A Research On Configuration Of A Enterprise Annular Automatic Picking System And Optimization Of Goods Location

At present,many "Goods to person" picking systems in China include AGV system and stacker automatic storage system(Automated Storage/Retrieval System,AS/RS)and multi-layer shuttle system(Automated Vehicle Storage/Retrieval System,AVS/RS),There are many studies on the delivery person picking system at home and abroad,Most people focus on system performance evaluation,equipment on figuration,cargo space optimization,path optimization and soon,However,few literature studies on ring automatic picking system.The annular automatic access system is mainly composed of robot,box shelves and conveying line.The robot is located in the center of the circular space,and holds the goods and loads and unloading at the port of the conveying line.Because the working space is circular,the moving distance of the robotic arm is shorter.In this paper,the ring automatic picking system,which has been put into practical use but the literature research is still in a blank area,studies the influence of the shelf structure(number of ranks)on the picking efficiency and the influence of the cargo space distribution on the picking efficiency.Firstly,by analyzing the operation process of the system,establish the operation time model of the ring automatic picking system and the objective function(obtain the optimal system equipment configuration in the section of the example),determine the total quantity,and change the shelf structure(the number of shelf lines and columns)by Matlab to study the influence on the picking time.Secondly,in order to further improve the picking efficiency of the ring picking system,by analyzing the shelf characteristics and order characteristics of the ring automatic picking system,EIQ analysis is used to determine the strategy of ABC classification storage,and a mathematical model is established for the cargo space optimization problem of this system.The model takes the total working time and shelf weight in to account,and takes the shortest total working time and the lowest shelf weight to solve this mathematical model.Finally,this paper introduces enterprise order data,and then solves the multi-objective function with the lowest cost and the shortest operation time,so that the hourly shelf structure of the multi-objective function is 10 groups,25 columns and 10 layers.According to the above shelf structure,the designed genetic algorithm is used to solve the cargo space optimization model,and then the target function value is compared with the random cargo space layout.The results show that the shelf structure has some influence on the picking time,and the designed cargo space optimization model and algorithm effectively reduce the picking time of the system.