Research On Multi Agv Control And Scheduling Strategy In Intelligent Production Line

The scheduling strategy aims to improve the system efficiency and resource utilization,solve the problem of time and space mismatch between the supply and demand of resources in the operating environment of the system;at the same time,in order to realize the transformation and upgrading of traditional manufacturing industry and solve the current international difficulties faced by China's manufacturing industry,the research significance and application of the scheduling strategy in many fields such as product production,material transportation,etc.of the manufacturing production line The value is increasingly prominent;at present,the traditional manufacturing industry has problems such as disordered production line environment layout and insufficient automation of material conveying system.In order to realize the transformation and upgrading of the manufacturing industry and solve the problems existing in the traditional manufacturing industry,it is necessary to plan scientific production line layout,use intelligent material conveying tools and design intelligent material conveying tool scheduling strategy in combination with product process flow.In this thesis,the intelligent production line scheduling in the discrete manufacturing system is taken as the scene.Aiming at the complex environment and poor material transportation capacity of the discrete manufacturing system,the layout of the discrete manufacturing intelligent production line environment is planned,the material transportation tool AGV is designed,the moving track of AGV is optimized,the multi AGV task assignment equalization problem is studied,and the intelligent material transportation scheme of the discrete manufacturing system is proposed The work and research contents are as follows.(1)Intelligent production line operation environment setting.This thesis expounds the technological process and technical characteristics of the traditional discrete manufacturing line and the typical intelligent production line;formulates the intelligent scheme of the traditional discrete manufacturing line,plans the discrete production line;layout of the manufacturing intelligent production line;develops the production line process flow,designs the production line layout,and designs the logistics tools in the intelligent production line by combining the example rolling bearing assembly intelligent production line.(2)Multi AGV control scheme and its hardware design.According to the working environment of intelligent production line,the existing control scheme of multi AGV is studied,and the existing control scheme is improved.Combined with the working environment and control scheme,the function of AGV is determined,the architecture and key circuit of AGV control system are designed,and the models and parameters of some parts are determined.(3)Research on multi AGV material loading and transportation strategy.According to the intelligent production line working environment,the grid graph method and the topological graph method are combined to build the environment map that conforms to the AGV working in this thesis.The scheduling problem of multiple AGVs in the intelligent production line is divided into two problems of material loading and material transportation for solution.Aiming at the problem of obstacle avoidance in material loading,the improved genetic algorithm with smoothness penalty function is applied to improve the bending moment and road length,It makes the planned path smoother;aiming at the shortest route problem of material loading,an improved particle swarm optimization algorithm based on the improved inertia weight and convergence mode is proposed to optimize the material loading path by correcting the convergence accuracy and improving the local convergence;aiming at the conflict problem of material transportation path,the priority and traffic strategy to deal with the path conflict are formulated;aiming at many problems in the material problem Constraints,including road network carrying capacity,AGV capacity,time window and so on,are established respectively.(4)Case simulation verification.Aiming at the working environment of the example rolling bearing assembly intelligent production line,a multi AGV scheduling mathematical model with the lowest cost as the goal is established,the experimental scheme is designed,and the improved genetic algorithm and particle swarm optimization algorithm are applied to solve the intelligent production line and material distribution problem of rolling bearing assembly.The experimental results verify the effectiveness of the model and strategy established in this thesis.It provides a new solution and idea to solve the multi AGV scheduling problem of intelligent production line.Aiming at the key problems of multi AGV in intelligent production line,this thesis studies the layout of production line and multi AGV scheduling.The innovation of this thesis is to put forward the corresponding material transportation scheduling strategy based on the lack of material transportation automation of rolling bearing assembly production line.Combined with intelligent logistics tool AGV,the material transportation problem is divided into material transportation and material transportation,and the path conflict strategy is formulated to improve the accuracy of AGV path planning,balance the task allocation of production line,and provide a teaching platform for discrete manufacturing intelligent production line It provides a theoretical basis for multi AGV scheduling.