Warehouse management system based on big data

Abstract

The invention discloses a warehouse management system based on big data, and the system comprises a data collection module which is used for collecting warehouse management data information, and transmitting the collected warehouse management data information to a server; the stock pre-pushing module receives the warehouse management data information sent by the server and generates a sorting table of the warehouse stock based on the warehouse management data information, and the sorting table is generated and constructed based on the emergency degree of the warehouse stock to form a guide table for warehouse management of warehouse management personnel. According to the invention, the stock pre-pushing module processes the warehouse management data information collected by the data collection module, obtains the sorting values of warehouse stock cardinal numbers with the warehouse stock loss rate, the cargo warehousing time and the occupied space of the cargoes in the warehouse as parameters, and arranges the sorting values according to the sequence of small and large and carries out early warning. The real-time reminding of the stock of the warehouse management personnel is realized, and the intelligent management of the warehouse is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of warehouse management, and particularly relates to a warehouse management system based on big data. Background Art

[0002] The warehouses of modern enterprises have become the logistics centers of enterprises. Their functions are not only for storage, but more importantly as material transfer centers. The focus of warehouse management is no longer only on the safety of material storage, but more on how to use modern technologies, such as information technology and automation technology, to improve the speed and efficiency of warehouse operations. Modern warehousing plays a crucial role in the logistics supply chain. If correct inbound, inventory control, and outbound cannot be ensured, it will lead to an increase in management costs and it will be difficult to guarantee service quality, thus affecting the competitiveness of enterprises.

[0003] Therefore, a warehouse management system based on big data is needed to give timely warning prompts for the inventory quantity, periodic inbound quantity, and periodic outbound quantity in the warehouse, so as to maintain a good supply and demand cycle in warehouse management and improve warehouse management capabilities. Summary of the Invention

[0004] The purpose of the present invention is to provide a warehouse management system based on big data. The stock quantity pre-prediction module processes the warehouse management data information collected by the data collection module to obtain the sorting values of the warehouse inventory base with the warehouse inventory loss rate, the goods inbound time, and the occupied space of the goods in the warehouse as parameters. The sorting values are arranged in ascending order and warned, so as to realize the real-time reminder of the inventory quantity for warehouse management personnel, enable warehouse management personnel to obtain the inventory information in the warehouse in a timely manner, and realize the intelligent management of the warehouse.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A warehouse management system based on big data, characterized by including:

[0007] A data collection module, which is used for collecting warehouse management data information and sending the collected warehouse management data information to the server;

[0008] A stock quantity pre-prediction module, which receives the warehouse management data information sent by the server and generates a sorting table of warehouse stock quantity based on the warehouse management data information. The sorting table is generated based on the urgency of the warehouse inventory quantity and is constructed as a guidance table for warehouse management personnel to conduct warehouse management.

[0009] As a further solution of the present invention: The warehouse management data information includes the warehouse inventory loss rate, the goods inbound time, and the occupied space of the goods in the warehouse.

[0010] As a further solution of the present invention: the process of obtaining the storage inventory loss rate is as follows:

[0011] The data acquisition module collects the storage quantity of goods in the warehouse, the periodic shipment volume, and the periodic inbound volume;

[0012] Mark the storage quantity of goods in the warehouse as M, mark the periodic shipment volume as S i, i = 1, 2,..., n; where i is the cycle number of the periodic shipment volume, and mark the periodic inbound volume as B j, j = 1, 2,..., m; where j is the cycle number of the periodic inbound volume;

[0013] Through the formula Obtain the storage inventory loss rate P, where M t is the current actual storage quantity in the warehouse.

[0014] As a further solution of the present invention: the occupied space of the goods in the warehouse is the ratio of the area occupied by the goods in the warehouse to the area of the warehouse.

[0015] As a further solution of the present invention: the stock prediction module marks the storage inventory loss rate as P; marks the goods inbound time as T; marks the occupied space of the goods in the warehouse as R;

[0016] According to the formula Calculate the sorting value Cd of the storage inventory base, where d1, d2, d3, and d4 are all preset proportional coefficients, and λ is a preset correction coefficient;

[0017] Arrange the sorting value Cd of the storage inventory base in ascending order, and send the sorting table of the sorting value Cd of the storage inventory base to the server.

[0018] As a further solution of the present invention: it further includes an intelligent reminder module, and the intelligent reminder module receives the sorting table of the storage inventory base transmitted by the server;

[0019] The intelligent reminder module assigns a red icon to the first 0 - 10% of the sequence table in the sorting table, assigns a yellow icon to the 11% - 30% part in the middle of the sorting table, and assigns a green icon to the 31% - 100% part at the end of the sorting table;

[0020] Among them, the red icon indicates that the storage inventory status is poor; the yellow icon indicates that the storage inventory status is moderately good; the green icon indicates that the storage inventory status is excellent.

[0021] 7. A big data - based warehouse management system according to claim 6, characterized in that the server stores the icons corresponding to each position of the sorting table of the storage inventory base and the inventory names corresponding to the icons, and sends the stored inventory names and the icons to which the inventory belongs to the display terminal of the warehouse management personnel.

[0022] As a further solution of the present invention: it includes an intelligent reminder module, and the intelligent reminder module receives the storage quantity of goods in the warehouse, the periodic shipment quantity, and the periodic purchase quantity transmitted by the server;

[0023] The intelligent reminder module realizes early warning and reminder for warehouse management personnel based on the sorting table of the storage quantity.

[0024] As a further solution of the present invention: within the same period, when the periodic purchase quantity Bj is greater than the periodic shipment quantity Si, it will lead to an increase in the storage quantity of goods and an increase in the storage inventory pressure. At this time, Qi = Si / (Bj - Si) is used to obtain the purchase blanking base number, where Qi is an integer. When the period of the periodic purchase quantity and the periodic shipment quantity reaches Qi times, the periodic purchase quantity is blanked once, and the periodic shipment quantity maintains normal shipment.

[0025] As a further solution of the present invention: within the same period, when the periodic purchase quantity Bj is greater than the periodic shipment quantity Si, it will lead to an increase in the storage quantity of goods and an increase in the storage inventory pressure. At this time, Qi = Si / (Bj - Si) is used to obtain the purchase blanking base number, where Qi is an integer. When the period of the periodic purchase quantity and the periodic shipment quantity reaches Qi times, the periodic purchase quantity is blanked once, and the periodic shipment quantity maintains normal shipment.

[0026] The beneficial effects of the present invention:

[0027] (1) Through the stock quantity pre - deduction module of the present invention, the warehousing management data information collected by the data collection module is processed to obtain the sorting value of the warehousing inventory base number with the warehousing inventory loss rate, the goods warehousing time, and the occupied space of the goods in the warehouse as parameters. The sorting values are arranged in ascending order and early - warned, realizing real - time reminder of the inventory quantity for warehouse management personnel, enabling warehouse management personnel to obtain the inventory information in the warehouse in a timely manner, and realizing the intelligent management of warehousing;

[0028] (2) The intelligent reminder module of the present invention combines the storage quantity of goods in the warehouse, the periodic shipment quantity, and the periodic purchase quantity collected by the data collection module to make a directional plan for the periodic shipment quantity, the periodic purchase quantity, and the storage quantity of goods in the warehouse. Warehouse management personnel realize the control of the storage quantity in combination with the planning scheme, which can avoid the situation of over - stock or under - stock of the storage quantity, and has strong practicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The present invention will be further described below with reference to the drawings.

[0030] Figure 1 It is a schematic diagram of the flow chart of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0031] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0032] Embodiment 1

[0033] Please refer to Figure 1 As shown, the present invention is a warehouse management system based on big data, including: a data collection module, a stock quantity prediction module, an intelligent reminder module, and a server;

[0034] The data collection module is used for collecting warehouse management data information;

[0035] The stock quantity prediction module generates a sorting table of warehouse stock quantities based on the warehouse management data information, and the sorting table is generated based on the urgency degree of warehouse inventory;

[0036] The intelligent reminder module realizes early warning and reminder to warehouse management personnel based on the sorting table of warehouse stock quantities.

[0037] The warehouse management data information includes the warehouse inventory loss rate, the goods receipt time, and the occupied space of the goods in the warehouse. The data collection module transmits the collected warehouse inventory loss rate, goods receipt time, and occupied space of the goods in the warehouse to the server;

[0038] The stock quantity prediction module receives the warehouse inventory loss rate, goods receipt time, and occupied space of the goods in the warehouse transmitted by the server and transmits them to the server;

[0039] Mark the warehouse inventory loss rate as P; mark the goods receipt time as T; mark the occupied space of the goods in the warehouse as R;

[0040] According to the formula Calculate the sorting value Cd of the warehouse inventory base, where d1, d2, d3, and d4 are all preset proportional coefficients, and λ is a preset correction coefficient;

[0041] Arrange the sorting values Cd of the warehouse inventory base in ascending order and send the sorting table of the sorting values Cd of the warehouse inventory base to the server;

[0042] According to the formula for calculating the sorting value Cd of the warehouse inventory base, it can be known that:

[0043] When the warehouse inventory loss rate is larger, the sorting value of the warehouse inventory base is smaller, indicating that the warehouse inventory pressure is greater;

[0044] When the storage time of goods is longer, the sorting value of the warehousing inventory base is smaller, indicating that the warehousing inventory pressure is greater;

[0045] When the occupied space of goods in the warehouse is larger, that is, when the area occupied by goods in the warehouse and the warehouse area are larger, the sorting value of the warehousing inventory base is smaller, indicating that the warehousing inventory pressure is greater.

[0046] Among them, the process of obtaining the warehousing inventory loss rate P is as follows:

[0047] The warehousing management data information collected by the data acquisition module also includes the storage quantity of goods in the warehouse, the periodic shipment volume, and the periodic incoming volume. Among them, the periods of the periodic shipment volume and the periodic incoming volume are both 10 days;

[0048] The inventory pre-estimation module receives the storage quantity of goods in the warehouse, the periodic shipment volume, and the periodic incoming volume transmitted by the server;

[0049] Mark the storage quantity of goods as M, mark the periodic shipment volume as S i, i = 1, 2,..., n; where i is the cycle number of the periodic shipment volume, and mark the periodic incoming volume as Bj, j = 1, 2,..., m; where j is the cycle number of the periodic incoming volume;

[0050] Through the formula Obtain the warehousing inventory loss rate P, where Mt is the current actual storage quantity in the warehouse.

[0051] The intelligent reminder module receives the sorting table of the warehousing inventory base transmitted by the server. The intelligent reminder module assigns a red icon to the first 0 - 10% of the sequence table in the sorting table, assigns a yellow icon to the middle 11% - 30% of the sorting table, and assigns a green icon to the last 31% - 100% of the sorting table;

[0052] The intelligent reminder module sends the icons corresponding to each position of the sorting table of the warehousing inventory base and the inventory names corresponding to the icons to the server for storage;

[0053] At the same time, the server sends the stored inventory names and the icons belonging to the inventory to the display terminal of the warehousing management personnel to remind the warehousing management personnel of the inventory quantity, so as to enable the warehousing management personnel to obtain the inventory information in the warehouse in a timely manner and realize more intelligent management of the warehouse.

[0054] Embodiment 2

[0055] The intelligent reminder module receives the storage quantity of goods in the warehouse, the periodic shipment volume, and the periodic incoming volume transmitted by the server;

[0056] Mark the storage quantity of goods as M, mark the periodic shipment volume as S i, where i = 1, 2, ……, n; here i is the number of periods of the periodic shipment volume, mark the periodic purchase volume as B j, where j = 1, 2, ……, m; here j is the number of periods of the periodic purchase volume;

[0057] In the same period, when the periodic purchase volume B j is greater than the periodic shipment volume S i, it will lead to an increase in the storage quantity of goods and increase the pressure on the warehouse inventory. At this time, Q i = S i / (B j - S i) to obtain the stock-out base number, where Q i takes an integer. When the periods of the periodic purchase volume and the periodic shipment volume reach Q i times, the periodic purchase volume is out of stock once, and the periodic shipment volume maintains normal shipment;

[0058] Or: Preset the threshold of the storage quantity of goods as M k (reserve quantity). At this time, G i = (M - M k) / S i to obtain the number of times G i of the storage quantity of goods. After G i times, calculate the stock-out base number of the periodic purchase volume again;

[0059] The intelligent reminder module sends the stock-out base number Q i to the server, and the server displays the stock-out base number Q i on the terminal of the warehouse management staff to remind the warehouse management staff of the number of periods of the periodic purchase volume, effectively avoiding the pressure on the warehouse inventory.

[0060] Embodiment 3

[0061] The intelligent reminder module receives the storage quantity of goods, the periodic shipment volume, and the periodic purchase volume transmitted by the server;

[0062] Mark the storage quantity of goods as M, mark the periodic shipment volume as S i, where i = 1, 2, ……, n; here i is the number of periods of the periodic shipment volume, mark the periodic purchase volume as B j, where j = 1, 2, ……, m; here j is the number of periods of the periodic purchase volume;

[0063] In the same period, when the periodic purchase volume B j is less than the periodic shipment volume S i, it will lead to a decrease in the storage quantity of goods. Preset the threshold of the storage quantity of goods as M k (reserve quantity). At this time, O i = (M - M k) / (S i - B j) to obtain the inventory clearance base number of the goods warehouse, where O i takes an integer. When the periods of the periodic purchase volume and the periodic shipment volume reach O i times, it means that the threshold of the storage quantity of goods in the current warehouse has reached the warning value, and a warning signal is generated;

[0064] The intelligent reminder module sends the warning signal to the server, and the server sends the warning signal to the terminal of the warehouse management staff to remind the warehouse management staff to manage the current inventory of goods, and at the same time enable the warehouse management staff to adjust the periodic purchase volume or the periodic shipment volume to avoid the warning of the reserve quantity in the warehouse.

[0065] Embodiment 4

[0066] The intelligent reminder module receives the storage quantity of goods in the warehouse, the periodic shipment quantity, and the periodic purchase quantity transmitted by the server;

[0067] Mark the storage quantity of goods in the warehouse as M, mark the periodic shipment quantity as S i, i = 1, 2,..., n; where i is the cycle number of the periodic shipment quantity, and mark the periodic purchase quantity as B j, j = 1, 2,..., m; where j is the cycle number of the periodic purchase quantity;

[0068] In the same cycle, when the periodic purchase quantity B j is equal to the periodic shipment quantity S i, the storage quantity of goods in the warehouse remains unchanged, and the warehouse staff can give early warnings or handle the storage quantity of goods in the warehouse in combination with Embodiment 1 or Embodiment 2.

[0069] The above has described an embodiment of the present invention in detail, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.

Claims

1. A warehouse management system based on big data, characterized in that: include: A data collection module, which is used to collect warehouse management data information and send the collected warehouse management data information to a server; The inventory pre-push module receives the warehouse management data information sent by the server, and generates a sorting table of warehouse inventory based on the warehouse management data information. The sorting table is generated based on the urgency of the warehouse inventory and is constructed as a guidance table for warehouse management personnel to perform warehouse management.

2. According to the big data based warehouse management system described in claim 1, it is characterized in that: The warehouse management data information includes the warehouse inventory loss rate, the goods entry time and the space occupied by the goods in the warehouse.

3. A warehouse management system based on big data according to claim 2, characterized in that: The process of obtaining the warehouse inventory loss rate is as follows: The data collection module collects the cargo storage quantity, periodic shipment quantity and periodic incoming quantity; The cargo storage volume is marked as M, and the periodic shipment volume is marked as Si, i = 1, 2, ..., n; Where i is the cycle number of the cycle shipment quantity, and the cycle purchase quantity is marked as Bj, j = 1, 2, ..., m; Where j is the number of cycles of periodic purchase quantity; By formula Get the warehouse inventory loss rate P, where Mt is the actual storage capacity of the current warehouse.

4. According to the big data based warehouse management system of claim 2, it is characterized in that: The space occupied by the goods in the warehouse is the ratio of the area occupied by the goods in the warehouse to the warehouse area.

5. According to the big data based warehouse management system of claim 2, it is characterized in that: The inventory pre-push module marks the warehouse inventory loss rate as P; the goods entry time as T; and the space occupied by the goods in the warehouse as R; According to the formula The ranking value Cd of the warehouse inventory cardinality is calculated, where d1, d2, d3 and d4 are all preset proportional coefficients, and λ is a preset correction coefficient; The sorting values ​​Cd of the warehouse inventory cardinality are arranged in ascending order, and the sorting table of the sorting values ​​Cd of the warehouse inventory cardinality is sent to the server.

6. A warehouse management system based on big data according to claim 5, characterized in that: It also includes an intelligent reminder module, which receives a sorting table of warehouse inventory bases transmitted by the server; The intelligent reminder module assigns a red icon to the first 0-10% of the sequence list in the sorting list, a yellow icon to the middle 11%-30% of the sequence list, and a green icon to the tail 31%-100% of the sequence list; Among them, the red icon indicates that the warehouse inventory status is poor; the yellow icon indicates that the warehouse inventory status is good; and the green icon indicates that the warehouse inventory status is excellent.

7. A warehouse management system based on big data according to claim 6, characterized in that: The server stores the icons corresponding to each position in the sorting table of the warehouse inventory cardinality and the inventory names corresponding to the icons, and sends the stored inventory names and inventory icons to the warehouse management personnel display terminal.

8. The big data based warehouse management system according to claim 3 is characterized in that: It includes an intelligent reminder module, which receives the cargo storage quantity, periodic shipment quantity and periodic incoming quantity transmitted by the server; The intelligent reminder module provides early warning reminders to warehouse management personnel based on the warehouse storage inventory ranking table.

9. A warehouse management system based on big data according to claim 8, characterized in that: In the same cycle, when the cycle purchase volume Bj is greater than the cycle shipment volume Si, the storage volume of goods in the warehouse will increase, increasing the pressure on the warehouse inventory. At this time, Qi=Si / (Bj-Si) is used to obtain the purchase by-cycle base, where Qi is an integer. When the cycle of the cycle purchase volume and the cycle shipment volume reaches Qi times, the cycle purchase volume will be by-cycled once, and the cycle shipment volume will remain normal.

10. A warehouse management system based on big data according to claim 8, characterized in that: In the same cycle, when the cycle purchase volume Bj is greater than the cycle shipment volume Si, the storage volume of goods in the warehouse will increase, increasing the pressure on the warehouse inventory. At this time, Qi=Si / (Bj-Si) is used to obtain the purchase blank cardinality, where Qi is an integer. When the cycle of the cycle purchase volume and the cycle shipment volume reaches Qi times, the cycle purchase volume will be blank once, and the cycle shipment volume will remain normal.

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