Study And Application Of The Automotive Assembly Line Balancing Method

With the rapid development of the manufacturing industry, people attach more and more attention to the quality, cost and efficiency. Especially in the typical motor industry, automobile manufacturers compete more and more fiercely nowadays. They will be eliminated if not to improve production quality and efficiency and reduce costs. The imbalance of Automobile assembly line will seriously affects the quality and efficiency of vehicle assembly. The paper proposed the methods of optimizing car assembly line balancing in the background of the plan that trial-produce small quantities of Zhongqi Sedan.Establishing a new assembly line balance model, infusing operation difficulty parameters into assembly line balance, make a more humanistic results of optimization of the assembly line balance, and give workers a sense of fairness and motivate them, which lead a conduct significance to the optimization of the realistic assembly line balance.The method of three-dimensional digital simulation is adopted to analyze the assembly process through using the DELMIA system, and then the relationship of task elements can be fixed. By using the visual assembly technology, we realized unified management of the product, resource and process data, and parallelization of the vehicle modification, tolls and fixture design and technology formulating, to achieve truly DFA and shorten the product development cycle.A genetic algorithm was designed to solve assembly line balancing problem efficiently. The coding result can meet tasks relationships in the design of population initialization, realizes the high efficiency of the algorithm processing problem. The decoding principles are based on the constraint conditions and objective functions. Both crossing and mutating are not against the constraints of tasks relation. The offspring succeed the excellent task order after crossover between their parents. Mutating diversifies individuals. Improvement strategies on the selection principle and mutating were put forward. Individual fitness function was modified according to the idea of the simulated annealing algorithm, which improves the way of choosing individuals. To enhance the capability of global search, the probability of mutating was designed to change with the generation. The improved genetic algorithm was verified efficient and acceptable with an example.The trial-produce line balancing of Zhongqi sedan is analyzed by using the introduced method of assembly line balancing in the paper. The actual resource constraints are taken into consideration in the analysis process and the results are optimized. Therefore, the method can guide automobile manufacturers to optimize their car assembly line balancing.