Management method for automatically and intelligently pushing order to warehouse

Abstract

The invention provides a management method for automatically and intelligently pushing orders to warehousing, and the method comprises the steps: (1) carrying out the classification processing of orders, and generating a unique product label; (2) a goods picking task is generated according to a produced order, and warehousing and goods collection are carried out; (3) carrying out intelligent warehousing management on the warehoused collected goods; and (4) intelligently monitoring the collected products and making a task scheduling plan. According to the technical scheme, through intelligent pushing of the production tasks, intelligent warehousing of the products and intelligent scheduling of the products, production efficiency, logistics efficiency and warehousing efficiency are improved, automation and intelligence of production, logistics and distribution are achieved, smooth operation of production and logistics is ensured, and efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent technology, and specifically relates to an automated intelligent management method for order pushing to warehousing. Background Art

[0002] With the development of science and technology and the progress of society, intelligent manufacturing systems, logistics management and warehousing management have become an indispensable and important part of modern enterprises. Intelligent manufacturing systems use automation equipment and computer technology to achieve intelligent control and optimization of the production process, improve production efficiency and product quality. Logistics management uses information technology and network technology to achieve the rational allocation and utilization of logistics resources, improve logistics efficiency and reduce logistics costs. Warehousing management uses automation equipment and computer technology to achieve intelligent management and inventory control of warehouses, improve warehouse utilization and inventory turnover.

[0003] However, the existing manufacturing system usually adopts an order-based production model, that is, production is arranged according to customer orders. Although this method can meet customer needs, the production efficiency is low because each order requires a separate production line and workers. At the same time, there are also some problems with the existing logistics management and warehousing management, such as unreasonable utilization of logistics resources and inefficient warehouse management.

[0004] Although the existing intelligent manufacturing systems, logistics management and warehousing management technologies have improved production efficiency and logistics efficiency to a certain extent, there are still some problems. For example, the existing intelligent manufacturing systems usually lack the function of intelligently pushing production tasks, and require manual arrangement of production lines and workers, resulting in low production efficiency. The existing logistics management lacks real-time monitoring and intelligent scheduling functions for logistics points, which is prone to problems such as waste of logistics resources and logistics delays. The existing warehousing management lacks the function of intelligent warehousing for inventory goods, and requires manual warehousing operations, which is inefficient. Summary of the invention

[0005] The present invention provides an automated intelligent management method for pushing orders to warehousing, the improvement of which is that the method comprises

[0006] (1) Orders are classified and processed, and unique product labels are generated;

[0007] (2) Generate a pick-up task for the produced order and collect the goods into the warehouse;

[0008] (3) Intelligent warehousing management of incoming goods;

[0009] (4) Intelligently monitor the collected products and formulate task scheduling plans.

[0010] Furthermore, the step (1) includes the system identifying that after the factory receives the order, it automatically prints labels according to the project and user dimensions and labels each product.

[0011] Furthermore, the label printing includes a system order management module triggering a label printing instruction, generating a unique product label for printing according to product order information, and the label information includes project and user information.

[0012] Furthermore, the step (2) includes automatically generating a pick-up task based on the produced order, and sending the task to the carrier, and the carrier collects the goods into the warehouse.

[0013] Furthermore, the system production management module confirms the production status of each product in the order and notifies the order management module to automatically generate a pickup task based on the order information. The order management module uses AI technology to optimize the logistics path and sends the pickup task to the carrier. The carrier confirms the task information and picks up the goods according to the task requirements, and delivers the products to the project's logistics point or warehouse for warehousing and collection.

[0014] Furthermore, step (3) includes performing intelligent warehousing operations on the ordered products delivered by the carrier, and the intelligent warehousing operations include automatically scanning product information, updating inventory data and allocating storage locations, updating product information into the system, and placing the products at designated storage locations.

[0015] Furthermore, the system warehouse management module automatically selects a suitable storage location for warehousing based on preset rules and algorithms. The warehouse management module considers factors including storage location occupancy, cargo type and shelf life, and intelligently arranges order products for intelligent warehousing operations.

[0016] Furthermore, the step (4) includes intelligently monitoring whether the ordered products at each logistics point have been collected. After the collection is completed, a long-distance task is automatically sent to the carrier according to a time period to deliver the products to the project site or the user's home.

[0017] Furthermore, the system logistics management module uses big data analysis to predict collection time and demand, optimize logistics resource allocation, and monitor the product collection status in each logistics point order in real time; when the order product collection of a certain logistics point is completed, the logistics management module automatically generates a long-distance transportation task.

[0018] Furthermore, blockchain technology is used to send long-distance transportation tasks to carriers and monitor data. The carriers will dispatch logistics vehicles to logistics points and send products to project sites or users' homes according to the task requirements.

[0019] Beneficial effects:

[0020] This technical solution improves production efficiency, logistics efficiency and warehousing efficiency through intelligent push of production tasks, intelligent warehousing of products and intelligent scheduling of products, and realizes the automation and intelligence of production, logistics and distribution to ensure the smooth operation of production and logistics and improve efficiency and accuracy.

[0021] The present invention realizes the rational allocation and utilization of logistics resources through information technology and network technology, such as AI technology and machine learning technology, to improve logistics efficiency and reduce logistics costs. In addition, the present invention realizes the monitoring and optimization of all processes, real-time monitoring and intelligent scheduling of logistics points through automated equipment and monitoring technology, avoids problems such as waste of logistics resources and logistics delays, ensures smooth information flow, realizes intelligent management and inventory control of warehouses, improves warehouse utilization and inventory turnover, and at the same time, through intelligent monitoring of whether the goods of the owners of each logistics point have been collected, automatically sends long-distance tasks to carriers, and sends them to the project site or the owner's home, realizes real-time monitoring and intelligent scheduling of logistics points, improves logistics efficiency, reduces logistics costs, and improves customer satisfaction.

[0022] It should be understood that the above general description and the following specific embodiments are only exemplary and illustrative and do not limit the scope of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A flow chart of an automated intelligent management method for pushing orders to warehousing according to the present invention;

[0024] It should be understood that the drawings are not necessarily drawn to scale, presenting somewhat simplified representations of various features illustrative of the basic principles of the present disclosure. The specific design features of the present invention as disclosed herein, including, for example, specific dimensions, orientations, locations, and shapes will be determined in part by the particular intended application and use environment.

[0025] In the drawings, reference numbers refer to the same or equivalent parts of the present invention throughout the several figures of the drawing. DETAILED DESCRIPTION

[0026] Reference will now be made in detail to various embodiments of the present invention, examples of which are illustrated in the accompanying drawings and described below. Although the present invention will be described in conjunction with exemplary embodiments of the present invention, it should be understood that this specification is not intended to limit the present invention to those exemplary embodiments. On the other hand, the present invention is intended to cover not only the exemplary embodiments of the present invention, but also various alternatives, modifiers, equivalents and other embodiments, which may be included in the spirit and scope of the present invention as defined by the appended claims.

[0027] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. The specific structures and functions described in the exemplary embodiments of the present invention are for illustrative purposes only. Embodiments according to the concepts of the present invention can be implemented in various forms, and it should be understood that they should not be interpreted as being limited to the exemplary embodiments described in the exemplary embodiments, but include all modifications, equivalents or substitutes included in the spirit and scope of the present invention.

[0028] Throughout the specification, the professional terms used herein are only for describing various exemplary embodiments and are not intended to be limiting. It will be further understood that the terms "include", "comprising", "having", etc., when used in the exemplary embodiments, specifically refer to the presence of the stated parts, steps, operations or elements, but do not exclude the presence or addition of one or more other parts, steps, operations or elements.

[0029] like Figure 1 As shown, the present invention provides an automated intelligent management method for pushing orders to warehousing, and the specific steps are as follows:

[0030] Step 1: Classify the orders and generate unique product labels; after the system recognizes that the factory has received the order, the system automatically prints labels according to project and user dimensions, and workers label each product.

[0031] After the system recognizes that the factory has received the order, the system order management module triggers the label printing instruction, and the system generates a unique product label based on the product order information;

[0032] The label information includes project and user information to facilitate subsequent logistics and delivery;

[0033] Workers label products according to label information and accurately attach labels to each product to ensure that each product can be accurately traced to the project and user;

[0034] Use RFID tags and readers for labeling to achieve automatic labeling and reduce manual operations;

[0035] Introducing machine learning algorithms to automatically optimize label design and content to improve read rates and customer satisfaction.

[0036] For example: -Parameter settings for printing labels:

[0037] - Temperature: 40℃

[0038] - Duration: 20 seconds

[0039] -Pressure: 0.5MPa

[0040] Step 2: Generate a pickup task for the produced order and collect the goods into the warehouse; after the order is produced, the system will automatically generate a pickup task based on the produced order and send the task to the carrier. The carrier is responsible for picking up the goods to the project's logistics point or warehouse for collection.

[0041] After the system production management module confirms that the production is completed, it confirms the production status of each product in the order and notifies the order management module to automatically generate the corresponding delivery task according to the order information;

[0042] The order management module uses AI technology to optimize logistics routes and send pick-up tasks to designated carriers to ensure that goods can be picked up in a timely manner, which can reduce transportation time and costs for internal logistics departments or external logistics service providers;

[0043] The carrier confirms the task information and picks up the goods according to the task requirements, sends the logistics vehicle to the factory's logistics point or warehouse, and delivers the products in the order to the project's logistics point or warehouse for warehousing and collection. The system uses IoT devices to monitor the delivery process and monitor the transportation status and cargo safety in real time.

[0044] For example: -Generated pickup task parameter settings:

[0045] -Transport vehicle model: Beijing XX0000

[0046] -Transportation route: City ring line

[0047] - Estimated shipping time is 3 hours.

[0048] Step 3: Intelligent warehousing management for incoming goods; intelligent warehousing operations are performed on the ordered products delivered by the carrier, including automatic scanning of product information, updating inventory data, allocating storage locations, etc. The product information is updated in the system, and the products are placed in the designated warehouse locations. The system will guide logistics personnel or automatic equipment to place the products in the correct warehouse locations, designated shelves or areas for subsequent outbound delivery and distribution.

[0049] The system warehouse management module automatically selects the most suitable storage location for warehousing according to preset rules and algorithms. The warehouse management module considers factors such as storage location occupancy, cargo type, shelf life, etc.; it uses automated warehousing equipment, such as automatic forklifts, stacking robots, etc., to achieve efficient warehousing;

[0050] The warehouse management module introduces machine vision technology to automatically detect the quality and quantity of incoming products and reduce human errors.

[0051] For example: -Parameter settings for intelligent warehousing:

[0052] -Storage location allocation algorithm: Shortest distance first

[0053] - Inventory turnover target: 90%.

[0054] Step 4: Intelligently monitor the collected products and formulate a task scheduling plan; the system intelligently monitors whether the products in the orders of each logistics point have been collected. After the collection is completed, the system automatically sends long-distance tasks to the carrier according to the time period to send the products to the project site or the user's home.

[0055] The system logistics management module monitors the cargo collection status of each logistics point;

[0056] The logistics management module uses big data analysis to predict the collection time and demand and optimize the allocation of logistics resources. The logistics management module monitors the collection status of products in the order of each logistics point in real time. Whether the products in the order have been collected, when the order products of a certain logistics point have been collected, the logistics management module automatically generates a long-distance transportation task;

[0057] Using blockchain technology, long-distance transportation tasks are sent to carriers and data is monitored. According to the task requirements, the carrier dispatches logistics vehicles to logistics points and safely sends products to the project site or the user's home, ensuring the security and transparency of the data.

[0058] Such as: - Monitoring parameter settings:

[0059] -Monitoring frequency: once every half hour

[0060] - Monitoring range: within a 10km radius of the logistics point.

[0061] The above-mentioned embodiments of the present application can be implemented in various hardware, software coding or a combination of the two. For example, the embodiments of the present application can also represent the program code for executing the above-mentioned method in a data signal processor. The present application can also relate to the various functions performed by a computer processor, a digital signal processor, a microprocessor or a field programmable gate array. The above-mentioned processor can be configured according to the present application to perform specific tasks, which are completed by executing machine-readable software code or firmware code that defines the specific method disclosed by the present application. The software code or firmware code development can represent different programming languages ​​and different formats or forms. Different target platform compiled software codes can also be represented. However, the different code styles, types and languages ​​of the software code for performing tasks according to the present application and other types of configuration codes do not depart from the spirit and scope of the present application.

[0062] The foregoing description of specific exemplary embodiments of the present invention has been presented for the purpose of illustration and description. It is not intended to exclude or limit the present invention to the precise form disclosed, and it is obvious that many modifications and changes are feasible in view of the above teachings. Exemplary embodiments are selected and described to explain certain principles of the present invention and their practical application, so that other technicians in the field can make or use various exemplary embodiments of the present invention, and various alternatives and modifications thereof. It is intended that the scope of the present invention will be defined by the claims attached hereto and their equivalents.

[0063] It is to be understood that the above embodiments are merely exemplary embodiments used to illustrate the principles of the present invention, but the present invention is not limited thereto. For those of ordinary skill in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. An automated and intelligent management method for pushing orders to warehousing, characterized in that: The method comprises (1) Orders are classified and processed, and unique product labels are generated; (2) Generate a pick-up task for the produced order and collect the goods into the warehouse; (3) Intelligent warehousing management of incoming goods; (4) Intelligently monitor the collected products and formulate task scheduling plans.

2. The method for managing the automated and intelligent order push to warehousing according to claim 1, characterized in that: The step (1) includes the system identifying that after the factory receives the order, it automatically prints labels according to the project and user dimensions and labels each product.

3. The method for managing the automated and intelligent order push to warehousing according to claim 2, characterized in that: The label printing includes a system order management module triggering a label printing instruction, generating a unique product label for printing according to product order information, and the label information includes project and user information.

4. The method for managing the automated and intelligent order push to warehousing according to claim 1, characterized in that: The step (2) includes automatically generating a pick-up task based on the produced order, and sending the task to the carrier, and the carrier collects the goods into the warehouse.

5. The method for managing the automated and intelligent order push to warehousing according to claim 4 is characterized in that: The system production management module confirms the production status of each product in the order and notifies the order management module to automatically generate a pickup task based on the order information. The order management module uses AI technology to optimize the logistics path and sends the pickup task to the carrier. The carrier confirms the task information and picks up the goods according to the task requirements, and delivers the products to the project's logistics point or warehouse for warehousing and collection.

6. The method for managing the automated and intelligent order push to warehousing according to claim 1, characterized in that: The step (3) includes performing intelligent warehousing operations on the ordered products shipped by the carrier, and the intelligent warehousing operations include automatically scanning product information, updating inventory data and allocating storage locations, updating product information into the system, and placing the products at designated storage locations.

7. The method for managing the automated and intelligent order push to warehousing according to claim 6, characterized in that: The system warehouse management module automatically selects a suitable storage location for warehousing based on preset rules and algorithms. The warehouse management module considers factors including storage location occupancy, cargo type and shelf life, and intelligently arranges order products for intelligent warehousing operations.

8. The method for managing the automated and intelligent order push to warehousing according to claim 1, characterized in that: The step (4) includes intelligently monitoring whether the ordered products at each logistics point have been collected. After the collection is completed, a long-distance task is automatically sent to the carrier according to a time period to send the products to the project site or the user's home.

9. The method for managing the automated and intelligent order push to warehousing according to claim 8, characterized in that: The system logistics management module uses big data analysis to predict collection time and demand, optimize logistics resource allocation, and monitor the product collection status in each logistics point order in real time; when the order product collection of a certain logistics point is completed, the logistics management module automatically generates a long-distance transportation task.

10. The method for managing the automated and intelligent order push to warehousing according to claim 9, characterized in that: Using blockchain technology, long-distance transportation tasks are sent to carriers and data is monitored. According to the task requirements, the carriers dispatch logistics vehicles to logistics points and send products to project sites or users' homes.

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