JPH07223711A - Automatic picking method and system - Google Patents

Abstract

PURPOSE:To effectively operate a picking system according to system constitution and orders. CONSTITUTION:The constitution of a system and the performance of each component are input in a computer (step 201). A kind allocation plan for each rack is prepared (step 203). Order processing order is decided (step 204). Total processing time and filling up generation time/number of filling time when picking work is conducted according to the kind allocation plan for each set at the step 203 in the order processing order decided at the step 204 are calculated (step 205). From the determined order processing order, kind layout plan by step rack and filling generation time/number of filling time, a work plan for pickers, conveyers and operators is prepared (step 206). Based on the work plan, work instruction is issued to each equipment (step 207).

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an automatic picking system, and in particular, it creates rack-based product type allocation, order processing order and picking work plan that minimize order processing time in accordance with system configuration and order contents. The present invention relates to an automatic picking method and system for operating an efficient picking system.

[0002]

2. Description of the Related Art Order picking is to take out ordered products from a storage location, collect them, and sort them by shipping destination. In recent years, computer-controlled automatic picking systems have been put into practical use for the purpose of labor saving and speeding up of order picking with the progress of mechanical technology. Regarding the automatic picking system, “Order Picking System Handbook” edited by the Cargo Handling Research Institute
The trend is described in (pages 4 to 7), and in particular, an automatic picking system for case picking for picking items one by one includes an input conveyor which is a storage device, a rack which is a storage device, a picking and It consists of a picking device, a bucket, a shipping conveyor, and a computer that controls these equipments. Based on these configurations, the picker picks the items assigned to the rack according to the order data, stores the items in the buckets that are loaded from the receiving conveyor, and collects the buckets for each order after the picking process for shipping. It was carried out on the conveyor.

In particular, in one line where pickers are arranged in series, picking requests from different orders are assigned to each picker and processed at the same time. In addition, even after a picking process is completed among a plurality of lines, an order is placed. In order to put together, processing was performed while synchronizing each device. Therefore, the picker that requires the maximum processing time is rate-controlling the entire synchronized system.

[0004]

In the actual operation, not only the average order processing but also the order processing in which the number of orders and the type are considerably biased is processed. Therefore, in the above-mentioned conventional technology, if the racks are randomly assigned to different types and the picking processing is performed in the order of arrival, waiting time for each device occurs due to the extreme difference in the processing time of each rack, and the estimation can be made at the design stage. Due to the performance of the automatic picking system, it was not possible to perform optimal operations according to daily operations, and it was not possible to achieve sufficient effects by automation. Also,
If you have an order group that needs to be processed suddenly,
The automatic picking system was unable to determine if it could be processed in time, and there were some situations where processing was done manually.

The present invention has been made based on the recognition of such problems.

It is an object of the present invention to allocate a product type for each rack that balances the processing load among the devices and reduces the order processing time according to the order contents, obtain the order processing order, and create a picking work plan. Accordingly, it is an object of the present invention to provide a picking method and system for an automatic warehouse that achieves optimum picking operation.

Other objects of the present invention can be easily inferred by those skilled in the art from the present specification and the accompanying drawings.

[0008]

[Means for Solving the Problems] The above object is to provide a rack consisting of shelves to which articles are allocated, at least one picker for extracting a plurality of types of articles from the rack according to order data, and the articles extracted by the picker. In the automatic picking method using a bucket that stores the data, a conveyor that conveys the bucket to a position that stores the extracted product, and a calculator, and input order data, and picking based on the input order data. This is achieved by creating an operation plan and performing picking work according to the operation plan.

Further, in creating an operation plan, parameters of the system configuration are input, order data is read,
According to the order data, create a rack-specific product allocation correspondence, determine the order processing order of the picker, calculate the time required to process all orders when picking in the rack-specific product allocation and the order processing order, This is achieved by creating a work plan based on the rack-specific product allocation and the order processing order, and instructing the work to the worker, the rack, the picker, and the conveyor.

[0010]

According to the present invention, by simulating in advance according to the daily order data, it is possible to assign the rack type according to the order data and determine the order processing order, so that efficient automatic picking in a short processing time is possible. The system can be operated.

Further, since the replenishment time and the picking time can be calculated in advance by the simulation, it is possible to easily create a work plan for operating the system efficiently.

[0012]

Embodiments of the present invention will now be described in detail with reference to the drawings.

FIGS. 1 and 2 are process flowcharts of an automatic picking method showing an embodiment of the present invention. Figure 1
This is a main processing routine, and FIG. 2 is a processing routine for creating an operation plan. In addition, FIGS. 4, 5, and 6 are subroutines for performing processing for creating an operation plan.

FIG. 3 is a block diagram of an automatic order picking system for realizing this embodiment. The system configuration is rack 301, picker 302, bucket 30.
3, payout conveyor 304, delivery conveyor 305
And the computer 306 and the storage device 30 connected to the computer 306
7, an input device 308, and an output device 309.

The picker 302 is for extracting a plurality of kinds of items from the rack 301 into the bucket 303 according to the order contents, and is installed corresponding to each rack.
One line in which the pickers are arranged in series is called a line. Therefore, in FIG. 3, the number of lines is two.

The payout conveyor 304 is a bucket 30.
3 is for transporting to the position where the extracted item is stored and paying it out. The delivery conveyor 305 is for collecting and shipping buckets for each order.

Next, the input / output information to / from the computer 306 will be explained. Reference numeral 310 is information on the rack 301 (product type and quantity by shelf), 311 is work instruction and status grasp to the picker 302, and 312 is work to the conveyor 304. Instruction and situation grasp,
Reference numeral 313 is simulation result information, work instructions, and work progress status grasping information for the worker via the output device.

The processing operation of this embodiment will be described with reference to FIG. 3 and according to the processing flowcharts of FIGS.

<Step 101> Input order data to the computer 306 using the input device 308. The input order data is stored in the storage device 307 in the file format shown in FIG. The order data 701 includes an order code field 702, an order name field 703, and a product-specific order quantity field 704. Order quantity field 704 by product type
Is a field for storing the number of orders for each type for each order, and is a field for the number of types.

<Step 102> Step 102 is a step for creating a picking operation plan, and proceeds to step 201 of the subroutine FIG.

<Step 201> Using the input device 308, the system configuration (the number of pickers, the number of racks, the number of lines) and the performance of each part (the time for taking out the goods, the time for accessing each shelf of the picker, the time for moving the conveyor) are used. Computer 306
To enter. In order to improve the operability, it is desirable to set a standard value in advance in this step when the system configuration and component performance are constant and not process it in normal operation. However, configuration changes due to system introduction or some failures,
This process needs to be performed when the setting is newly changed when the performance is improved by replacing the parts.

<Step 202> The order data 701 stored in the storage device 307 is read.

<Step 203> FIG. 8 shows an example of a rack. The rack 801 is composed of at least one row and at least one column of shelves 802, and an article 803 of one kind is arranged on each shelf. Picker 302
A line 804 represents the movement when the person picks.
As can be seen from this figure, generally, the farther the shelf is from the home position of the picker 302, the longer the picker access time. Therefore, the higher the frequency of picking request, the closer to the home position the access time may be.

At the step 203, since the type allocation plan for each rack is prepared, the step 401 of the subroutine FIG.
Go to.

<Step 401> From the read order data 701, the number of orders and the number of occurrences of orders are totaled for each product type,
This is stored in the product-type order frequency table 901 shown in FIG.
The product type order frequency table 901 is displayed in the product type field 90.
2. An order quantity field 903.

<Step 402> The total processing time for each product type is calculated from the picker performance item take-out time, the picker access time to each shelf, and the number of orders corresponding to each product type in the product type order frequency table 901. This is stored in the processing time table 1001 for each product type shown in FIG. The product type processing time table 1001 includes a product type field 1002 and a processing time field 1003. For example, the processing time for a product with picker performance is 0.4 * 15 + 1, the picker shelf access time is 0.4 seconds, the picker shelf access time is 1 second, the number of orders is 15, and the number of times an order is generated is 3. * 15 = 21.0 seconds.

<Step 403> The type name having the longest processing time is selected from the type-based processing time table 1001.

<Step 404> Select the line and rack that have the smallest total extraction time of the products to which the products have already been allocated, and allocate to the shelf to which the product in the rack has not been allocated and with the smallest picker movement time. . The correspondence of rack type allocation is stored in the rack type allocation correspondence table 1101 of FIG. The table 1101 shows which product type is assigned to each row and each column, and is stored for each line and each rack. Therefore, product type allocation is performed by assigning product type names to the corresponding rows and columns.

A null code (here, blank) is included in the unallocated area. Further, the allocated product types are distinguished by inserting a null code in the processing time field 1003 of the product type processing time table 1001.

<Step 405> The processing time table 1001 for each product type is still checked, and if there is a product type that has not been allocated, steps 403 and 404 are repeated.
If there is no type to be assigned, the process returns to step 204 of the main processing routine.

<Step 204> Step 204 advances to step 501 of the subroutine FIG. 5 in order to determine the order of processing for obtaining the order processing order that minimizes the total order processing time.

<Step 501> For each order, how much processing time is required for each line and rack is calculated from the rack type allocation correspondence set in step 203 and the picker performance, and shown in FIG. This is stored in the order-specific processing time table 1201. The order-by-order processing time table 1201 indicates how long a certain order takes for each line and rack, and is stored for each order.

<Step 502> The order of processing the order data is rearranged, and the total order processing time is calculated for all the processing orders.

<Step 503> The processing times of all the obtained orders are compared to find the order of the minimum processing time, which is set as the order processing order of the order data 701, and the process returns to step 205 of the main processing routine.

However, in the case of the method of steps 502 and 503, the processing time is calculated for the factorial of the number of orders /
Since it is necessary to make a comparison, when the number of orders increases, the calculation cost increases and the processing speed becomes extremely slow. Therefore, here, for an order to be processed simultaneously, an example of a method for determining the order processing order so that the variance of the processing time obtained in step 501 is reduced is shown in the processing flow of FIG.

<Step 601> An order with a high priority of delivery or an order with the minimum initial processing time is set as an order to be processed first.

<Step 602> The variance of the processing time between the final part i of the order whose processing order is determined and the remaining orders is calculated. There is the following formula (Equation 1) as an evaluation function for measuring the variance.

[0038]

[Equation 1]

<Step 603> An order j that minimizes (Equation 1) is set as an order to be processed next to the order i.

<Step 604> Steps 602 and 60
3 is repeated until there are no more orders, and the order processing order is determined. In the case of this evaluation function, there is no guarantee that the variance with subsequent orders will be minimized, but it is effective in that the order processing order that approximately reduces the variance can be obtained and the processing speed is fast. .

<Step 205> The rack type allocation plan set in step 203, the total processing time when the picking work is performed in the order processing order determined in step 204, and the replenishment occurrence time / number are calculated.

<Step 206> Based on the order processing order determined in Step 204, the rack type product allocation plan set in Step 203, and the replenishment occurrence time / number determined in Step 205, a work plan is created for the picker, conveyor, and worker. To do.

<Step 207> Based on the work plan, work instructions 310, 311, 312, 313 are given to each equipment.

<Step 103> Picking work is performed based on the work instruction.

As described above, only by inputting the order data, the optimum rack type product allocation plan and order processing order can be obtained within a short time in the simulator. This balances the processing load of each picker and reduces the play of each device, so when processing the same order group,
You will be able to bring out high abilities as a whole system.

Further, the timing of replenishment and the time required to process the entire order can be calculated, and the work plan based on the calculated time can be created quickly and easily.
Optimal operation can be achieved according to the order contents even when the number of orders is peak or when an urgent order process is performed.

Further, since the picking process can be completed at a fixed time in accordance with the shipping timing, there is an effect that it is not necessary to secure a space for storing the ordered goods for a long time.

Further, since a work plan is prepared in advance and the operation can be performed as planned, it is possible to equalize the daily work volume and to implement the picking process in consideration of the delivery order.

Furthermore, it is possible to work in cooperation with office work and delivery work, and wasteful office work and waiting time for delivery vehicles can be reduced.

If there is a time before delivery, as in the above embodiment, it is possible to collectively enter orders for several days in step 101 to make an efficient operation plan. , Even if you do not have time to deliver,
By placing a terminal in the order receiving department and inputting order data in real time online, it is possible to make an efficient picking operation plan using the present invention.

Regarding the system configuration and the performance of each part, in normal operation, standard values are set, and the system is expanded / changed such as when the structure is changed due to a partial failure of the part or when the performance is improved by replacing the part. When a problem occurs, it is not necessary to replace the simulator, and only by changing the setting in the process of step 201, it is possible to operate according to the system configuration.

13 and 14 show examples of system configurations different from those of the first embodiment. FIG. 12 shows an example of a 1-line configuration. Also in this configuration, the same effect as that of the first embodiment can be obtained by performing the same processing steps as those of the above embodiment.

Further, the structure of one rack n line in FIG. 14 may be used. However, in this case, the difference from the first embodiment is that
In this configuration, only one order is processed at the same time, and since there is no effect of changing the order processing order, step 204 is unnecessary.

Next, an embodiment for realizing the automatic picking system according to the present invention on the apparatus configuration diagram shown in FIG. 13 will be described with reference to FIG. Since the outline of the device configuration is the same as that of FIG. 3, its explanation is omitted. The present embodiment will be described in correspondence with the functions described with reference to FIG.

System configuration (number of pickers, number of racks,
The number of lines) and the performance of each part (item take-out time, picker moving time to each shelf, conveyor moving time) are input to the computer 306 using the input device 308 (step 1).
501). The order data 701 is input to the computer 306 using the input device 308 and stored in the storage device 307 (step 1502), and a rack type product allocation plan is created (step 1503). The order of processing the order is determined (step 1504). The rack-specific product allocation plan set in step 1503, the total processing time when the picking work is performed in the order processing order determined in step 1504, and the replenishment occurrence time / number are calculated (step 15).
05). From the order processing order determined in step 1504, the rack type product allocation plan set in step 1503, and the replenishment occurrence time / number determined in step 1505, a work plan is created for the picker, conveyor, and worker (step 1506). Work instructions for each facility based on the work plan 3
10, 311, 312, 313 (step 15)
07).

As described above, according to this embodiment, like the embodiment described with reference to FIG.
In the simulator, the optimal rack-specific product allocation plan and order processing order are calculated within a short time, the timing of replenishment and the time required to process the entire order are calculated, and a work plan based on that can be created quickly and easily. Therefore, not only the daily order processing, but also at the peak of the number of orders or in the case of urgent order processing, the optimum operation according to the order content can be achieved.

Further, the present embodiment gives a suggestion to the case where each function realized by a computer is realized by a dedicated circuit, and is useful for a circuit engineer to realize a dedicated device.

[0058]

As described above, according to the present invention,
It is possible to operate the automatic picking system efficiently with less processing time, and the processing time, replenishment time, and picking time of each facility can be calculated in advance by simulation, so work to operate the system efficiently The effect is that a plan can be created easily.

[Brief description of drawings]

FIG. 1 is a diagram showing a processing flow showing an embodiment of the present invention.

FIG. 2 is a diagram showing a processing flow for creating a picking operation plan.

FIG. 3 is a diagram showing a configuration of an automatic order picking system using the present invention.

FIG. 4 is a diagram showing a subroutine for performing processing according to the present invention.

FIG. 5 is a diagram showing a subroutine for performing processing according to the present invention.

FIG. 6 is a diagram showing a subroutine for performing processing according to the present invention.

FIG. 7 is a diagram showing an example of order data.

FIG. 8 is a diagram showing details of a rack.

FIG. 9 is a diagram showing an example of a product type order frequency table.

FIG. 10 is a diagram showing an example of a processing time table for each product type.

FIG. 11 is a diagram showing an example of a table that stores the product type names assigned to each line and rack.

FIG. 12 is a diagram showing an example of a table for storing processing time in each line and rack for each order.

FIG. 13 is a diagram showing an example of a system configuration to which the present invention is applicable.

FIG. 14 is a diagram showing another example of a system configuration to which the present invention is applicable.

FIG. 15 is a diagram showing a configuration of an embodiment for implementing the present invention on the system configuration shown in FIG. 14 in correspondence with the function described with reference to FIG.

[Explanation of symbols]

301 ... Rack, 302 ... Picker, 303 ... Bucket, 304 ... Delivery conveyor, 305 ... Delivery conveyor, 306 ... Calculator, 307 ... Storage device, 308 ... Input device, 309 ... Output device.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Nobuyuki Baba Inventor Nobuyuki Baba 603 Jinritsucho, Tsuchiura City, Ibaraki Pref.

Claims (8)

[Claims] 1. A rack comprising shelves to which items are allocated, at least one picker for extracting a plurality of types of items from the rack according to order data, a bucket for storing the items extracted by the picker, and the bucket. In the automatic picking method using a conveyor that conveys and pays out the extracted items to a position for storing the items, input order data, create a picking operation plan based on the input order data, and perform the operation An automatic picking method characterized by performing picking work according to a plan. 2. The operation plan is created by inputting system configuration parameters, reading order data, creating a rack type allocation correspondence according to the order data, determining an order processing order of the picker, Allocating product types for each rack and calculating the time required to process all orders when picking in the order processing order, and creating a work plan based on the product allocation for each rack and the order processing order. 2. The automatic picking method according to claim 1, wherein the work is instructed to the picker and the conveyor. 3. The creation corresponding to the rack type allocation is
The picking processing time for each product type is calculated from the order data, and the picking processing time is arranged in order from the product having the longest picking processing time so that the picking processing time for each rack becomes even. The automatic picking method according to claim 2, wherein: 4. The order of processing the orders is determined by processing the read order data one by one according to the created rack-specific product allocation correspondence. 3. The automatic order picking method according to claim 2, wherein the order processing order that minimizes the total processing time is set by calculating whether the processing time is required. 5. The automatic order picking method according to claim 2, wherein the order processing time is calculated on the basis of the replenishment time and the number of times of the items in the rack. 6. The automatic order picking system according to claim 5, wherein a work plan for a worker is created based on the replenishment time and the number of times calculated by the simulator. 7. A rack comprising shelves to which items are allocated, at least one picker for extracting a plurality of types of items from the rack according to order data, a bucket for storing the items extracted by the picker, and the bucket. To the position for storing the extracted goods, and a payout conveyor, means for inputting order data, means for creating a picking operation plan based on the input order data, and picking work according to the operation plan. An automatic picking system, which comprises: 8. A means for creating a picking operation plan comprises means for inputting system configuration parameters, means for reading order data, means for creating a rack-specific product type allocation correspondence according to the order data, and a means for selecting the picker. Based on the means for determining the order processing order, the means for calculating the time required for processing all orders when the rack-specific product allocation and the order processing order are picked, the rack-specific product allocation and the order processing order 8. The automatic picking system according to claim 7, further comprising means for creating a work plan and means for instructing a worker, the rack, the picker, and the conveyor to work.