Minimizing assembly variation in selective assembly for complex assemblies using genetic algorithm

When a product consists of two or more components, the quality of that product depends upon the quality of the mating parts. The mating parts may be manufactured using different machines and processes with different standard deviations. Therefore, the dimensional distributions of the mating parts are not similar. This results in clearance and surplus parts between the mating parts. In this paper, a new method for selective assembly is proposed to minimize the clearance variation without any surplus part for a complex assembly which consists of three components which are gears. In this assembly, each component will have 1000 mating parts totally but with dissimilar dimensional distribution. Genetic algorithm is used to find the best combination to obtain the minimum clearance variation and zero surplus part in this assembly.