Research On Optimization Of Storage And Retrieval Of Semi Finished Car Body High Bay Warehouse In A Vehicle Manufacturing Enterprise

W enterprise is a well-known automobile manufacturing enterprise in China.The enterprise is using an automatic high bay warehouse for mixed storage of semi-manufacture painted body and semi-manufacture body-in-white,which undertakes the storage and retrieval of semi-finished body of the entire enterprise.It is the core storage and transportation area of Bodyshop,Paint shop and Assembly shop.Currently,the high bay warehouse has problems such as traffic jams at the entrance,traffic outages at the exit,and insufficient production capacity,which affects the whole vehicle manufacturing plant capacity.So how to reasonably optimize the storage and retrieval of the high bay warehouse has already become an urgent problem to be solved.In this article,the high bay warehouse is taken as the research object,and industrial engineering,intelligent algorithms,and model simulation related methods are used to carry out research.Firstly,the current problems of the high bay warehouse of W enterprise are analyzed,and the work process and the current running status of the stereo warehouse are studied through on-site process observation.Based on the detailed known of the high bay warehouse,the main problems existing of the storage and retrieval work are summarized and analyzed;Secondly,with the goal of improving the sorting speed and efficiency,balancing the workload of the stacker,reducing the time for the stacker to pick goods in multiple tasks and optimizing the storage of related goods,a multi-objective optimization model is constructed in order to optimize the goods allocation selection and capacity of the stacker.Compare the advantages and disadvantages of the genetic algorithm and the particle swarm algorithm,and analysis the results of the two algorithms,the improved particle swarm algorithm is used to solve the problem,the reasonable and effectiveness of the optimization of the multi-objective model were verified.Finally,2D and 3D models of the warehouse are established in plant simulation software,and the improved particle swarm algorithm is used to solve the multi-objective optimization model.The optimization scheme is verified and analyzed according to the real-time data of the dynamic simulation model of the high bay warehouse.The average production capacity before optimization is 45.04 JPH,and it is very unstable,and there will be many hours that will not reach the target volume;After optimization,the average production capacity is 47.01 JPH,which not only increases the production capacity,but also makes the hourly output more and more stable.The plant simulation running results show that: the algorithm optimization proposed in this article can realize the daily production requirements of W enterprise,so that the output of the high bay warehouse can increase the overall production capacity on the basis of maintaining stable production capacity,and solve the critical problems of W enterprise.