Research On S Company Engine Assembly Line Production System Modeling And Improvement

In recent years, China’s automobile industry develop rapidly, car sales and productionappear a multiple growth. Well-known brands abroad is bullish on the Chinese market andChina’s auto industry manufacturing capacity, establishing joint venture with Chinese carcompanies in succession. Meanwhile further reduce production costs, transportation costs,aiming at more production and sales. According to statistics, in the manufacturing,assembly workload average accounts for45%of the production workload, and the costsaccounted for about30%of the manufacturing cost. Therefore solve the problem ofefficiency and cost of assembly link is one of the important means of enterprise to keepmarket competitiveness. Engine as the core component of automobile, its assembly processis the concentrated reflection of assembly technology in manufacturing. This thesis takecompany S engine assembly line as the research object, carries research on assembly lineproduction system modeling and improvement.Based on Petri net modeling rules, a Petri net model is established, and based on themapping of actual system and the Petri net model to the Flexsim model, establish aFlexsim simulation model. By running the simulation, export the result of simulation andstatistical charts. And summarize the problems of the production line through the furtheranalysis of the results. Looking for the key factors influencing the efficiency of assembly,and carries on the optimization to improve test. At the same time, establish line balancingas a more effective way to optimize production to fundamentally improve the performanceof the system, improve the assembly line production.Target on the assembly line balance, redistrict process operating element and establishelement priority relationship. Take assembly line production equilibrium index as theobjective function, and based on the actual situation, analysis the deficiency of the generalgenetic algorithm in solving assembly line balancing problem. The improved geneticalgorithm is proposed. Through the improved genetic algorithm implement optimizationdesign of the research object. Using Matlab software implement algorithm to obtain theoptimal assembly sequence and the result of homework assigned for each station, the balance of production line for better state, and verify the effectiveness of the proposedmethod. Carry on simulation experiment again, the results showed that the productivityoptimization effect is remarkable.