Integrated AGV Path Planning Of Digital Workshop Equipment Layout Optimization Method And Its Applications

Technology and industrial revolution are developing rapidly in the world.By improving people's work,life and environment with automation,the production efficiency and product quality can be improved to achieve low cost,low energy consumption,safe,reliable and intelligent production.Digital workshop should be highly integrated with automation and informatization.However,some traditional workshops mainly rely on manual driving forklifts for material transportation,which leads to low transportation efficiency.In order to promote intelligent manufacturing,it is of great urgency to achieve the digital workshop of intelligent manufacturing.The workshop automation is realized by replacing the traditional artificial forklift truck with Automatic Guided Vehicle for material transportation.Aiming at the problems existing in the multi-row facility layout and AGV path planning in the digital workshop,this paper analyzes the coupling relationship between the two,proposes the digital multi-row facility layout model and solution scheme integrated with AGV path planning,and applies it to the automatic production line design process of Wanjie intelligent fresh and wet noodle machine workshop.The main contents of this paper are as follows:In the first chapter,the development status of multi-row facility layout and AGV path planning are summarized.This chapter describes the research significance and technical background of this topic,and summarizes the research status of equipment layout modeling method,AGV path planning method and meta-heuristic algorithm.According to the shortcomings of the existing methods,the research content and organizational framework of this paper are proposed.In the second chapter,based on the mixed integer programming model,the multi-row facility layout was modeled.The objective was to minimize the logistics traffic,and the location of equipment was determined by decision variables and relevant constraints were set.In the process of solving the model,the solution process was designed based on the interactive method,and the model was solved based on the improved firefly algorithm.Finally,a machining shop is taken as an example to verify the effectiveness of the model,solution flow and algorithm in this chapter.In the third chapter,an optimization model of AGV path planning was established based on the segment flow topolpgy,and the optimal path in AGV path planning was solved by sparse A*algorithm.By establishing the relative entropy aggregation model of group decision making,the Pareto solution set of AGV path planning problem is optimized,and the reliability of decision result is improved based on entropy reliability.Finally,a machining shop is taken as an example to prove the effectiveness of the model and the solution method in this chapter.In the fourth chapter,the coupling relationship between multi-line equipment layout and AGV path planning was analyzed,and an integrated optimization model aiming at the minimum total logistics transportation amount,minimum material handling time and minimum AGV quantity between equipment groups in the digital workshop was established.An improved immune genetic algorithm was used to solve the ensemble model.Finally,an example is given to illustrate the effectiveness of the proposed method.In the fifth chapter,combine with the actual project of the enterprise,using the theory and method proposed in this paper,based on the actual environment of the enterprise workshop,multi-row facility layout and AGV path planning are carried out.By comparing the integrated optimization results with the separate optimization results,the effectiveness of the multi-row facility layout model and the solution method for integrated AGV path planning is verified.In the sixth chapter,the contents of this research are summarized and the further research of this subject is prospected.