Data Driven Modeling Simulation And Optimization Of Logistics System For Auto Parts Dispatching In Final Assembly

In recent years,with the rapid development of domestic economy,the customer demand for personalized automobile products is increasing constantly.Simultaneously,more and more enterprises choose mixed flexible production lines to meet the diversified needs of the market.Mixed-model assembly line has a higher demand on the logistics of auto parts distribution.How to ensure the accurate and timely supply of materials has become a key issue to be considered by the automobile manufacturers.Because of the complexity of automobile material supply system,it is difficult to use mathematical modeling to solve this kind of problems.Therefore,the modeling and simulation methods are used to solve these problems.However,the current modeling and simulation method requires a lot of manpower,and the results of the model differs from person to person.In order to simulate more efficiently and accurately,modeling and simulation technology based on data-driven has been applied gradually.Based on this idea,this paper takes the third-party logistics company as an example,and uses the data driven modeling method to study the problem of logistics distribution optimization.Based on the full analysis of the present situation of the logistics distribution system,for some prominent distribution problems of the unloading platform and line area of the company,solutions has been proposed: first classify parts according to the distribution characteristics,and comprehensively using Kitting,Kanban,batch distribution these three kinds of material distribution strategies to optimize the distribution strategy;then an optimization scheme about the division on line area is proposed to solve the congestion problem of line area,realizing the line logistics equalization;finally,planning lead time is optimized for the improvement of the existing logistics distribution plan.In view of the complexity of the logistics distribution system and the variety of parts and components,the data driven technology is used to simulate the model,and the optimization scheme is verified and the optimization parameters are optimized.Firstly,the workshop layout information is inputted to automatically generate the workshop layout model.After the local logic is added,input the production and logistics data to drive simulation operation.Input and output data are based on the database as a transitional platform,through the data model built in the database to achieve the conversion of the actual system data and simulation data.Through the above method,simulation experiments were carried out based on the production and logistics data of one period of time from this company.The effectiveness of the logistics distribution and line region partition optimization scheme has been verified.Simultaneously,finish the parameter settings.The optimized parameter and logistics distribution plan is transferred to the logistics planning system to guide the logistics plan adjustment through database.The experimental results show that the proposed optimization scheme can effectively reduce queue waiting time and warehouse inventory of the unloading platform,making logistics equilibrium of unloading platform and final assembly auto parts more average,so as to solve the congestion problem of unloading platform and line religion,realizing the logistics equalization.