Production Scheduling Problem Of Mixed-model Assembly Lines With Buffers

With the advancement of science and technology and the rapid development of social economy,people’s living standards have also been continuously improved,coupled with the increase in people’s demand for personalized and diversified products,so that the automotive industry continues to get the opportunity to continue to rise in efficiency.In response to this personalized and diversified demand,most of the domestic automobile manufacturing has adopted the mixed flow assembly manufacturing mode,but the mixed flow assembly line can assemble multiple types of products with similar structure and processing technology conditions at the same time,which makes its complexity much higher than that of a single product assembly line.How to reasonably improve the mixed flow assembly line under the existing production conditions and improve its ability to produce products to meet the needs of consumers for automotive products has become a key consideration for automobile manufacturing enterprises.Therefore,based on the actual situation of enterprise production lines,this paper studies the multi-objective balance optimization problem of non-just-in-time mixed flow assembly line with buffer zone limitation.First,a production system with a limited buffer zone consisting of two sub-lines and a final assembly line was establishedMathematical model of scheduling optimization.The sequencing problem of composite mixed flow assembly line production system with limited buffer zone refers to the non-punctual arrival of the workpiece that is about to enter the limited buffer zone in the previous process of the final assembly line,considering the production load balance problem of the sub-production line and the final assembly line,and the problem of minimizing the idle waiting time of the machine,and finally establishing a mathematical model with the minimum production cycle,the levelization index of the sub-production line and the similarity index of the assembly line as the multi-objective,so as to optimize such problems.Secondly,in order to solve this problem,this paper proposes particle swarm optimization as a global optimization algorithm.The advantages of concise,easy to implement and efficient rules of elementary particle swarm operation are used to find the optimal particles and obtain the optimal ranking.In order to improve the performance of the algorithm,this paper improves the performance of the particle swarm algorithm by using the strategy of wolves rounding up prey in the wolf pack algorithm and the reference compression factor,and improves the global search ability of the algorithm.Compared with the sorting of traditional methods,the maximum completion time is more optimized than the results before improvement,which verifies the effectiveness of the algorithm.Finally,for a mixed-flow assembly line producing automotive ECUs of Weipai Automotive Electronics Company,this paper establishes a workshop multi-objective scheduling optimization model based on the mathematical model of scheduling optimization constructed in this paper when the buffer capacity and number of machines are known and the production cycle is to be determined,so as to improve the balance of the entire mixed-flow assembly line.The improved particle swarm algorithm is used to improve the mixed flow assembly line,and the results show that the multi-objective optimization model proposed in this paper has a significant effect on the overall balance of the mixed flow assembly line,and the improved mixed wolf pack particle swarm algorithm can achieve good results in solving practical problems and has practical value.