Optimization Of Cellular Manufacturing System Considering Learning Effect And Logistics

With the rapid development of the Internet,the resources of the world have been shared to the greatest extent,and the demands of consumers are more diversified.Manufacturing enterprises need to change into multi-batch and small-batch production mode to cope with the new consumption mode.Cell manufacturing system has attracted the attention of scholars and enterprises in the industry because it can meet the requirements of multi-batch and small-batch production.Cell construction and cell scheduling are the main problems in the design of cell manufacturing system.Considering the learning effect and product logistics optimization,a 0-1 non-linear programming model is established.Cell production is an important part of cell manufacturing system.This paper mainly studies how to optimize the allocation of employees and machines in cell manufacturing system,and how to optimize the production path of products so as to produce multi-type products.The corresponding cost model is constructed,and genetic algorithm is designed to optimize it.This paper is divided into two steps to optimize the unit manufacturing system.The main contents of this paper are as follows:The optimization of product logistics in cell manufacturing environment is studied.Suppose the product studied is an urgent product,that is,a product with a shorter production cycle.Aiming at minimizing the total logistics cost and delay cost of cell manufacturing system and maximizing the reward of early delivery,a non-linear mathematical programming model for production scheduling of equipment in cell is proposed,and a genetic algorithm for this problem is constructed.According to the characteristics of product scheduling,the algorithm finally obtains the optimal results.The unit system optimization problem considering employee learning effect and product flow is studied.Considering the learning effect under the influence of product complexity,new and old versions of equipment and differences in learning ability of employees,as well as the logistics cost in the process of processing,a mathematical model for minimizing inventory cost,delay cost and logistics cost is established.According to the characteristics of the problem and model,a genetic algorithm with two-dimensional solution structure is developed to solve the joint decision-making problem of personnel scheduling and product scheduling.In view of the above two parts,this paper validates them with examples,designs chromosomes with two-dimensional structure and corresponding genetic algorithm,solves the objective function of the example with MATLAB,and finally outputs the optimal personnel allocation scheme and product production route.The results of numerical experiments show that the 0-1 non-linear programming model constructed in this paper can greatly reduce the production cost under different production scales.The production cost under product logistics is significantly lower than that without logistics,which greatly enhances the advantages of enterprises in market competition.