A New Method in Selective Assembly to Minimize Clearance Variation for a Radial Assembly Using Genetic Algorithm

Abstract

Selective assembly is the method of obtaining high-precision assemblies from relatively low-precision components. A relatively smaller clearance variation is achieved than in interchangeable assembly, with the components manufactured with wider tolerance. In selective assembly, the mating parts are partitioned to form selective groups with smaller tolerance, and the corresponding groups are assembled interchangeably. The mating parts are manufactured in different machines, using different processes, and with different standard deviations. Therefore, the dimensional distributions of the mating parts are not similar. In selective assembly, the number of parts in the corresponding selective groups is not similar and will result in surplus parts. The clearance variation is also very high. In this article, a new method is proposed in selective assembly. Instead of assembling components from corresponding selective groups, the components from different combination of selective groups can be assembled to achieve minimum clearance variation. Genetic algorithm is used to find the best combination of the selective groups for minimizing the clearance variation. A case of hole and shaft (radial) assembly is analyzed in this article, and the best combination is obtained to minimize assembly clearance variation. The assembly is done in three stages to completely use all the components. The best combination for the selective groups and the resulting clearance variations are tabulated. The surplus parts are minimized to a large extent.