Optimization of clearance variation in selective assembly for components with multiple characteristics

Abstract

Quality is an important aspect of any manufacturing process. Only high quality products can survive in the market. The consumer not only wants quality, precision and trouble-free products, but also wants them at attractive prices. 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 or interference between the mating parts. In some high precision assemblies, it may not be possible to have closer assembly clearance variation with interchangeable system. Selective assembly meets the above requisite and gives an enhanced solution. Selective assembly is a method of obtaining high precision assemblies from relatively low precision components. In this paper, a new selective assembly method is proposed to minimize the clearance variation and surplus parts for a complex assembly which consists of the components viz. piston, piston ring. In this assembly, each component will have more than one quality characteristic contributing for the assembly, for e.g., piston diameter will assemble with cylinder inner diameter; piston groove diameter will assemble with piston ring inner diameter, etc. In selective assembly each quality characteristic will fall in different groups. Non-dominated sorting genetic algorithm (NSGA) is used to find the best combination to obtain the minimum clearance variation in this assembly.