Minimization of clearance variation and cost of assemblies using selective assembly

Abstract

Allowable variation from the nominal dimension called tolerance of a component plays a vital role in selecting manufacturing process functioning of the product while mating with other sub components and its manufacturing cost Closer tolerance required secondary process which increases manufacturing cost in considerable amount Selective assembly is a method where components are manufactured with wider tolerance measured and partitioned into groups and the components in their corresponding groups are assembled together to form precision assemblies This method reduces the cost involved in secondary operation but in the mean time cost of measuring the components are additions with the existing random assembly process A tradeoff between measuring cost of each components and secondary operation cost will be the deciding factor in implementing the selective assembly techniques Existing method mostly focused on equal group numbers and equal group width in reducing either surplus parts or reducing the clearance variation or both New methodologies and algorithms have been introduced in this work to minimize the clearance variation and cost of assemblies with two approaches In the first approach a new technique of variable group numbers according to their tolerance is suggested and the precision assemblies were produced using the best bin combinations obtained using Teaching Learning Based Optimization TLBO algorithm. newline