CN118863754A - A method for processing logistics warehousing data - Google Patents

Abstract

The present invention relates to the field of logistics technology, and discloses a logistics warehousing data processing method, including: receiving production tasks, extracting production data; obtaining the warehousing data of the plant area; forming judgment data through data comparison strategy according to the production data and the warehousing data of the plant area, so as to judge whether it is necessary to borrow materials to meet the production demand of the plant area; borrowing materials through the borrowing strategy according to the judgment data. The logistics warehousing data processing method can judge whether it is necessary to borrow target materials from other plants after receiving the production tasks to meet the current production demand, and avoid the situation of production interruption caused by insufficient materials. When borrowing target materials from other plants, it can not only meet the requirements of not delaying the production and use of target materials in other plants, but also meet the requirements of the borrowed target materials arriving at the plant area before the estimated start time of production in the plant area, so that the current production tasks of the plant area can be carried out normally.

Description

A method for processing logistics warehousing data

Technical Field

The present invention relates to the field of logistics technology, and in particular to a logistics warehousing data processing method.

Background Art

Logistics originally means "physical distribution" or "goods delivery". It is a part of supply chain activities. With warehousing as the center, logistics promotes the synchronization of production and market. Logistics is the whole process of planning, implementation and management of the transfer of raw materials, semi-finished products, finished products and related information through transportation, storage, distribution and other means to meet customer needs at the lowest cost. Logistics consists of the transportation, service, distribution, warehousing, packaging, handling, circulation and processing of goods, as well as related logistics information.

Existing large-scale product manufacturing companies generally have multiple factories, each of which generally stores raw materials for manufacturing products. As the factory operates, the inventory weight of the raw materials stored will also change. When a factory receives a production task and needs to carry out a production plan, the raw materials stored in the factory may not be enough for this production, so it is necessary to borrow from other factories to ensure normal production;

The existing logistics and warehousing data processing methods are not convenient for determining the time when other factories are expected to use borrowed materials based on historical production records, and are not convenient for determining from which other factories the borrowed materials can arrive before the start of production. As a result, when borrowing target materials from other factories, the production of other factories may be delayed, and the borrowed materials may still be in transit when production in this factory starts, and have not yet been transported to this factory. This cannot completely solve the problem that the production task of this factory cannot be carried out on time.

Summary of the invention

The present invention provides a logistics warehousing data processing method, which has the ability to determine whether it is necessary to borrow target materials from other factories to meet the current production needs after receiving a production task, so as to avoid production interruptions caused by insufficient materials. When borrowing target materials from other factories, it can not only ensure that the production and use of target materials in other factories are not delayed, but also ensure that the borrowed target materials arrive at this factory before the expected start time of production in this factory, so that the current production task of this factory can be carried out normally. This solves the problem mentioned in the above background technology that in the process of enterprise production, when borrowing target materials from other factories, the production of other factories may be delayed, and the problem that the current production task of this factory cannot be carried out on time cannot be completely solved.

The present invention provides the following technical solution: a logistics warehousing data processing method, comprising:

Receive production tasks and extract production data;

Obtaining the warehouse data of the factory area, wherein the warehouse data of the factory area includes inventory weight and estimated replenishment time;

Based on the production data and the storage data of the factory, the decision data is formed through data comparison strategy to determine whether materials need to be seconded to meet the production needs of the factory;

Based on the judgment data, materials are borrowed through the borrowing strategy to meet the production needs of this plant without affecting the use of materials in other plants.

As an optional solution of the logistics warehousing data processing method of the present invention, the data comparison strategy includes:

Receive production tasks;

Extract the product type in the production task and set it as the target type;

Extract the materials needed in the production task and set them as target materials;

Extract the weight of the target material required for the production task and set it as the required weight;

Execute the loss rate determination strategy to obtain the average loss rate;

Calculate the target weight, target weight = required weight + (required weight × average loss rate);

Obtain the inventory weight of the target material in the factory area and set it as the target inventory weight;

If the target inventory weight ≥ the target weight, no judgment is made;

If the target inventory weight is less than the target weight, the estimated replenishment time of the target material in the factory area is obtained and set as the pre-replenishment time;

Extract the estimated start time of production in the production task and set it as the pre-production time;

If the estimated replenishment time is ≤ the estimated production time, no judgment is made;

If the expected replenishment time is greater than the expected production time, the secondment strategy will be implemented.

As an optional solution of the logistics warehousing data processing method of the present invention, the loss rate determination strategy includes:

Get the date of receiving the production task and set it as the date of receiving the task;

Set the collection end date, collection end date = receiving task date - 1;

Set the collection duration;

Calculate the collection start date, collection start date = collection end date - collection duration;

The time period between the collection start date and the collection end date is defined as the collection period;

Obtain all historical production records of the factory area within the collection period, which is defined as the collection of historical production records;

Extract the collected historical production records whose product type is the target type and define them as the target historical production records;

Obtain the loss rate of the target material in each target historical production record, define it as the material loss rate, and form a material loss rate set A, recorded as A1...An;

Obtain the number of elements in the material loss rate set A, and set it as the first number;

Calculate the average value of the material loss rate, recorded as the average loss rate, the average loss rate = (material loss rate A1 + ... material loss rate An) ÷ the first quantity.

As an optional solution of the logistics warehousing data processing method of the present invention, the secondment strategy includes:

Obtain all the factory areas owned by the enterprise except the factory area itself, and define them as supporting factory areas to form a supporting factory area set B, recorded as B1...Bn;

Obtain the time required for the transport vehicle to travel from the factory to each supporting factory respectively, and define it as the required time, forming a required time set C, which is recorded as C1...Cn respectively;

Get the current time;

Calculate the estimated arrival time of the transport vehicle from each supporting plant to the plant area respectively, and set it as the expected arrival time to form an expected arrival time set D, recorded as D1...Dn, and the expected arrival time set D = the required time set C + the current time;

The elements in the supporting plant area set B are matched one by one with the elements in the expected arrival time set D to form a first set, which is recorded as B1D1...BnDn;

Get the pre-fill time;

Calculate the earliest time that the factory can return the target materials to each supporting factory respectively, and set it as the earliest pre-return time, to form the earliest pre-return time set E, recorded as E1...En, the earliest pre-return time set E = demand duration set C + pre-supplement time;

The elements in the first set are matched one by one with the elements in the earliest pre-return time set E to form a second set, which is recorded as B1D1E1...BnDnE1;

Execute the data integration strategy to obtain the pre-use time set F;

The elements in the second set are matched one by one with the elements in the pre-use time set F to form a third set, which is recorded as B1D1E1F1...BnDnEnFn;

Extract all elements in the third set whose expected arrival time is less than or equal to the expected production time and whose earliest expected return time is less than or equal to the expected use time, and define them as the elements to be tested;

Obtain the supporting plant area under each element to be tested, define it as the plant area to be tested, and form a set of plant areas to be tested G, recorded as G1...Gn;

Execute the secondment parameter determination strategy.

As an optional solution of the logistics warehousing data processing method of the present invention, the data integration strategy includes:

Obtain the historical production records of each supporting plant area whose product type is the target type during the collection period, and define them as supporting historical production records;

Get the number of supporting factories, record it as the support quantity,

Obtain the production start time of the historical production records of each supporting plant to form a set of production start times of the supporting quantity;

The pre-use time determination strategy is executed for each production start time set, and the pre-use time corresponding to each production start time set is obtained to form a pre-use time set F, which is recorded as F1...Fn.

As an optional solution of the logistics warehousing data processing method of the present invention, the pre-use time determination strategy includes:

Arrange the production start times in the production start time set from small to large values, set the production start time with the largest value as the most recent start time, and obtain the interval between each two adjacent production start times as the adjacent interval length;

Get all different adjacent interval durations and set them as different interval durations;

Get the number of each different interval length and set it as a different number;

Arrange each different quantity from large to small according to the value, and set the different quantity with the largest value as the maximum value;

Get the number of elements in the production start time set and set it as the second number;

If the maximum number is ≥ (the second number - 1) × 60%, then the different interval durations corresponding to the maximum number are obtained and set as the target interval durations;

Calculate the pre-use time, pre-use time = most recent start time + target interval duration;

If the maximum value is less than (the second value - 1) × 60%, all different interval durations are arranged in ascending order according to their values, and the interval duration with the smallest value is set as the shortest interval duration;

Calculate the pre-use time, pre-use time = most recent start time + shortest interval duration.

As an optional solution of the logistics warehousing data processing method of the present invention, the secondment parameter determination strategy includes:

Obtain the inventory weight of the target material under each element in the plant area set G to be tested, set it as the available weight, and form an available weight set H, recorded as H1...Hn;

The elements in the plant area set G to be tested are matched one by one with the elements in the borrowable weight set H to form a fourth set, which is recorded as G1H1...G1Hn;

Calculate the pre-loan weight, pre-loan weight = target weight - target inventory weight;

Get the element whose borrowable weight ≥ pre-borrowed weight in the fourth set and set it as the target element;

Get the number of target elements;

If the number of target elements = 1, the plant area to be tested corresponding to the target element is obtained and determined as the target seconded plant area;

Then transport the target materials with the pre-loaned weight from the target loaned factory to this factory;

If the number of target elements is greater than 1, the secondment plant area determination strategy is executed;

If the number of target elements = 0, the dispersed borrowing strategy is executed.

As an optional solution of the logistics warehousing data processing method of the present invention, the secondment plant area determination strategy includes:

Obtain the plant area to be tested corresponding to each target element and define it as the determination plant area;

The time required for the transport vehicle to travel from each determined factory area to the current factory area is obtained respectively and is determined as the determined time;

Arrange all judgment durations from small to large in numerical order, and set the judgment duration with the largest value as the target duration;

Obtain the determined factory area corresponding to the target duration and set it as the target secondment factory area;

The target material with the pre-loaned weight will be transported from the target loaned factory to this factory.

As an optional solution of the logistics warehousing data processing method of the present invention, the decentralized secondment strategy includes:

Calculate the total amount of available weight, which is: total amount of available weight = available weight H1 + ... + available weight Hn;

Calculate the ratio between each element in the borrowable weight set H and the total borrowable weight, record it as weight ratio, form a weight ratio set I, record it as I1...In, weight ratio set I = borrowable weight set H ÷ total borrowable weight;

Calculate the borrowed weight of each plant area to be tested, set it as the sub-borrowed weight, and form a sub-borrowed weight set J, recorded as J1...Jn, sub-borrowed weight set J = weight ratio set I × pre-borrowed weight;

The elements in the tested plant area set G are matched one by one with the elements in the sub-borrowed weight set J to form a fifth set, which is recorded as G1J1...GnJn;

Then, according to the fifth set, target materials of different weights are loaned to each plant to be tested.

The present invention has the following beneficial effects:

1. This logistics warehousing data processing method can obtain the materials required for this production task, namely the target materials, and calculate the weight of the target materials when the factory receives the production task. Then, it can judge whether the remaining target materials in the factory are sufficient for this production according to the inventory weight of the target materials in the factory, so as to judge whether it is necessary to borrow the target materials from other factories to meet the production needs and avoid production interruptions due to insufficient materials.

2. The logistics warehousing data processing method can predict the time when other factory areas are expected to use the target materials based on the historical production records of other factory areas, and combine the estimated replenishment time of the target materials in the factory area, and the time required for the transport vehicle to travel from each factory area to the factory area, to determine which other factory areas, i.e., the factory areas to be tested, to borrow the target materials, so as not to delay the production and use of the target materials in the factory area to be tested, and to ensure that the borrowed target materials can arrive at the factory area before the estimated start time of production in the factory area, so that the production task of the factory area can proceed normally.

3. The logistics warehousing data processing method can borrow the target material from only one plant area to be tested when the target material inventory weight is sufficient for the plant area to be borrowed for use; when the target material inventory weights in multiple plant areas to be tested are sufficient for the plant area to be borrowed for use, the target material can be borrowed from the plant area with a shorter borrowing time first, thereby reducing the borrowing cost; when the target material inventory weights in all individual plant areas to be tested are insufficient for the plant area to be borrowed for use, the target materials can be borrowed from multiple plant areas respectively to ensure the normal progress of the production task of the plant area.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a block diagram of the logistics warehousing data processing method of the present invention.

DETAILED DESCRIPTION

The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

Embodiment 1, please refer to FIG1, a logistics warehousing data processing method, including:

Receive production tasks and extract production data;

Obtaining the warehouse data of the factory area, wherein the warehouse data of the factory area includes inventory weight and estimated replenishment time;

Based on the production data and the storage data of the factory, the decision data is formed through data comparison strategy to determine whether materials need to be seconded to meet the production needs of the factory;

Based on the judgment data, materials are borrowed through the borrowing strategy to meet the production needs of this plant without affecting the use of materials in other plants.

Through the above-mentioned logistics warehousing data processing method, after receiving the production task, it is possible to obtain the materials required for this production task, that is, the target materials, calculate the weight of the target materials, and then judge whether the remaining target materials in the factory are sufficient for this production according to the inventory weight of the target materials in the factory, so as to judge whether it is necessary to borrow the target materials from other factories to meet the current production needs and avoid production interruptions due to insufficient materials; when it is necessary to borrow the target materials, it is possible to judge which other factories, that is, the factories to be tested, to borrow the target materials, so as not to delay the production and use of the target materials in the factory to be tested, and to meet the borrowing needs. The target materials must arrive at this factory area before the estimated start time of production in this factory area, so that the production task of this factory area can be carried out normally; when the inventory weight of the target materials in only one factory area to be tested is sufficient for this factory area to borrow and use, the target materials can be borrowed from only this factory area to be tested; when the inventory weight of the target materials in multiple factory areas to be tested is sufficient for this factory area to borrow and use, the target materials can be borrowed from the factory area with a shorter borrowing time first, which can reduce the borrowing cost; when the inventory weight of the target materials in all individual factory areas to be tested is insufficient for this factory area to borrow and use, the target materials can be borrowed from multiple factories respectively to ensure the normal progress of this production task of this factory area.

Embodiment 2: This embodiment is an improvement made on the basis of embodiment 1. The logistics warehousing data processing method, specifically, the data comparison strategy includes:

Receive production tasks;

Extract the product type in the production task and set it as the target type;

Extract the materials needed in the production task and set them as target materials. The target materials here can be the main materials used to produce the target type of products;

Extract the weight of the target material required for the production task and set it as the required weight;

Execute the loss rate determination strategy to obtain the average loss rate;

Calculate the target weight, target weight = required weight + (required weight × average loss rate);

Obtain the inventory weight of the target material in the factory area and set it as the target inventory weight;

If the target inventory weight ≥ the target weight, it means that the remaining internal target materials in the factory area are sufficient for this production, and no judgment is made;

If the target inventory weight is less than the target weight, it means that the remaining target materials in the factory are not enough for this production. Then the estimated replenishment time of the target materials in the factory is obtained and set as the pre-replenishment time.

Extract the estimated start time of production in the production task and set it as the pre-production time;

If the estimated replenishment time is ≤ the estimated production time, it means that before or at the beginning of this production, this plant will purchase a new batch of target materials and put them into storage. Therefore, the purchase of new target materials will not affect the normal production of this time, and there is no need to borrow from other plants, so no judgment is made;

If the estimated replenishment time is greater than the estimated production time, it means that the new target materials purchased by the factory can only arrive at the factory and be put into storage after the start of this production. At the same time, the inventory weight of the existing target materials in the factory cannot meet the needs of this production, so the secondment strategy is implemented.

In this embodiment, the loss rate determination strategy specifically includes:

Get the date of receiving the production task and set it as the date of receiving the task;

Set the collection end date, collection end date = receiving task date - 1;

Set the collection duration, which is the duration of the collection period, that is, the duration of collecting historical production records;

Calculate the collection start date, collection start date = collection end date - collection duration;

The time period between the collection start date and the collection end date is defined as the collection period;

Obtain all historical production records of the factory area within the collection period, which is defined as the collection of historical production records;

Extract the collected historical production records whose product type is the target type and define them as the target historical production records;

Obtain the loss rate of the target material in each target historical production record, define it as the material loss rate, and form a material loss rate set A, recorded as A1...An;

Obtain the number of elements in the material loss rate set A, and set it as the first number;

Calculate the average value of the material loss rate, recorded as the average loss rate, the average loss rate = (material loss rate A1 + ... material loss rate An) ÷ the first quantity.

Embodiment 3: This embodiment is an improvement made on the basis of Embodiment 2. The logistics warehousing data processing method, specifically, the secondment strategy, includes:

Obtain all the factory areas owned by the enterprise except the factory area itself, and define them as supporting factory areas to form a supporting factory area set B, recorded as B1...Bn;

Obtain the time required for the transport vehicle to travel from the factory to each supporting factory respectively, and define it as the required time, forming a required time set C, which is recorded as C1...Cn respectively;

Get the current time;

Calculate the estimated arrival time of the transport vehicle from each supporting plant to the plant area respectively, and set it as the expected arrival time to form an expected arrival time set D, recorded as D1...Dn, and the expected arrival time set D = the required time set C + the current time;

The elements in the supporting plant area set B are matched one by one with the elements in the expected arrival time set D to form a first set, which is recorded as B1D1...BnDn;

Get the pre-fill time;

Calculate the earliest time that the factory can return the target materials to each supporting factory respectively, and set it as the earliest pre-return time, to form the earliest pre-return time set E, recorded as E1...En, the earliest pre-return time set E = demand duration set C + pre-supplement time;

The elements in the first set are matched one by one with the elements in the earliest pre-return time set E to form a second set, which is recorded as B1D1E1...BnDnE1;

Execute the data integration strategy to obtain the estimated use time set F, where the elements of the estimated use time of the target material are each supporting plant area;

The elements in the second set are matched one by one with the elements in the pre-use time set F to form a third set, which is recorded as B1D1E1F1...BnDnEnFn;

Extract all elements in the third set whose expected arrival time ≤ expected production time and whose earliest expected return time ≤ expected use time, and define them as the elements to be tested. The target materials transported from the supporting plant under the elements to be tested to the target plant can arrive at or before the start of this production, which indicates that borrowing the target materials from the supporting plant under the elements to be tested will not affect the normal production of this plant. At the same time, this plant can return the borrowed target materials before the supporting plant under the elements to be tested starts the next production, which will not affect the production of the supporting plant.

Obtain the supporting plant area under each element to be tested, define it as the plant area to be tested, and form a set of plant areas to be tested G, recorded as G1...Gn;

Execute the secondment parameter determination strategy.

In this embodiment, the data integration strategy specifically includes:

Obtain the historical production records of each supporting plant area whose product type is the target type during the collection period, and define them as supporting historical production records;

Get the number of supporting factories, record it as the support quantity,

Obtain the production start time of the historical production records of each supporting plant to form a set of production start times of the supporting quantity;

The pre-use time determination strategy is executed for each production start time set, and the pre-use time corresponding to each production start time set is obtained to form a pre-use time set F, which is recorded as F1...Fn.

In this embodiment, the pre-use time determination strategy specifically includes:

Arrange the production start times in the production start time set from small to large values, set the production start time with the largest value as the most recent start time, and obtain the interval between each two adjacent production start times as the adjacent interval length;

Get all different adjacent interval durations and set them as different interval durations;

Get the number of each different interval length and set it as a different number;

Arrange each different quantity from large to small according to the value, and set the different quantity with the largest value as the maximum value;

Get the number of elements in the production start time set and set it as the second number;

If the maximum quantity is ≥ (the second quantity - 1) × 60%, it indicates that in the production start time set, the different interval durations corresponding to the maximum quantity appear the most times and occupy the majority of all adjacent interval durations, which indicates that in the support plant corresponding to the production start time set, the interval durations between each use of the target material for production work are mostly the different interval durations corresponding to the maximum quantity. Then, the different interval durations corresponding to the maximum quantity are obtained and determined as the target interval duration, so as to predict that the time interval between the next time the target material is needed for production and the last time the target material has been used for production in the support plant corresponding to the production start time set is the target interval duration;

Calculate the pre-use time, pre-use time = most recent start time + target interval duration;

If the maximum quantity is less than (the second quantity - 1) × 60%, it indicates that the quantity of each different interval duration in the production start time set is not much different. Then, all different interval durations are arranged in ascending order according to the numerical value, and the different interval duration with the smallest numerical value is determined as the shortest interval duration. The shortest interval duration is determined as the time interval between the time when the target material is needed to be used for production next time and the time when the target material was used for production most recently in the support plant area corresponding to the production start time set. Thus, when the pre-use time is calculated by the shortest interval duration, the predicted time when the support plant area corresponding to the production start time set needs to use the target material for production next time can be made to be earlier. When determining whether the target material can be lent to the local plant area for use according to the pre-use time, it is avoided as much as possible that the target material corresponding to the production start time set is borrowed by the local plant area and not returned when the target material is used for production next time due to an error in the predicted pre-use time, so that the local plant area cannot produce on time.

Calculate the pre-use time, pre-use time = most recent start time + shortest interval duration.

In this embodiment, the parameter determination strategy is adjusted, specifically including:

Obtain the inventory weight of the target material under each element in the plant area set G to be tested, set it as the available weight, and form an available weight set H, recorded as H1...Hn;

The elements in the plant area set G to be tested are matched one by one with the elements in the borrowable weight set H to form a fourth set, which is recorded as G1H1...G1Hn;

Calculate the pre-loan weight, pre-loan weight = target weight - target inventory weight;

Get the element whose borrowable weight ≥ pre-borrowed weight in the fourth set and set it as the target element;

Get the number of target elements;

If the number of target elements = 1, it means that there is only one target material inventory in the plant area to be tested that has enough weight for the plant area to borrow and use, then the plant area to be tested corresponding to the target element is obtained and is determined as the target borrowed plant area;

Then transport the target materials with the pre-loaned weight from the target loaned factory to this factory;

If the number of target elements is greater than 1, it indicates that the target material inventory weight in multiple plants to be tested is sufficient for use by this plant, and the plant determination strategy for use is executed;

If the number of target elements = 0, it indicates that the target material inventory weight in all individual plants to be tested is not enough for the plant to borrow and use, so it is necessary to borrow the target materials from multiple plants at one time, and the decentralized borrowing strategy is implemented.

In this embodiment, the secondment plant area determination strategy specifically includes:

Obtain the plant area to be tested corresponding to each target element and define it as the determination plant area;

The time required for the transport vehicle to travel from each determined factory area to the current factory area is obtained respectively and is determined as the determined time;

Arrange all judgment durations from small to large in numerical order, and set the judgment duration with the largest value as the target duration;

Obtain the determined factory area corresponding to the target duration and set it as the target secondment factory area. Then, set the factory area that takes a shorter time to reach this factory area as the target secondment factory area, and secondment the target materials from the factory area with a shorter time to reduce the secondment cost;

The target material with the pre-loaned weight will be transported from the target loaned factory to this factory.

The decentralized secondment strategy includes:

Calculate the total amount of available weight, which is: total amount of available weight = available weight H1 + ... + available weight Hn;

Calculate the ratio between each element in the borrowable weight set H and the total borrowable weight, record it as weight ratio, form a weight ratio set I, record it as I1...In, weight ratio set I = borrowable weight set H ÷ total borrowable weight;

Calculate the borrowed weight of each plant area to be tested, set it as the sub-borrowed weight, and form a sub-borrowed weight set J, recorded as J1...Jn, sub-borrowed weight set J = weight ratio set I × pre-borrowed weight;

The elements in the tested plant area set G are matched one by one with the elements in the sub-borrowed weight set J to form a fifth set, which is recorded as G1J1...GnJn;

Then, according to the fifth set, target materials of different weights are loaned to each plant to be tested.

The embodiments of the present disclosure also provide a non-transitory computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the logistics warehousing data processing method in the aforementioned method embodiment.

It should be noted that more specific examples of computer-readable storage media may include portable computer disks, hard disks, erasable programmable read-only memories (EPROMs or flash memories), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present disclosure, computer-readable storage media may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device, and the computer-readable medium may be contained in the electronic device; or it may exist independently without being assembled into the electronic device.

The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device can implement the solution provided by the method embodiment.

Computer program code for performing operations of the present disclosure may be written in one or more programming languages or a combination thereof, and may be executed entirely on a user's computer, partially on a user's computer, as a stand-alone software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims (9)

1. A logistics warehousing data processing method, characterized in that it includes: Receive production tasks and extract production data; Obtaining the warehouse data of the factory area, wherein the warehouse data of the factory area includes inventory weight and estimated replenishment time; Based on the production data and the storage data of the factory, the decision data is formed through data comparison strategy to determine whether materials need to be seconded to meet the production needs of the factory; Based on the judgment data, materials are borrowed through the borrowing strategy to meet the production needs of this plant without affecting the use of materials in other plants. 2. The method for processing logistics warehousing data according to claim 1, characterized in that: the data comparison strategy includes: Receive production tasks; Extract the product type in the production task and set it as the target type; Extract the materials needed in the production task and set them as target materials; Extract the weight of the target material required for the production task and set it as the required weight; Execute the loss rate determination strategy to obtain the average loss rate; Calculate the target weight, target weight = required weight + (required weight × average loss rate); Obtain the inventory weight of the target material in the factory area and set it as the target inventory weight; If the target inventory weight ≥ the target weight, no judgment is made; If the target inventory weight is less than the target weight, the estimated replenishment time of the target material in the factory area is obtained and set as the pre-replenishment time; Extract the estimated start time of production in the production task and set it as the pre-production time; If the estimated replenishment time is ≤ the estimated production time, no judgment is made; If the expected replenishment time is greater than the expected production time, the secondment strategy will be implemented. 3. The method for processing logistics warehousing data according to claim 2, characterized in that: the loss rate determination strategy includes: Get the date of receiving the production task and set it as the date of receiving the task; Set the collection end date, collection end date = receiving task date - 1; Set the collection duration; Calculate the collection start date, collection start date = collection end date - collection duration; The time period between the collection start date and the collection end date is defined as the collection period; Obtain all historical production records of the factory area within the collection period, which is defined as the collection of historical production records; Extract the collected historical production records whose product type is the target type and define them as the target historical production records; Obtain the loss rate of the target material in each target historical production record, define it as the material loss rate, and form a material loss rate set A, recorded as A1...An; Obtain the number of elements in the material loss rate set A, and set it as the first number; Calculate the average value of the material loss rate, recorded as the average loss rate, the average loss rate = (material loss rate A1 + ... material loss rate An) ÷ the first quantity. 4. The method for processing logistics warehousing data according to claim 2, characterized in that: the secondment strategy includes: Obtain all the factory areas owned by the enterprise except the factory area itself, and define them as supporting factory areas to form a supporting factory area set B, recorded as B1...Bn; Obtain the time required for the transport vehicle to travel from the factory to each supporting factory respectively, and define it as the required time, forming a required time set C, which is recorded as C1...Cn respectively; Get the current time; Calculate the estimated arrival time of the transport vehicle from each supporting plant to the plant area respectively, and set it as the expected arrival time to form an expected arrival time set D, recorded as D1...Dn, and the expected arrival time set D = the required time set C + the current time; The elements in the supporting plant area set B are matched one by one with the elements in the expected arrival time set D to form a first set, which is recorded as B1D1...BnDn; Get the pre-fill time; Calculate the earliest time that the factory can return the target materials to each supporting factory respectively, and set it as the earliest pre-return time, to form the earliest pre-return time set E, recorded as E1...En, the earliest pre-return time set E = demand duration set C + pre-supplement time; The elements in the first set are matched one by one with the elements in the earliest pre-return time set E to form a second set, which is recorded as B1D1E1...BnDnE1; Execute the data integration strategy to obtain the pre-use time set F; The elements in the second set are matched one by one with the elements in the pre-use time set F to form a third set, which is recorded as B1D1E1F1...BnDnEnFn; Extract all elements in the third set whose expected arrival time is less than or equal to the expected production time and whose earliest expected return time is less than or equal to the expected use time, and define them as the elements to be tested; Obtain the supporting plant area under each element to be tested, define it as the plant area to be tested, and form a set of plant areas to be tested G, recorded as G1...Gn; Execute the secondment parameter determination strategy. 5. The method for processing logistics warehousing data according to claim 4, characterized in that: the data integration strategy includes: Obtain the historical production records of each supporting plant area whose product type is the target type during the collection period, and define them as supporting historical production records; Get the number of supporting factories, record it as the support quantity, Obtain the production start time of the historical production records of each supporting plant to form a set of production start times of the supporting quantity; The pre-use time determination strategy is executed for each production start time set, and the pre-use time corresponding to each production start time set is obtained to form a pre-use time set F, which is recorded as F1...Fn. 6. The method for processing logistics warehousing data according to claim 5, characterized in that: the pre-use time determination strategy includes: Arrange the production start times in the production start time set from small to large values, set the production start time with the largest value as the most recent start time, and obtain the interval between each two adjacent production start times as the adjacent interval length; Get all different adjacent interval durations and set them as different interval durations; Get the number of each different interval length and set it as a different number; Arrange each different quantity from large to small according to the value, and set the different quantity with the largest value as the maximum value; Get the number of elements in the production start time set and set it as the second number; If the maximum number is ≥ (the second number - 1) × 60%, then the different interval durations corresponding to the maximum number are obtained and set as the target interval durations; Calculate the pre-use time, pre-use time = most recent start time + target interval duration; If the maximum value is less than (the second value - 1) × 60%, all different interval durations are arranged in ascending order according to their values, and the interval duration with the smallest value is set as the shortest interval duration; Calculate the pre-use time, pre-use time = most recent start time + shortest interval duration. 7. The method for processing logistics warehousing data according to claim 4, characterized in that: the secondment parameter determination strategy includes: Obtain the inventory weight of the target material under each element in the plant area set G to be tested, set it as the available weight, and form an available weight set H, recorded as H1...Hn; The elements in the plant area set G to be tested are matched one by one with the elements in the borrowable weight set H to form a fourth set, which is recorded as G1H1...G1Hn; Calculate the pre-loan weight, pre-loan weight = target weight - target inventory weight; Get the element whose borrowable weight ≥ pre-borrowed weight in the fourth set and set it as the target element; Get the number of target elements; If the number of target elements = 1, the plant area to be tested corresponding to the target element is obtained and determined as the target seconded plant area; Then transport the target materials with the pre-loaned weight from the target loaned factory to this factory; If the number of target elements is greater than 1, the secondment plant area determination strategy is executed; If the number of target elements = 0, the dispersed borrowing strategy is executed. 8. The method for processing logistics warehousing data according to claim 7, characterized in that: the secondment plant area determination strategy includes: Obtain the plant area to be tested corresponding to each target element and define it as the determination plant area; The time required for the transport vehicle to travel from each determined factory area to the current factory area is obtained respectively and is determined as the determined time; Arrange all judgment durations from small to large in numerical order, and set the judgment duration with the largest value as the target duration; Obtain the determined factory area corresponding to the target duration and set it as the target secondment factory area; The target material with the pre-loaned weight will be transported from the target loaned factory to this factory. 9. The method for processing logistics warehousing data according to claim 8, characterized in that: the decentralized secondment strategy includes: Calculate the total amount of available weight, which is: total amount of available weight = available weight H1 + ... + available weight Hn; Calculate the ratio between each element in the borrowable weight set H and the total borrowable weight, record it as weight ratio, form a weight ratio set I, record it as I1...In, weight ratio set I = borrowable weight set H ÷ total borrowable weight; Calculate the borrowed weight of each plant area to be tested, set it as the sub-borrowed weight, and form a sub-borrowed weight set J, recorded as J1...Jn, sub-borrowed weight set J = weight ratio set I × pre-borrowed weight; The elements in the tested plant area set G are matched one by one with the elements in the sub-borrowed weight set J to form a fifth set, which is recorded as G1J1...GnJn; Then, according to the fifth set, target materials of different weights are loaned to each plant to be tested.