Minimizing Cost of Assembly of an Interrelated Dimensional Chain Product Using ABC Algorithm

Abstract

Selective assembly is a method where components made with wider tolerance are grouped into a number of bins. Based on the best combination of the bin, the corresponding group components are randomly selected and matched together to make an assembly. Existing techniques focused on equal group number partitioning of components, equal probability, equal group width, and equal area methods to minimize either clearance variation or surplus parts using different optimization techniques. Mostly, simple assemblies with two or three components are worked by various authors in the literature without considering their original dimension by considering only their component’s tolerance. In the present work, components are classified into different unequal group numbers based on their tolerance values. The interrelated dimensional assemblies are made in a single stage by matching the parts based on the best bin combination obtained by the artificial bee colony algorithm. A simple linear assembly and a three-armed knuckle joint assembly are considered examples of problems to demonstrate the effectiveness of the proposed method by minimizing the manufacturing cost.