows picking work data shaped using picking work data, picking means data, action data, and work log data. In the example of FIG. 7, attributes related to items and picking work are converted into dummy variables (binary 0 or 1) or converted into continuous values, and scaling is performed on the data in each cell. Therefore, in the example of FIG. 7, X' is used to clearly indicate that the attributes are related to items and picking work that have been shaped. The data shaping unit 102 stores the shaped picking work data in the database 121.

[0093] Next, the processes executed by the processing capacity prediction unit 103 and the work planning unit 104, which are functions of the upper level management device 1, will be described. FIG. 8 is a diagram for explaining an example of the processing performed by the processing capacity prediction unit 103 and the work planning unit 104. As shown in FIG. In the example of FIG. 8, operations 1 to D are considered to be assigned to any of picking means a to c.

[0094] The processing capacity prediction unit 103 predicts the processing capacity of each worker (picking means 113) for the picking work to be assigned based on the data obtained by shaping the picking work data. At this time, the prediction of the processing capacity of the picking means 113 is based on the measures Z1, Z2, ..., Z l The implementation is divided into cases depending on the presence or absence of the above. Fig. 8 shows an example in which the processing capacity of the picking means 113 is predicted for each measure. Then, the work planning unit 104 formulates an optimal combination of the allocation work and the measures as a work plan, among the possible combinations of allocation, while satisfying various constraints. Fig. 8 shows an example in which each work is allocated to picking means a to c.

[0095] For example, the prediction of the processing capacity may be performed by extracting the performance value of a picking operation having similar conditions to the next picking operation from a past operation log and using the performance value as the predicted value. Alternatively, a function (prediction model) may be constructed using machine learning or the like, with attribute data related to the operation to be performed as explanatory variables and the processing capacity as the objective variable.

[0096] In other words, the processing capacity prediction unit 103 predicts the processing capacity of the picking means 113 using a prediction model learned with attribute data related to the picking work to be performed based on the picking work data as explanatory variables and the processing capacity of the picking means 113 as the objective variable.

[0097] The processing capacity may be a probability distribution of the operation time. In this case, the mean value of the probability distribution and the value of the one-sided α point may be used as a representative value of the processing capacity for the operation time.

[0098] A prediction model of processing capacity may be constructed individually for each picking means 113. Also, multiple models may be constructed classified by the attributes or specifications of the picking means 113. Furthermore, a general-purpose model may be constructed that predicts processing capacity from the attributes of the picking work or the picking means 113 and the presence or absence of measures.

[0099] When predicting the processing capacity of a picking means 113 with no past work records, the capacity may be calculated from work records with similar attributes of the picking means 113 in past work logs. Alternatively, a model of a picking means with similar attributes or specifications may be selected from already constructed prediction models, and operation may be started.

[0100] Attributes X1, X2, …, X related to items and picking operations n , attributes Y1, Y2, ..., Y m , measures Z1,Z2,…,Z l The content of and the calculation rules for the workload W can be set by a system administrator. The system administrator may also review the settings depending on the operating status of the system.

[0101] The various constraints are that it is possible to achieve this given the operating status of the AGV shelves 8 and AGVs 7, and that the latest time for each picking station P to finish processing all of the assigned picking tasks does not exceed the process deadline, which is determined based on the shipping time.

[0102] Among them, the optimal combination of allocation work and measures is one that averages out the work completion times of each picking station P and minimizes the total time required for the station that takes the longest. Therefore, measures for each worker are basically selected so that the average processing capacity increases compared to the case without any measures.

[0103] Next, a function implemented by the policy setting condition determination unit 105, which is a function of the higher level management device 1, will be described. The measure setting condition determination unit 105 changes the measure to be executed next when the processing capacity of the picking means 113 is not within a predetermined range of the predicted processing capacity.

[0104] The determination of the policy setting conditions is performed based on the work results collected from each picking station P (i.e., each picking means 113). For example, when setting at the beginning of the work, the policies are limited to those that increase the processing capacity at each picking station P. Therefore, in the work plan created initially, combinations of policies that have the opposite effect (reducing processing capacity) are excluded. As the picking work progresses, for a picking station P that is determined to have experienced a decrease in processing capacity or accumulated fatigue, the policy setting conditions are changed to load reduction and a work plan is drawn up again. At this time, policies such as increasing the processing capacity of the relevant station or allocating work with a high load are excluded.

[0105] As a measure to increase the average processing capacity, for example, a method of presenting a target work time can be considered. This target work time may be set based on past performance data of an individual who has worked longer than the target worker and has a higher processing capacity for picking work. In addition, the measure setting condition determination unit 105 may set a value obtained by multiplying a certain percentage (for example, a 10% reduction) based on the target worker's own past work performance as the target time (new measure).

[0106] Another possible measure to increase the average throughput is to display the remaining time until the task is completed. This remaining time is calculated, for example, based on the sum of the estimated task times for the picking tasks that have not yet been performed.

[0107] On the other hand, as working hours increase, workers' processing ability may decrease due to fatigue. However, if it is difficult to take breaks at will and workers must continue working, measures can be considered such as limiting work to picking work, which is less strenuous. This will prevent further decline in processing ability or restore processing ability.

[0108] Conversely, if it is expected that the processing capacity will be higher than expected and disrupt the leveling, measures such as allocating more picking work, which is more of a load, can be considered.

[0109] Measures for each worker do not need to be uniform for all workers, and each worker may be individually implemented with what is effective at the time. Therefore, while a measure to present a target time is implemented for one picking station P, a measure to detect fatigue of a worker at another picking station P and limit the allocation of the worker to picking work with low load may be implemented. It may also be determined that it is best to implement no measures at all.

[0110] In the above explanation, only the operation time of the picking means 113 waiting at the picking station P was mentioned. However, if the next AGV shelf 8 to be used has not arrived at the picking station P and a waiting time occurs, it will affect the throughput of the entire process. Therefore, the operation allocation needs to be determined comprehensively, taking into account the expected waiting time.

[0111] When the number of AGVs 7 is limited, it is necessary to optimize the operation of the AGVs 7 so as to shorten the waiting time at the picking station P or the movement time of the AGVs 7. Therefore, from the viewpoint of the processing capacity of the picking means 113, a work plan that is not necessarily optimal may be adopted.

[0112] Next, the operation of the host management device 1 in the picking system 100 according to the embodiment will be described. FIG. 9 is a flowchart for explaining an example of the operation of the host management device 1 in a retrieval operation of an item in the picking system 100 according to the embodiment. The operation of this flowchart is realized by the processor 11 of the upper level management device 1 reading and executing a program stored in the internal memory of the processor 11, the ROM 12, or the RAM 13.

[0113] In step S101, in the retrieval work of goods, the upper level management device 1 acquires an order list from the external system 3 via the communication interface 15. For example, the order list is made up of orders that associate goods to be picked with the delivery destination of the goods, etc. Here, the order list is assumed to be one batch of orders made up of a plurality of orders. The order may be an order slip or the like. The upper level management device 1 may acquire the order list from an external storage device via an interface for the external storage device, or may accept an order list input by a worker using an operation unit or the like.

[0114] In step S102, the processor 11 creates picking work data. The processor 11 functioning as the work data creation unit 101 creates the picking work data based on the order list and the inventory list through the above-described processing.

[0115] In step S103, the processor 11 formats the picking operation data. The processor 11 functioning as the data formatter 102 formats the picking operation data based on the operation data and the log data by the above-mentioned process. Here, when there is no log data and the picking operation data is first formatted, the processor 11 formats the picking operation data based on the attributes Y1, Y2, ..., Y m , measures Z1,Z2,…,Z l For the workload W, the provisional data may be used as log data to shape the picking operation data.

[0116] In step S104, the processor 11 sets the action setting conditions. The action setting condition determination unit 105 sets the action setting conditions. As described above, when step S104 is performed for the first time, the action setting condition determination unit 105 limits the action setting conditions to those that increase the processing capacity in each picking station P. However, when S104 is performed for the second or subsequent times (i.e., when processing the second or subsequent batches), it is not necessary to set the above conditions, and the action setting conditions set in step S112 described later are used.

[0117] In step S105, the processor 11 predicts the processing capacity. The processor 11 functioning as the processing capacity prediction unit 103 predicts the processing capacity of each picking means 113 by distinguishing between the presence or absence of a measure through the above-described process.

[0118] In step S106, the processor 11 determines a work plan. The processor 11 functioning as the work planner 104 creates work plan data by the above-mentioned process. For example, when processing step S106 for the first time, the measures set in step S104 are limited to those that increase the processing capacity of each picking means 113. Therefore, the work planner 104 excludes work plans that reduce the efficiency of the picking means 113 in accordance with the measures.

[0119] FIG. 10 is a diagram showing an example of the target effect of each picking means 113 (worker) and the image of the measures to be taken to achieve that effect. 10, the predicted processing ability of the top worker is more efficient than that of a general worker, the predicted processing ability of the middle worker is general, and the predicted processing ability of the bottom worker is lower than the general processing ability. In such a case, the work planner 104 assigns a heavy burden to the top worker, presents a target distribution of the processing speed of the middle worker, and assigns a light burden or a task that allows the bottom worker to get back on track.

[0120] In step S107, the processor 11 selects an AGV to be used for shelf transport in accordance with the work plan and sends a transport instruction to call up the shelf to the picking station using the AGV 7.

[0121] In step S108, the processor 11 calls the AGV shelf 8 to the picking station and causes the picking means 113 present in the picking station P to execute a picking operation corresponding to the AGV shelf 8 brought by the AGV 7.

[0122] In step S109, processor 11 generates a work log indicating the work content performed during the picking work, and creates shaping work log data by adding the performance values ​​included in the work log. For example, processor 11 creates a work log indicating the work content performed each time picking work (sorting work) of a specified item is completed, and saves (updates) the created work log in database 121. When the work log is updated, processor 11 creates shaping work log data that contains information similar to the shaping work data shown in FIG. 7.

[0123] In step S110, processor 11 determines whether or not there is any unprocessed allocation work remaining at each picking station P. If there is any unprocessed work remaining, the process returns to step S107, and continues to call up the shelf (step S107), the picking work (step S108), and create and generate the work log (step S109). On the other hand, if there is no unprocessed allocation work remaining, the process proceeds to step S111.

[0124] In step S111, the processor 11 determines whether the capacity of the picking means 113 is within an expected range. For example, the processor 11 calculates the difference between the set time for processing of each picking means 113 determined by the work plan unit 104 and the time actually required for the processing. If the difference does not exceed a predetermined threshold, it is determined that there is no need to change the set measure, and the processing ends. In other words, the processor 11 proceeds to the next batch processing.

[0125] On the other hand, if the difference exceeds a predetermined threshold, the processor 11 determines that it is outside the expected range. In this case, the process proceeds to step S112. Note that since the worker who is the picking means 113 is a human, there is variation in the process. Therefore, in this embodiment, the difference between the set time for the batch process and the time actually taken for the process is calculated. However, this embodiment is not limited to this, and it is of course possible to calculate the difference for each process of the batch process or for an arbitrary number of processes and determine whether or not to change the policy setting conditions.

[0126] In step S112, the processor 11 changes the action setting conditions. The processor 11 changes the action setting conditions to be used in step S104 in the next batch process. For example, when it is determined that a specific picking means 113 (worker) is tired and efficiency is declining, a action is set to bring the worker back into good shape.

[0127] (Effects of the embodiment) According to the embodiment described above, the upper management device 1 that determines the warehouse work plan has measures that directly or indirectly affect the processing ability of the workers, and can determine the work plan taking into account the effects of these measures. In addition, the measures for each worker are appropriately changed according to the progress of the work. This makes it possible to improve the average processing ability of each worker, prevent a sudden decrease in ability, and shorten the absolute work time of each worker from a long-term perspective.

[0128] (Modification) The above-mentioned embodiment has been described assuming a case where the picking system 100 performs a retrieval operation, but the above-mentioned embodiment may also be applied to a retrieval operation. For example, a warehouse in which the picking system 100 is operated may be provided with a retrieval operation area in addition to the goods management area and retrieval operation area shown in Fig. 1. As in the retrieval operation described above, a station where an operator waits in the retrieval operation area may be arranged, and the retrieval (goods replenishment) operation may be performed in response to an instruction from the upper management device 1.

[0129] In a warehouse where the picking system 100 is operated, the warehousing operation is assumed to involve setting newly arrived goods on the AGV shelf 8 transported by the AGV 7, assuming that the trays 10 arranged at the picking station P contain newly arrived goods. Note that the newly arrived goods may be packed in cardboard boxes or the like instead of on the trays 10.

[0130] The program according to this embodiment may be transferred in a state where it is stored in an electronic device (computer) serving as the upper management device 1, or in a state where it is not stored in an electronic device. In the latter case, the program may be transferred via a network, or in a state where it is stored in a storage medium. The storage medium is a non-transient tangible medium. The storage medium is a medium that can be read by a computer serving as the upper management device 1 (a computer-readable medium). The storage medium may be any medium capable of storing a program and being readable by a computer, such as an optical disk (e.g., a CD-ROM), a magnetic disk, or a semiconductor memory (e.g., a memory card), and its form is not important.

[0131] Although some 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 implemented 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 in the scope and spirit of the invention, and are included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0132] 100...Picking system 1...Upper management device 11…Processor 101...Work data creation department 102…Data Formatting Department 103... Processing capacity prediction section 104…Work Planning Department 105...Policy setting condition judgment section 12...ROM 13…RAM 14. Auxiliary storage device 121…Database 15...Communication interface 2. Network 3. External systems 7...AGV 71…Processor 72...ROM 73…RAM 74...Auxiliary storage device 75...Communication interface 76...Drive unit 77…Sensor 78…Battery 79…Charging mechanism 70…Tire 8…AGV shelf P: Picking station 10…Tray 112…Work management department 113...Picking method

Claims

1. An information processing method executed by a processor of an information processing device, comprising: Creating picking operation data related to a picking operation in which a picking means picks up an item based on an order list acquired from an external system; performing a shaping process on the picking operation data; predicting a processing capacity of the picking means for the picking operation based on the shaped picking operation data; An information processing method comprising:

2. The picking means is a worker, The shaping process is a process of assigning attributes of the picking means, measures, the workload of the picking means, and the processing capacity of the picking means to each of the picking operations. The information processing method according to claim 1 .

3. The attributes of the picking means include at least one of a worker ID, age, sex, height, exercise experience, years of employment, employment type, working time that has elapsed since starting work at the current time, or fatigue level. The information processing method according to claim 2 .

4. The measures include at least one of information presentation via a work management unit connected to the information processing device, a change in the picking work assigned to the picking means, and a constraint on the workload of the picking means. The information processing method according to claim 2 .

5. The measures regarding the information presentation include at least one of the following: a target time for the work or an estimate of the end of the work, presentation of information to support the picking work to be performed by the worker, presentation of a character, playback of music, presentation of an amount of incentive, and presentation of a ranking of the workers. The information processing method according to claim 4.

6. the picking means is a worker, and the picking operation data is data to which attributes related to the item and the picking operation are assigned; The shaping process includes a variable process for converting attributes related to the item and the picking operation into dummy variables or continuous values. The information processing method according to claim 1 .

7. The shaping process includes a process of adding a measure to the picking operation data, The prediction is performed by dividing the case into the presence or absence of the measure for the picking means, The information processing method according to claim 1 .

8. The predicting step includes predicting the processing capacity of the picking means using a prediction model trained with attribute data related to the work to be performed based on the picking work data as an explanatory variable and with the processing capacity of the picking means as a target variable. The information processing method according to claim 1 .

9. The prediction model is constructed for each picking means. The information processing method according to claim 8.

10. Further comprising storing a work log relating to past picking work, The information processing method according to claim 1 , wherein the prediction includes extracting a performance result value of a picking operation having conditions similar to those of a picking operation to be performed based on the picking operation data from the work log, and using the performance result value as a predicted value.

11. Further comprising setting a policy setting condition based on the work results collected from each of the picking means. The information processing method according to claim 1 .

12. determining whether the work performance of the picking means is within a predetermined range of the predicted processing capacity; When it is determined that the predetermined range is exceeded, the policy setting condition is changed. The information processing method according to claim 11 , further comprising:

13. a task data creation unit that creates picking task data related to a picking task in which a picking means picks up an item based on an order list acquired from an external system; A data shaping unit that performs a shaping process on the picking operation data; a processing capacity prediction unit that predicts a processing capacity of the picking means for the picking operation based on the shaped picking operation data; An information processing device comprising:

14. An information processing program comprising instructions to be executed by a processor of an information processing device, Creating picking operation data related to a picking operation in which a picking means picks up an item based on an order list acquired from an external system; performing a shaping process on the picking operation data; predicting a processing capacity of the picking means for the picking operation based on the shaped picking operation data; An information processing program comprising:

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