CN113496368A

CN113496368A - Configuration method and device of picking workstation

Info

Publication number: CN113496368A
Application number: CN202010203497.2A
Authority: CN
Inventors: 陈勃
Original assignee: Beijing Jingdong Qianshi Technology Co Ltd
Current assignee: Beijing Jingdong Qianshi Technology Co Ltd
Priority date: 2020-03-20
Filing date: 2020-03-20
Publication date: 2021-10-12

Abstract

The invention discloses a configuration method and a configuration device of a picking workstation. The configuration method comprises the steps of determining an order range of today current wave and an order range of yesterday and this wave according to yesterday; counting the number of commodities to be picked and the number of pieces of commodities to be distributed in the current order today, and counting the number of commodities to be picked and the number of pieces of commodities to be distributed in the current order yesterday at the next time yesterday; if the current time average remaining workload is greater than the product of the time average remaining workload at yesterday and the order increase threshold, then the picking workstation resources are increased.

Description

Configuration method and device of picking workstation

Technical Field

The present invention relates generally to warehouse logistics technology, and more particularly, to a method and apparatus for configuring a picking station.

Background

The goods picking operation in the goods delivery process is to pick the goods on an order from a goods shelf, and the goods picking operation is the most important and cost-occupying operation of the warehouse logistics center. Meanwhile, the timeliness of the goods picking operation greatly influences the logistics service quality.

A warehouse logistics center is typically provided with a plurality of picking stations, and Automated Guided vehicles (Automated Guided vehicles) in the warehouse logistics center transport bins, each typically containing a plurality of items, from a storage area to the picking stations, which pick the corresponding items from the bins according to the type and quantity of the items in the order.

If the resource allocation of the picking workstation is too much, the sorting efficiency is reduced overall, and the operation cost is too high, while if the resource allocation of the picking workstation is too little, the picking operation is difficult to complete on time, and the logistics service quality is reduced.

The configuration of the warehouse operation management personnel on the relevant resources of the picking workstation is decided and judged by depending on the brain according to the actual situation and the historical experience of the site; with the increase of single quantity and the increase of the number of the AGVs, the change of field operation conditions is complex, and the conditions of misjudgment and untimely decision judgment sometimes occur in subjective judgment of people, so that the resource allocation of the picking workstation is unreasonable.

The above information disclosed in this background section is only for enhancement of understanding of the background of the invention and therefore it may contain information that does not constitute prior art that is already known to a person of ordinary skill in the art.

Disclosure of Invention

In this summary, concepts in a simplified form are introduced that are further described in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter.

It is a primary object of the present invention to overcome at least one of the above-mentioned drawbacks of the prior art, and to provide a method of configuring a picking station, comprising:

determining the order range of today's current wave and the order range of yesterday's current wave according to the current time;

counting the number of commodities to be picked and the number of pieces of commodities to be distributed in the current order today, and counting the number of commodities to be picked and the number of pieces of commodities to be distributed in the current order yesterday at the next time yesterday;

dividing the sum of the number of commodities to be picked and the number of the commodities to be distributed in the current order by the number of currently opened picking workstations to obtain the average remaining workload of the current order, and dividing the sum of the number of the commodities to be picked and the number of the commodities to be distributed in the current order by the number of opened picking workstations at the time of yesterday to obtain the average remaining workload of the current order at the time of yesterday;

if today's current time average remaining workload is greater than yesterday's product of the time average remaining workload and the order increase threshold, then the picking workstation resource allocation is increased.

According to one embodiment of the invention, increasing picking workstation resource configuration comprises:

if the difference between the current quantity of the commodities to be distributed at the current time today and the current quantity of the commodities to be distributed at the current time yesterday is larger than or equal to the difference between the current quantity of the commodities to be picked at the current time today and the current quantity of the commodities to be picked at the current time yesterday, more picking workstations are started, and otherwise, more caching bits are added.

According to an embodiment of the invention, the value range of the order amplification threshold is 1.1-1.4.

According to an embodiment of the invention, the configuration method further comprises:

acquiring a median picking speed of each picking workstation according to historical working data of each picking workstation;

predicting the picking time length consumed by the opened picking work stations for picking the goods to be picked according to the number of the goods to be picked on the current warehouse, the middle picking speed and the number of the opened picking work stations;

if the number of items to be picked at the present day is greater than the product of the number of items to be picked at the present day in the current warehouse and the present day ratio threshold, and the sum of the present time and the picking duration exceeds the scheduled completion time at the present day, increasing the picking workstation resource allocation.

when the picking duration is longer than the overstock configuration time parameter, judging whether the difference between the total number of commodities to be sorted on the day and the number of commodities to be sorted on the previous day is larger than or equal to the difference between the number of commodities to be sorted on the day and the number of commodities to be sorted on the previous day, if so, starting more picking workstations, and otherwise, increasing more cache positions.

when the slot utilization rate of the picking work station is smaller than a slot capacity margin threshold value and the picking time is smaller than a margin configuration time parameter, calculating the number of the picking work stations needing to be closed according to the following formula:

wherein a is the number of picking workstations needing to be closed, b is the number of the opened picking workstations, c is the number of commodities to be picked on the day, d is the median picking speed, and e is the expected picking completion time;

if the number of picking stations that need to be shut down is greater than zero, the a picking stations are shut down.

According to one embodiment of the invention, obtaining a median picking speed for each picking station from historical work data for the picking station comprises:

arranging the number of picking items of each picking workstation in each preset time length in the last preset days from small to large;

and selecting the number of picking items in the middle position, wherein the middle picking speed is equal to the number of picking items divided by the preset time length.

According to one embodiment of the invention, determining the order range of the current time of day and the order range of the time of yesterday according to the current time comprises:

determining the order range of the current order today:

judging whether the wave frequency planning completion time is earlier than the current time and the wave frequency of incomplete sorting work exists, if so, adding the order of the wave frequency into the order range of the current wave frequency;

judging whether the order has the order of the order plan completion time within the preset time length from the current moment, and if so, adding the order of the order into the order range of the current order;

if the order does not have the wave number of the wave number plan completion time within the preset time length from the current time, judging whether the order has the wave number of the wave number plan completion time after the preset time length from the current time and before twice the preset time length from the current time, and if so, adding the order of the wave number plan completion time most ahead in the wave number into the order range of the current wave number.

A step of determining an order range of yesterday at this moment:

judging whether the current time with the wave-number planning completion time earlier than the previous day and the wave-number with incomplete sorting work exist or not, and if so, adding the order of the wave-number into the order range of the wave-number at the current time yesterday;

judging whether the wave number within a preset time length from the moment of the previous day to the later moment of the wave number plan completion time exists or not, and if so, adding the order of the wave number into the order range of the wave number at the moment of yesterday;

if the wave times within the preset time length from the moment to the back of the previous day of the wave time plan completion time are not available, whether the wave times after the preset time length from the moment to the back of the previous day of the wave time plan completion time and before twice the preset time length from the moment to the back of the previous day are available is judged, and if the wave times before the preset time length from the moment to the back of the previous day of the wave time plan completion time are available, an order of the wave times with the most front wave times in the wave times is added into an order range of the wave times at the last day.

In accordance with one embodiment of the present invention,

the step of determining the order scope for the present day current order further comprises:

if the wave times of the wave times plan completion time after the preset time length from the current time backward and before twice the preset time length from the current time backward are not available, adding the order of the last wave time in the current wave time in the order range of the current wave time;

the step of determining the order range for yesterday at this moment further comprises:

and if the wave times are not provided, the wave time planning completion time is after the preset time length from the moment of the previous day to the later time and is twice as long as the wave times before the preset time length from the moment of the previous day to the later time, adding the order of the last wave time of the previous day into the order range of the wave time of the previous day.

The invention also proposes a configuration device of a picking station, comprising:

the range determining module is used for determining the order range of today's current time and the order range of yesterday's current time in the same period of yesterday according to the current time;

the statistical module is used for counting the number of goods to be picked and the number of pieces of goods to be distributed in the current order today, and counting the number of goods to be picked and the number of pieces of goods to be distributed in the current order yesterday at this moment;

the calculation module is used for dividing the sum of the quantity of commodities to be picked and the quantity of commodities to be distributed in the current order by the quantity of currently opened picking workstations to obtain the average remaining workload of the current order, and dividing the sum of the quantity of commodities to be picked and the quantity of the commodities to be distributed in the current order by the quantity of opened picking workstations at the time of yesterday to obtain the average remaining workload of the current order at the time of yesterday;

and the configuration module is used for increasing the resources of the picking workstation if the current wave-time average remaining workload is larger than the product of the current wave-time average remaining workload and the order amplification threshold value yesterday.

The invention also proposes a computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the configuration method as described above.

The invention also proposes an electronic device comprising:

a processor; and

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform the configuration method as described above via execution of the executable instructions.

According to the technical scheme, the configuration method of the picking workstation has the advantages and positive effects that:

today, the probability that the current-time average remaining workload is higher than the product of the current-time average remaining workload and the order amplification threshold value at the moment of yesterday is higher, so that the resource configuration of the picking workstation needs to be increased to deal with the increased picking workload, and therefore the picking workstation is increased to avoid that the picking work of the current-time cannot be completed on time.

Drawings

Various objects, features and advantages of the present invention will become more apparent from the following detailed description of preferred embodiments of the invention, when considered in conjunction with the accompanying drawings. The drawings are merely exemplary of the invention and are not necessarily drawn to scale. In the drawings, like reference characters designate the same or similar parts throughout the different views. Wherein:

FIG. 1 is a flow chart illustrating a method of configuration of a picking workstation in accordance with an exemplary embodiment;

FIG. 2 is a schematic diagram of a configuration apparatus of a picking station shown in accordance with an exemplary embodiment;

FIG. 3 is a schematic diagram of an electronic device shown in accordance with an exemplary embodiment;

FIG. 4 is a schematic diagram illustrating a computer-readable storage medium according to an example embodiment.

Detailed Description

Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus their detailed description will be omitted.

Referring to fig. 1, fig. 1 shows a flow chart of a method of configuring a picking station in the present embodiment. The configuration method includes steps S1-S4.

S1: determining the order range of today's current wave and the order range of yesterday's current wave according to the current time;

after receiving the order, the automated warehouse needs to pack and export the commodities recorded on the order. The order may be a merchandise order sent from an e-commerce system. The main flow of commodity packing and delivery comprises sorting and packing. Sorting is to sort the commodities in the order from a plurality of commodities, and packing is to pack the sorted commodities by taking the order as a unit.

An automated warehouse typically includes a plurality of automated guided vehicles, a plurality of picking workstations, a plurality of stereoscopic racks, a plurality of bins, and a control unit. The bin is used for loading commodities. Each bin can be loaded with one or more items. The bins are typically stored on a shelf. The type and quantity of goods in each bin is stored in the control unit, as is the location of each bin.

The three-dimensional goods shelf is arranged in a storage area of the warehouse, and the picking work station is arranged outside the storage area. The control unit can control the automatic guide transport vehicle to transport the material box between the three-dimensional goods shelf and the picking workstation.

When a commodity needs to be taken out of the warehouse, the control unit controls the automatic guiding transport vehicle to transport a bin containing the commodity to the picking work station, a worker of the picking work station picks the commodity from the bin, and then the automatic guiding transport vehicle transports the bin back to the three-dimensional shelf after the worker of the picking work station confirms that the picking of the commodity is finished.

In order to improve the sorting efficiency, the automatic warehouse generally adopts a seeding type sorting method to sort. The seed sorting method is a method of sorting a plurality of orders into a plurality of batches, and collectively processing the orders of one batch at a time, and the batch of the operation is generally referred to as "wave times". In the E-market scenario, the warehouse has multiple waves due to transport pull production. When a picking work plan is made, all the times required to be completed in the current day are generally arranged in advance, each time has a time for completing the time of completing the time of completing the time of the order.

The time to schedule completion is typically not the same for each wave in the picking job schedule. Taking an automated warehouse as an example, the completion time of each picking work plan in one day according to the wave-time plan can be arranged as follows:

TABLE 1 schedule for planning completion of certain daily times in certain warehouse

00:00
	11:05
12:00
	14:00
14:30
	16:00
19:00
	21:00
23:59

The present wave number of the present day represents the highly-aged order task that the automated warehouse must currently complete, determining which wave numbers belong to the present wave number of the present day, the present wave number of the present day includes at least 1 wave number of the order, and may be an order number including a plurality of wave numbers. The order in the current wave today is the most urgent order at the present time.

The step of determining the order scope for the present day current wave comprises:

s111: judging whether the wave times of which the wave times plan completion time is earlier than the current time and the sorting work is not completed exist, if so, entering the step S112, and if not, entering the step S113;

s112: adding the order with the wave times which is scheduled to be finished earlier than the current time and has not finished sorting work into the order range of the current wave times today, and entering the step S113;

the order of the wave time plan which is earlier than the current time and the wave time of the incomplete sorting work is the order which exceeds the specified time limit of the sorting work plan and needs to be processed as soon as possible.

S113: judging whether the wave number of the wave number plan completion time within the preset time length from the current time exists or not, if yes, entering step S114, and if not, entering step S115;

s114: adding the order of the wave times with the wave time plan completion time within the preset time length from the current time to the order range of the current wave times;

the preset time period may be 50 to 70 minutes. The times of the wave completion time within the preset time duration in the future are the times of the wave scheduled completion time which is immediately expired, and therefore, the orders in the times are also orders which need to be processed as soon as possible. Taking the preset time length as 60 minutes as an example, the order of the wave times of which the wave time plan completion time falls into the interval belongs to the current wave order of today by pushing back for 60 minutes from the moment.

S115: judging whether the wave times after the wave times plan completion time is a preset time after the current time and before twice the preset time after the current time exist or not, if so, entering a step S116, otherwise, entering a step S117;

s116: adding the order of the wave times with the highest wave times of the wave times of which the planned completion time is behind the preset time length from the current time and before twice the preset time length from the current time into the order range of the current wave times.

Taking the preset time length as 60 minutes as an example, if no wave-order plan completion time exists within 60 minutes after the preset time length is started, then the wave-order of the wave-order plan completion time is searched from the 60 minutes to 120 minutes later, and if the wave-order of the wave-order plan completion time within the interval is available, the order of the wave-order plan completion time most ahead in the wave-orders is added into the current wave-order of the current wave-order.

S117: when no order exists in the current time of the day, the order of the last time of the day is added into the order range of the current time of the day.

If there are no orders in the current wave today, it is likely that the automated warehouse is busy during times such as, for example, a large promotion period for an e-commerce, where there is only one wave in the day whose scheduled completion time is the last second of the day. Therefore, the last wave of the current day can be taken as the current wave of today.

In order to make the order range of yesterday at this time comparable to the order range of today's current time, the method of determining the order range of yesterday at this time is similar to the method of determining today's current time, the step of determining the order range of yesterday at this time:

s121: judging whether the wave times with the wave times planning completion time earlier than the current day and incomplete sorting work exist, if yes, entering step S122, and if not, entering step S123;

s122: adding the order of the wave times with the wave time planning completion time earlier than the previous day and the wave times with incomplete sorting work into the order range of the wave times at the moment of yesterday, and entering the step S123;

s123: judging whether the wave number planning completion time is within a preset time length from the moment of the previous day to the back, if yes, entering step S124, and if not, entering step S125;

s124: adding the wave order with the wave planning completion time within the preset time length from the moment of the previous day to the wave order range of the current time of yesterday;

s125: judging whether the wave times of which the wave time planning completion time is after the preset time length from the moment of the previous day backward and before twice the preset time length from the moment of the previous day backward exist, if so, entering step S126, otherwise, entering step S127;

s126: adding the order of the wave in the wave before the wave planning completion time is two times of the preset time length from the moment of the previous day to the moment of the previous day, wherein the wave planning completion time is the most front wave, into the order range of the wave at the moment of yesterday.

S127: when no order is available in yesterday at this time, the last wave of the previous day is added to the range of orders at this time yesterday.

S2: counting the number of commodities to be picked and the number of pieces of commodities to be distributed in the current order today, and counting the number of commodities to be picked and the number of pieces of commodities to be distributed in the current order yesterday at the next time yesterday;

in the orders currently in the current pass today, there may be orders that have completed sorting, orders that are in order to be sorted, and orders that are in order to be dispensed. An order that is in a pending assignment state refers to an order that indicates that the warehouse system has not assigned order picking tasks to the picking workstations. And counting the number of the commodities to be picked in all the orders in the to-be-picked state in the current process of the current day, and counting the number of the commodities to be distributed in all the orders in the to-be-distributed state.

In the order in this time of yesterday, at this time of yesterday there may also be orders that have already finished sorting, orders that are in a state to be picked and orders that are in a state to be distributed. An order that is in a pending assignment state refers to an order that indicates that the warehouse system has not assigned order picking tasks to the picking workstations. And counting the number of commodities to be picked in all orders in the to-be-picked state in the next time of yesterday, and counting the number of commodities to be distributed in all orders in the to-be-distributed state.

S3: dividing the sum of the number of commodities to be picked and the number of the commodities to be distributed in the current order by the number of currently opened picking workstations to obtain the average remaining workload of the current order, and dividing the sum of the number of the commodities to be picked and the number of the commodities to be distributed in the current order by the number of opened picking workstations at the time of yesterday to obtain the average remaining workload of the current order at the time of yesterday;

a currently opened picking station refers to a picking station that is running at the current time. Yesterday when the picking workstation has been switched on means the picking workstation that was running at this time yesterday.

The current time average remaining workload today is the number of items that each picking station running that completed the current time of picking assignments on average still needs to pick. The average remaining work load of this time of yesterday is the number of items that need to be picked on average per picking workstation that completed the picking task of this time of yesterday that was running at this time of yesterday.

S4: if the current time average remaining workload is greater than the product of the time average remaining workload at yesterday and the order increase threshold, then the picking workstation resources are increased. Step S4 includes step S41 and step S42.

Step S41: and judging whether the current average residual workload of the wave time is larger than the product of the current average residual workload of the wave time and the order amplification threshold value yesterday or not, if so, entering the step S42, and if not, entering the step S51.

The order amplification threshold is a constant greater than 1. The value range of the order amplification threshold is 1.1-1.4, and preferably 1.2. The order amplification threshold value can be set according to the amplification of orders of two adjacent days in the history of the automatic warehouse, when the order amplification of the next day is larger than a certain value, the order is not sorted on time, and then the value is used as the order amplification threshold value.

In a planning stage, the problems of capacity, AGV and the quantity and proportion of picking workstations are considered in an AGV (automatic Guided Vehicle) goods-to-person picking storehouse, and generally, under the conditions of a promotion period and small fluctuation of orders, the difficulty in completing production tasks can be caused because a warehouse cannot change resource allocation in time. When an e-commerce storeroom is built and then is produced, the warehouse commodity stock, the order structure, the AGV quantity, the AGV operation environment, the picking work station and the shelf layout are relatively stable environments, so that the condition of the increase range of the order production task can accurately reflect whether the consequence that the order is not picked on time can occur or not in the stable environments compared with the condition that the e-commerce storeroom is operated in the same environment.

Step S42: pick workstation resources are increased.

Today, the current time average remaining workload is larger than the product of the time average remaining workload at yesterday and the order amplification threshold value, which indicates that the current time order is not completed on time, so that the picking workstation resources need to be increased to deal with the increased picking workload, and therefore, in the embodiment, the picking workstation resources are increased to avoid that the picking work at the current time cannot be completed on time.

Further, step S42 includes steps S421 to S423:

s421: judging whether the difference between the current quantity of the commodities to be distributed at the current time today and the current quantity of the commodities to be distributed at the current time yesterday is larger than or equal to the difference between the current quantity of the commodities to be picked at the current time today and the current quantity of the commodities to be picked at the current time yesterday, if so, entering a step S422, and if not, entering a step S423;

s422: starting more picking workstations;

when the difference between the current quantity of the commodities to be distributed at the current time today and the current quantity of the commodities to be distributed at the time yesterday is larger than or equal to the difference between the current quantity of the commodities to be picked at the current time today and the current quantity of the commodities to be picked at the time yesterday, the fact that the current quantity of the commodities to be distributed is more is shown, and therefore more picking workstations need to be started.

S423: more cache bits are added.

The buffer slots are physical locations near the picking workstation where the AGV may stay waiting for the picking slots to idle and then move to the picking slots when the picking workstation is not idle.

When the difference between the current quantity of the commodities to be distributed at the current time today and the current quantity of the commodities to be distributed at the current time yesterday is smaller than the difference between the current quantity of the commodities to be picked at the current time today and the current quantity of the commodities to be picked at the current time yesterday, the situation shows that the quantity to be picked in the whole warehouse is more, and therefore more cache bits are opened.

Further, the configuration method further includes steps S51 ~ 53 after the step S4:

s51: acquiring a median picking speed of each picking workstation according to historical working data of each picking workstation; s51 includes S511 to S512.

S511: arranging the number of picking items of each picking workstation in each preset time length in the last preset days from small to large, and entering step S512;

for example, the preset number of days may be seven days, and the preset length of time may be 10 minutes. The number of picks per tenth for each picking station during the last seven days is recorded and ranked in order of small to large.

S512: the picking speed is equal to the number of picking items divided by the preset time length, and the step S52 is proceeded.

The picking quantity at the middle position is selected from the picking quantities arranged from small to large, and the picking speed at the middle position is obtained by dividing the picking quantity by the preset time length. The median picking speed is the number of picks that can be completed per picking station per unit time.

S52: predicting the picking time length consumed by the opened picking work stations for picking the goods to be picked according to the number of the goods to be picked in the current warehouse, the middle picking speed and the number of the opened picking work stations, and entering the step S53;

the picking time length consumed for picking the goods to be picked up by the picking work station which is opened at present can be obtained by dividing the number of the goods to be picked up in the current warehouse by the number of the opened picking work stations and then dividing by the middle picking speed.

S53: if the present number of items to be picked is greater than the present number of items to be picked multiplied by the present current count ratio threshold and the sum of the present time and the picking duration exceeds the present current count completion time, then the process proceeds to step S42. Step S53 includes S531 and step S532.

Step S531: judging whether the number of the goods to be picked at the current time is larger than the product of the number of the goods to be picked at the current time and the current time ratio threshold value at the current time, if so, entering the step S532, otherwise, entering the step S61;

the value range of the current wave-time ratio threshold value is 0.6-0.8, and preferably 0.7. If the current number of the goods to be picked is larger than the product of the remaining number of the goods to be picked in the current day and the current ratio threshold value of the current day, the current number of the goods to be picked is over-high, and the current day may not complete the picking work in due time.

Step S532: and judging whether the sum of the present moment and the picking time length exceeds the completion time of the present moment, if so, entering the step S42, and otherwise, entering the step S61.

The completion time of the present wave of today is the latest wave plan completion time of the plurality of wave plan completion times included in the present wave of today. Adding the time of the present time of day to the picking duration that is required for the present time of day to anticipate completion of the picking operation results in the present time of day to anticipate completion, and if the time is greater than the projected completion time of the present time of day, indicating that the present time of day picking operation must not be completed on time, thus increasing picking station resources.

Further, the configuration method further comprises the following steps: steps S61 to S64.

S61: judging whether the picking time length is greater than the backlog configuration time parameter, if so, entering a step S62, otherwise, entering a step S71;

the backlog configuration time parameter is a preset time duration, which may be 40-60 minutes, preferably 50 minutes. The backlog configuration time parameter may be configured according to the actual conditions of the various warehouses. When the picking time of the current time exceeds the backlog configuration time parameter, the risk of backlog of sorting work is existed, and the production pressure is large.

S62: judging whether the difference between the total number of commodities to be distributed on the day and the number of commodities to be distributed on the previous day is larger than or equal to the difference between the number of commodities to be picked on the day and the number of commodities to be picked on the previous day, if so, entering step S63, otherwise, entering step S64;

s63: starting more picking workstations;

the difference between the total number of commodities to be distributed on the day and the number of commodities to be distributed on the previous day is larger than or equal to the number of commodities to be picked on the day and the number of commodities to be picked on the previous day, so that the warehouse has more to-be-distributed amount, and more picking workstations are started.

S64: more cache bits are added.

If the difference between the total number of commodities to be distributed on the day and the number of commodities to be distributed on the previous day is smaller than the difference between the number of commodities to be picked on the day and the number of commodities to be picked on the previous day, the warehouse is indicated to have more picking capacity, and therefore more cache positions are added.

Further, the configuration method further comprises the following steps: step S71 ~ 75.

S71: judging whether the slot utilization rate of the picking workstation is smaller than a slot capacity allowance threshold, if so, entering a step S71, otherwise, entering a step S81;

the slot capacity abundance threshold is an experimental value, and the value range of the slot capacity abundance threshold can be 0.4-0.6, and is preferably 0.5;

the slot utilization rate of the picking workstation is equal to the number of occupied slots of the picking workstation divided by the number of opened slots of the picking workstation.

S72: judging whether the picking time length is less than the affluent configuration time parameter, if so, entering the step S73, otherwise, entering the step S81;

the rich allocation time parameter is a preset time length which is smaller than the backlog allocation time parameter. The slack allocation time parameter is an empirical value, and may be, for example, 1 to 10 minutes.

The utilization rate of the slot positions of the picking work stations is smaller than a slot position capacity abundance threshold, and whether the picking time is smaller than an abundance configuration time parameter indicates that the picking work stations have capacity abundance risks, so that the operation cost needs to be reduced by reducing the number of the picking work stations.

S73: calculating the number of picking stations to be shut down according to the following equation:

the process proceeds to step S74.

S74: and judging whether the number a of the picking work stations needing to be closed is larger than zero, if so, entering the step S75, otherwise, entering the step S9.

S75: the a picking stations are shut down.

Under the condition of abundant productivity, the operation cost can be reduced by closing a picking workstations too many.

Further, the configuration method further comprises the following steps: steps S81, S82, and S9.

S81: whether the utilization rate of the cache bit of the picking workstation is smaller than the capacity allowance threshold of the cache bit or not is judged, if yes, the step S82 is carried out, and if not, the step S9 is carried out;

the picking station cache bit utilization is equal to the number of occupied cache bits for the picking station divided by the number of open cache bits for the picking station.

The buffer capacity abundance threshold is an experimental value, and the value range of the buffer capacity abundance threshold can be 0.4-0.6, and is preferably 0.5;

s82: judging whether the picking time length is less than the affluent configuration time parameter, if so, entering the step S73, otherwise, entering the step S9;

when the utilization rate of the buffer position of the picking workstation is smaller than the capacity margin threshold of the buffer position and the picking time is smaller than the margin configuration time parameter, the risk of capacity margin of the picking workstation is indicated, and the operation cost needs to be reduced by reducing the number of the picking workstations.

S9: and (6) ending.

When the existing picking workstation does not have the risk of high production pressure, overtime production or abundant productivity, the resource allocation of the picking workstation is normal and reasonable without adjustment.

With reference to fig. 2, the present embodiment also proposes a configuration device 1 of a picking station, the configuration device 1 comprising:

the range determining module 11 is used for determining the order range of today's current time and the order range of yesterday's current time in the same period of yesterday according to the current time;

the statistic module 12 is used for counting the number of goods to be picked and the number of pieces of goods to be distributed in the current order today, and counting the number of goods to be picked and the number of pieces of goods to be distributed in the current order yesterday at this moment yesterday;

the calculation module 13 is used for dividing the sum of the number of commodities to be picked and the number of commodities to be distributed in the current order by the number of currently opened picking workstations to obtain the average remaining workload of the current order, and dividing the sum of the number of commodities to be picked and the number of commodities to be distributed in the current order by the number of opened picking workstations at the time of yesterday to obtain the average remaining workload of the current order at the time of yesterday;

a module 14 is configured for increasing picking workstation resources if the current time-of-day average remaining workload is greater than yesterday times the product of the current time-of-day average remaining workload and the order increase threshold.

An electronic device 800 according to this embodiment of the invention is described below with reference to fig. 3. The electronic device 800 shown in fig. 3 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present invention.

As shown in fig. 3, electronic device 800 is in the form of a general purpose computing device. The components of the electronic device 800 may include, but are not limited to: the at least one processing unit 810, the at least one memory unit 820, and a bus 830 that couples the various system components including the memory unit 820 and the processing unit 810.

Wherein the storage unit stores program code that is executable by the processing unit 810 to cause the processing unit 810 to perform steps according to various exemplary embodiments of the present invention as described in the above section "exemplary methods" of the present specification.

The storage unit 820 may include readable media in the form of volatile memory units such as a random access memory unit (RAM)8201 and/or a cache memory unit 8202, and may further include a read only memory unit (ROM) 8203.

The storage unit 820 may also include a program/utility 8204 having a set (at least one) of program modules 8205, such program modules 8205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.

Bus 830 may be any of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

The electronic device 800 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable an insurance customer to interact with the electronic device 800, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 800 to communicate with one or more other computing devices. Such communication may occur via input/output (I/O) interfaces 850. Also, the electronic device 800 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the internet) via the network adapter 860. As shown, the network adapter 860 communicates with the other modules of the electronic device 800 via the bus 830. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the configuration method according to the embodiments of the present disclosure.

In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing one of the configuration methods described above in the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above section "exemplary methods" of the present description, when said program product is run on the terminal device.

Referring to fig. 4, a program product 900 for implementing the above configuration method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program codes, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.

The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the insurance client computing device, partly on the insurance client device, as a stand-alone software package, partly on the insurance client computing device and partly on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the insurance client computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).

It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.

Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.

Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the configuration method according to the embodiments of the present disclosure.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

Although the present invention has been disclosed with reference to certain embodiments, numerous variations and modifications may be made to the described embodiments without departing from the scope and ambit of the present invention. It is to be understood, therefore, that this invention is not limited to the particular embodiments disclosed, but it is intended to cover modifications within the scope of the appended claims and their equivalents.

Claims

1. A method of configuring a picking station, comprising:

counting the number of commodities to be picked and the number of pieces of commodities to be distributed in the current order at the present day, and counting the number of the commodities to be picked and the number of pieces of commodities to be distributed in the current order at the present day;

if the current time average remaining workload is greater than the product of the time average remaining workload at yesterday and the order increase threshold, then the picking workstation resources are increased.

2. The configuration method of claim 1, wherein increasing picking workstation resources comprises:

3. The configuration method according to claim 1, wherein the value of the order amplification threshold ranges from 1.1 to 1.4.

4. A configuration method according to any of claims 1 to 3, characterized in that the configuration method further comprises:

5. The configuration method according to claim 4, further comprising:

6. The configuration method according to claim 4, further comprising:

7. The configuration method of claim 4, wherein obtaining a median picking speed for each picking station based on historical work data for the picking station comprises:

8. A configuration method according to any of claims 1 to 3, characterized in that determining from the current time the order range for today's current wave and for yesterday this wave comprises:

determining the order range of the current order today:

A step of determining an order range of yesterday at this moment:

9. The configuration method according to claim 8,

10. An arrangement of picking stations, comprising:

and the configuration module is used for increasing the resource configuration of the picking workstation when the current wave-time average remaining workload is larger than the product of the current wave-time average remaining workload and the order amplification threshold value at yesterday.

11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the configuration method of any one of claims 1 to 9.

12. An electronic device, comprising:

a processor; and

a memory for storing executable instructions of the processor;

wherein the processor is configured to perform the configuration method of any of claims 1-9 via execution of the executable instructions.