Material distribution method based on task driving

Abstract

The invention relates to an AGV (Automatic Guided Vehicle) material distribution method driven by different assembly tasks, which comprises the following steps of: 1) determining specific requirements of material distribution, and analyzing key factors which influence the material distribution efficiency; 2) establishing a material distribution management system, and integrating order management, path planning and real-time monitoring functions; 3) performing optimal path planning by adopting a dynamic planning algorithm according to the real-time order information; adjusting the priority and the distribution time window of the distribution task according to the current field condition; aGV position and logistics information are monitored in real time, and changes in the distribution process are responded in time; 4) establishing a big data analysis platform, mining historical distribution data, and optimizing a distribution strategy; a machine learning technology is applied to predict demand changes and field conditions, and the distribution efficiency is improved; 5) continuously monitoring and improving a distribution scheme; problems existing in the distribution process are analyzed, and system functions and distribution strategies are continuously optimized. According to the invention, dynamic, collaborative and efficient material distribution is realized.

Description

Technical Field

[0001] The present invention relates to automatic navigation technology, robot control algorithm and sensor technology, and in particular to an AGV material distribution method driven by different assembly tasks. Background Art

[0002] With the development of intelligent and automated manufacturing, AGV (automatic guided vehicle) plays an increasingly important role in industrial production. This task-driven material distribution method aims to enable AGV to autonomously plan routes and perform material distribution according to different assembly tasks, thereby improving production efficiency and flexibility. AGV needs to have high-precision positioning and navigation capabilities, be able to perceive the surrounding environment in real time and make corresponding decisions to ensure safety and efficiency.

[0003] The application of AGV requires multiple technologies such as accurate navigation and positioning, reasonable path planning and dynamic adjustment, multi-sensor fusion, autonomous decision-making and learning. However, in the aerospace field, due to security and confidentiality requirements, the above technologies need to be implemented without the use of wireless technology, which brings huge challenges to the application of AGV in the aerospace field to deliver materials.

[0004] Therefore, the AGV material distribution method driven by different assembly tasks needs to enter the site terrain in advance, and then independently plan the route according to different assembly tasks, so as to flexibly adapt to changes in the production environment; AGV can maintain a certain speed and accuracy during uninterrupted operation, thereby improving the efficiency of material distribution; and automated material distribution can reduce labor costs, improve the degree of automation of production lines, and thus reduce production costs; furthermore, AGV is usually equipped with a variety of sensors, which can perceive the surrounding environment in real time, avoid collisions and ensure the safety of the production process.

[0005] In summary, the application of AGV material distribution methods driven by different assembly tasks in the aerospace field can make production tasks more flexible, efficient and safer, and is suitable for the intelligent and automated needs of modern manufacturing. Summary of the invention

[0006] The purpose of the present invention is to provide an AGV material distribution method driven by different assembly tasks, which solves the problem of using AGV to distribute materials without using wireless technology under the premise of confidentiality requirements.

[0007] The present invention is achieved by the following technical solutions:

[0008] A material distribution method based on task-driven includes the following steps:

[0009] 1) Demand analysis: determine the specific needs of material distribution, including distribution scope, frequency, material types and quantity; analyze the key factors affecting material distribution efficiency;

[0010] 2) System architecture design: Establish a material distribution management system that integrates order management, route planning, and real-time monitoring functions;

[0011] 3) Task-driven delivery strategy: Based on real-time order information, a dynamic planning algorithm is used to plan the optimal path; the priority and delivery time window of the delivery task are adjusted according to the current on-site conditions; the AGV location and logistics information are monitored in real time, and changes in the delivery process are responded to in a timely manner;

[0012] 4) Information support: Establish a big data analysis platform to mine historical delivery data and optimize delivery strategies; apply machine learning technology to predict demand changes and on-site conditions and improve delivery efficiency;

[0013] 5) Evaluation system: continuously monitor and improve the distribution plan; analyze problems in the distribution process and continuously optimize system functions and distribution strategies.

[0014] In step 1), the tasks are prioritized according to their urgency and importance during the demand analysis.

[0015] In step 1), the key factors affecting material distribution efficiency include site conditions, distribution routes, storage capacity, number of AGVs, and transportation capacity.

[0016] In step 5), analyzing the problems existing in the distribution process refers to analyzing various data in the material distribution process, including distribution time, cost, and satisfaction rate, and identifying problems and bottlenecks in the distribution process.

[0017] The present invention is based on a task-driven material distribution method, which makes full use of information technology to optimize the distribution process and realizes dynamic, collaborative and efficient material distribution. It can not only meet the needs of autonomously planning paths for different assembly tasks, but also improve efficiency, reduce costs and enhance safety. DETAILED DESCRIPTION

[0018] The present invention is a material distribution method based on task-driven, and the specific steps are as follows:

[0019] (1) Task information collection

[0020] Collect material requirement information for each production task, including material type, quantity, delivery time, etc.; prioritize tasks according to their urgency and importance.

[0021] (2) Material inventory and distribution capacity analysis

[0022] Statistics on current material inventory status and understanding of the existing inventory of each material; evaluation of logistics and distribution capabilities, including the number of AGVs, transportation capacity, and distribution routes.

[0023] (3) Material distribution plan formulation

[0024] Develop material distribution plans based on task information and inventory status; give priority to meeting the material needs of urgent and important tasks; reasonably arrange distribution routes and times to improve distribution efficiency; appropriately allocate inventory to ensure that the material needs of each task are met.

[0025] (4) Real-time monitoring and adjustment

[0026] Monitor task execution and material delivery progress in real time; promptly identify and resolve problems in the delivery process, such as site changes, AGV failures, etc.; dynamically adjust delivery plans based on actual conditions to ensure material supply.

[0027] (5) Data analysis and optimization

[0028] Collect and analyze various data in the material distribution process, including delivery time, cost, fulfillment rate, etc.; identify problems and bottlenecks in the distribution process and propose optimization measures; continuously optimize distribution plans to improve material distribution efficiency and response speed.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] (1) This method aims to effectively meet the material needs of production tasks and improve the overall material distribution efficiency through task-driven material distribution planning combined with real-time monitoring and dynamic adjustment;

[0031] (2) Continuously improve the scientificity and rationality of material distribution plans through data analysis and continuous optimization.

Claims

1. A task-driven material distribution method, characterized by: The following steps are involved: 1) Demand analysis: determine the specific needs of material distribution, including distribution scope, frequency, material types and quantity; analyze the key factors affecting material distribution efficiency; 2) System architecture design: Establish a material distribution management system that integrates order management, route planning, and real-time monitoring functions; 3) Task-driven delivery strategy: Based on real-time order information, a dynamic programming algorithm is used to plan the optimal route; Adjust the priority and delivery time window of the delivery task according to the current on-site conditions; Monitor AGV location and logistics information in real time and respond to changes in the distribution process in a timely manner; 4) Information support: Establish a big data analysis platform to mine historical delivery data and optimize delivery strategies; apply machine learning technology to predict demand changes and on-site conditions and improve delivery efficiency; 5) Evaluation system: continuously monitor and improve the distribution plan; analyze problems in the distribution process and continuously optimize system functions and distribution strategies.

2. The task-driven material distribution method according to claim 1 is characterized in that: In step 1), the tasks are prioritized according to their urgency and importance during the demand analysis.

3. The task-driven material distribution method according to claim 1 is characterized in that: In step 1), the key factors affecting material distribution efficiency include site conditions, distribution routes, storage capacity, number of AGVs, and transportation capacity.

4. The task-driven material distribution method according to claim 1 is characterized in that: In step 5), analyzing the problems existing in the distribution process refers to analyzing various data in the material distribution process, including distribution time, cost, and satisfaction rate, and identifying problems and bottlenecks in the distribution process.