Intensive intelligent storage shelf optimization method and system based on artificial intelligence

Abstract

The invention relates to the technical field of logistics storage, in particular to an intensive intelligent storage shelf optimization method and system based on artificial intelligence, and the method comprises the following steps: S1, transporting goods to a warehousing buffer area through a forklift; s2, after receiving the information of the background management system, the warehousing control system issues stacking warehousing information to a stacking robot; s3, the warehousing control system controls an elevator to lift the goods to the corresponding layer number according to the warehousing information of the goods; s4, when the goods are delivered, the background management system issues delivery information to the storage control system; and S5, the warehousing control system dispatches the cloud spider trolley and the unstacking robot to work in a matched mode to conduct seamless unstacking on the goods through the WCS according to the ex-warehouse condition. According to the method, the warehouse-out or warehouse-in efficiency is improved after optimization processing, the seamless unstacking function can be achieved, and therefore the waiting time during warehouse-out is shortened.

Description

Technical Field

[0001] The present invention relates to the field of logistics warehousing technology, and specifically to an optimization method and system for intensive intelligent storage shelves based on artificial intelligence. Background Art

[0002] Logistics and warehousing equipment is one of the main operating tools of modern enterprises and the basis for rationally organizing batch production and mechanized assembly line operations. For third-party logistics companies, logistics and warehousing equipment is the material and technical basis for organizing warehousing and logistics activities, reflecting the logistics capabilities of the company. Logistics and warehousing equipment is the material basis of the logistics system. With the development and progress of logistics, logistics and warehousing equipment has been continuously improved and developed.

[0003] At present, there are many problems with the existing storage shelves in terms of goods outbound and inbound. First, if the goods are outbound and inbound tasks are running at the same time in the same area, the Cloud Spider Cart cannot be separated, resulting in very low outbound efficiency; secondly, if two outbound tasks running at the same time appear in the same area, executing one product first will inevitably affect the outbound delivery of the other product. If the two products are to be delivered evenly, the Cloud Spider Cart in this area will not be able to supply the robot for depalletizing in time. Summary of the invention

[0004] The purpose of the present invention is to provide an artificial intelligence-based intensive intelligent warehouse shelf optimization method and system to solve the problem of low warehouse delivery efficiency in the prior art mentioned in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solution: an optimization method for dense intelligent storage shelves based on artificial intelligence, comprising the following steps:

[0006] S1: The goods are transported to the storage buffer of the warehouse by forklifts, and the barcode scanner reads the barcode of the goods to generate the goods information. The goods information is transmitted to the background management system for storage and processing, and the palletizing storage information is generated and sent to the warehouse control system;

[0007] S2: After receiving the information from the backend management system, the warehouse control system sends the palletizing warehousing information to the palletizing robot, which palletizes the goods. After palletizing, the warehouse control system optimizes and dispatches the cloud spider car to transport the goods to the conveyor line with the number corresponding to the warehousing information, and then the conveyor line delivers the goods to the elevator;

[0008] S3: The warehouse control system controls the elevator to lift the goods to the corresponding layer according to the warehousing information of the goods, and then the warehouse control system controls the four-way shuttle to transport the goods to the designated cargo position to complete the warehousing task;

[0009] S4: When the goods are shipped out, the backend management system sends the shipping information to the warehouse control system, and the warehouse control system controls the four-way shuttle, elevator, conveyor line and cloud spider car in turn to deliver the goods to the depalletizing line or depalletizing buffer zone;

[0010] S5: The warehouse control system dispatches the cloud spider car and the depalletizing robot through WCS to cooperate with each other to seamlessly depalletize the goods according to the outbound delivery situation. The depalletized goods are then transported out by forklifts to complete the outbound delivery task.

[0011] Preferably, the warehouse control system optimizes the scheduling of the cloud spider carts by selecting a storage area based on real-time conditions, and operating the warehouse control system through manual intervention to control multiple sets of cloud spider carts to run simultaneously.

[0012] Preferably, the multiple sets of cloud spider carts controlled by the warehouse control system are carts in different areas, that is, multiple goods that need to be stored at the same time are not stored in the same area. The warehouse control system controls the multiple sets of cloud spider carts to staggeredly enter the same area according to the distribution of goods in the warehouse area.

[0013] Preferably, the product barcode includes a finished product brand code or a unique box code.

[0014] Preferably, the palletizing warehousing information includes product specifications, types, storage areas, palletizing quantities, palletizing forms and shelf location numbers.

[0015] Preferably, the warehouse control system schedules the WCS of the cloud spider cart and the depalletizing robot so that after the last pallet of the previous goods is loaded onto the cloud spider cart, the outbound task of the pallet of the next goods will be issued immediately.

[0016] Preferably, in the WCS scheduling mode, when the pallet of the next cargo arrives at the depalletizing area in advance, the warehouse control system controls the cloud spider trolley not to enter the depalletizing buffer area, and directly enters the depalletizing line for seamless depalletizing.

[0017] The present invention also provides an artificial intelligence-based intensive intelligent warehouse shelf optimization system, including a background management system, a warehouse control system, a barcode scanning gun, a dismantling / stacking robot, a four-way shuttle, an elevator, a conveyor line and a cloud spider car, and the background management system is electrically connected to the warehouse control system.

[0018] Preferably, the warehouse control system is electrically connected to the dismantling / stacking robot, four-way shuttle, elevator, conveyor line and cloud spider car through a wireless data transmission communication module, and the barcode scanning gun is electrically connected to the background management system through a wireless data transmission communication module.

[0019] Compared with the prior art, the present invention has the following beneficial effects:

[0020] 1. The intensive intelligent warehouse shelf optimization method and system based on artificial intelligence uses the warehouse control system to optimize the scheduling of the cloud spider car, that is, to select the storage area according to the real-time situation, and operate the warehouse control system through manual intervention to control multiple sets of cloud spider cars in different areas to run simultaneously, so that multiple goods that need to be stored at the same time are not stored in the same area. The warehouse control system controls multiple sets of cloud spider cars to stagger the storage in the same area according to the distribution of goods in the warehouse area, thereby improving the efficiency of outbound or inbound storage;

[0021] 2. The intensive intelligent warehouse shelf optimization method and system based on artificial intelligence uses the warehouse control system to schedule the WCS of the cloud spider car and the depalletizing robot, that is, after the last pallet of the previous goods is on the cloud spider car, the pallet outbound task of the next goods will be issued immediately. In the WCS scheduling mode, when the pallet of the next goods arrives at the depalletizing area in advance, the warehouse control system controls the cloud spider car not to enter the depalletizing buffer area, and directly enters the depalletizing line for seamless depalletizing. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0024] The structure of the intensive intelligent storage shelf optimization method based on artificial intelligence provided by the present invention is as follows: Figure 1 As shown, the following steps are included:

[0025] S1: The goods are transported to the storage buffer of the warehouse by forklift, and the barcode of the goods is read by the barcode scanner to generate the goods information. The goods information is transmitted to the background management system for storage and processing, and the palletizing storage information is generated and sent to the warehouse control system.

[0026] Among them, the product barcode includes the finished product brand code or the unique code of the box; the palletizing warehousing information includes product specifications, types, storage areas, palletizing quantities, palletizing forms and shelf location numbers.

[0027] S2: After receiving the information from the background management system, the warehouse control system sends the palletizing warehousing information to the palletizing robot, which palletizes the goods. After palletizing, the warehouse control system optimizes and dispatches the cloud spider cart to transport the goods to the conveyor line with the number corresponding to the warehousing information, and then the conveyor line delivers the goods to the elevator.

[0028] Among them, the warehouse control system optimizes the scheduling of the Cloud Spider Carts as follows: select the warehousing area according to the real-time situation, and operate the warehouse control system through manual intervention to control multiple sets of Cloud Spider Carts to run simultaneously; the multiple sets of Cloud Spider Carts controlled by the warehouse control system are in different areas, that is, multiple goods that need to be stored at the same time are not stored in the same area. The warehouse control system controls multiple sets of Cloud Spider Carts to enter the warehouse in the same area at staggered intervals according to the distribution of goods in the warehouse area.

[0029] S3: The warehouse control system controls the elevator to lift the goods to the corresponding level according to the warehousing information of the goods. Then the warehouse control system controls the four-way shuttle to transport the goods to the designated cargo location to complete the warehousing task.

[0030] S4: When the goods are shipped out, the background management system sends the shipping information to the warehouse control system, and the warehouse control system controls the four-way shuttle, elevator, conveyor line and cloud spider car in turn to deliver the goods to the depalletizing line or depalletizing buffer zone.

[0031] S5: The warehouse control system dispatches the cloud spider car and the depalletizing robot through WCS to cooperate with each other to seamlessly depalletize the goods according to the outbound delivery situation. The depalletized goods are then transported out by forklifts to complete the outbound delivery task.

[0032] Among them, the warehouse control system's WCS scheduling of the Cloud Spider Cart and the depalletizing robot is that after the last pallet of the previous goods is on the Cloud Spider Cart, the pallet outbound task of the next goods will be issued immediately; in the WCS scheduling mode, when the pallet of the next goods arrives at the depalletizing area in advance, the warehouse control system controls the Cloud Spider Cart not to enter the depalletizing cache area, and directly enters the depalletizing line for seamless depalletizing.

[0033] The present invention also provides an artificial intelligence-based intensive intelligent warehouse shelf optimization system, including a background management system, a warehouse control system, a barcode scanner, a dismantling / stacking robot, a four-way shuttle, an elevator, a conveyor line and a cloud spider cart. The background management system is electrically connected to the warehouse control system, and the warehouse control system is electrically connected to the dismantling / stacking robot, the four-way shuttle, the elevator, the conveyor line and the cloud spider cart through a wireless data transmission communication module. The barcode scanner is electrically connected to the background management system through a wireless data transmission communication module.

[0034] Method steps: First, the goods are transported to the warehouse's warehousing buffer by forklifts, and the barcode scanner reads the barcode of the goods to generate the goods information. The goods information is transmitted to the background management system for storage and processing, and the palletizing warehousing information is generated and sent to the warehouse control system; then, after receiving the information from the background management system, the warehouse control system sends the palletizing warehousing information to the palletizing robot, and the palletizing robot palletizes the goods. After palletizing, the warehouse control system optimizes and dispatches the cloud spider cart to transport the goods to the conveyor line with the number corresponding to the warehousing information, and then the conveyor line delivers the goods to the elevator.

[0035] Subsequently, the warehouse control system controls the elevator to lift the goods to the corresponding level according to the warehousing information of the goods. Then the warehouse control system controls the four-way shuttle to transport the goods to the designated cargo location to complete the warehousing task.

[0036] When the goods are shipped out, the backend management system sends the shipping information to the warehouse control system. The warehouse control system controls the four-way shuttle, elevator, conveyor line and cloud spider car in turn to deliver the goods to the depalletizing line or depalletizing buffer zone. Then, the warehouse control system dispatches the cloud spider car and the depalletizing robot through WCS to cooperate with each other to seamlessly depalletize the goods according to the shipping situation. The depalletized goods are then transported out by forklift to complete the shipping task.

[0037] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An artificial intelligence-based intensive intelligent storage shelf optimization method, characterized in that: The steps include: S1: The goods are transported to the storage buffer of the warehouse by forklifts, and the barcode scanner reads the barcode of the goods to generate the goods information. The goods information is transmitted to the background management system for storage and processing, and the palletizing storage information is generated and sent to the warehouse control system; S2: After receiving the information from the backend management system, the warehouse control system sends the palletizing warehousing information to the palletizing robot, which palletizes the goods. After palletizing, the warehouse control system optimizes and dispatches the cloud spider car to transport the goods to the conveyor line with the number corresponding to the warehousing information, and then the conveyor line delivers the goods to the elevator; S3: The warehouse control system controls the elevator to lift the goods to the corresponding layer according to the warehousing information of the goods, and then the warehouse control system controls the four-way shuttle to transport the goods to the designated cargo position to complete the warehousing task; S4: When the goods are shipped out, the backend management system sends the shipping information to the warehouse control system, and the warehouse control system controls the four-way shuttle, elevator, conveyor line and cloud spider car in turn to deliver the goods to the depalletizing line or depalletizing buffer zone; S5: The warehouse control system dispatches the cloud spider car and the depalletizing robot through WCS to cooperate with each other to seamlessly depalletize the goods according to the outbound delivery situation. The depalletized goods are then transported out by forklifts to complete the outbound delivery task.

2. The method for optimizing dense intelligent storage shelves based on artificial intelligence according to claim 1 is characterized in that: The warehouse control system optimizes the scheduling of the cloud spider cart by selecting the storage area according to the real-time situation, and operates the warehouse control system through manual intervention to control multiple sets of cloud spider carts to run simultaneously.

3. The method for optimizing dense intelligent storage shelves based on artificial intelligence according to claim 2 is characterized in that: The multiple sets of cloud spider carts controlled by the warehouse control system are carts in different areas, that is, multiple goods that need to be stored at the same time are not stored in the same area. The warehouse control system controls the multiple sets of cloud spider carts to enter the warehouse in the same area in an staggered manner according to the distribution of goods in the warehouse area.

4. The method for optimizing dense intelligent storage shelves based on artificial intelligence according to claim 1 is characterized in that: The product barcode includes a finished product brand code or a unique box code.

5. The method for optimizing dense intelligent storage shelves based on artificial intelligence according to claim 1 is characterized in that: The palletizing warehousing information includes product specifications, types, storage areas, palletizing quantities, palletizing forms and shelf location numbers.

6. The method for optimizing dense intelligent storage shelves based on artificial intelligence according to claim 1 is characterized in that: The warehouse control system schedules the WCS of the cloud spider cart and the depalletizing robot in such a way that after the last pallet of the previous goods is loaded onto the cloud spider cart, the outbound task of the pallet of the next goods will be issued immediately.

7. The method for optimizing dense intelligent storage shelves based on artificial intelligence according to claim 6 is characterized in that: In the WCS scheduling mode, when the pallet of the next cargo arrives at the depalletizing area ahead of time, the warehouse control system controls the cloud spider trolley not to enter the depalletizing buffer area, and directly enters the depalletizing line for seamless depalletizing.

8. The intensive intelligent storage shelf optimization system based on artificial intelligence is characterized by: The artificial intelligence-based intensive intelligent warehouse shelf optimization method applied to any one of claims 1-7 includes a background management system, a warehouse control system, a barcode scanner, a dismantling / stacking robot, a four-way shuttle, an elevator, a conveyor line and a cloud spider car, and the background management system is electrically connected to the warehouse control system.

9. The artificial intelligence-based intensive intelligent storage shelf optimization system according to claim 8 is characterized in that: The warehouse control system is electrically connected to the dismantling / stacking robot, the four-way shuttle, the elevator, the conveyor line and the cloud spider car through a wireless data transmission communication module, and the barcode scanning gun is electrically connected to the background management system through a wireless data transmission communication module.

Images