Optimization Of Selective Assembly For Components With Multiple Quality Characteristics Of CoPS

With the diversity requirements, resulting in most of the products are toward the direction of increasing complexity. Components of complex products are usually with multiple quality characteristics. Study selective assembly problem of complex products which with multiple quality characteristics can reduce the production and improve the quality of products. So that customers can buy high-quality products at a lowest price.Firstly, the multi-objective optimization theory and multi-objective particle swarm optimization theory was analyzed. Then, the properties and quality criteria of selective assembly of components with multi-quality characteristics were analyzed to establish a mathematical model. The objective function of this model is to minimize the clearance variation in selective assembly for components with multiple characteristics. This multi-objective optimization model is constraint to clearance variation of every combination.And then, in order to improve the traditional multi-objective particle swarm optimization, paper introduces a fitness sharing strategy and a dynamic archiving strategy. Meanwhile, a quick sorting method is presented to improve the traditional sorting method of Pareto non-dominated solution set.Finally, the model is applied to optimize the selective assembly problem of an engine. The selective assembly problem of engine is a typical problem of the selective assembly for components with multiple characteristics. And the optimization achieved good results. Compared to interchangeable system, assembly precision was improved by about 60 percent in this model.