A hybridized approach to optimal tolerance synthesis of clutch assembly

Abstract

Specifying proper tolerances for manufactured goods results in greater savings and improved performance, which may ultimately determine whether a product succeeds or fails in the marketplace. In the past, tolerance specification has been more an art than a science, and is largely dependent upon experiences. A more scientific and reliable approach is presented in this paper. A hybrid of Nelder-Mead simplex method and particle swarm optimization (NM-PSO) is introduced for the design of tolerance of the machine elements of an overrunning clutch assembly. The objective is to obtain tolerances of the individual components so that the cost of manufacturing and quality loss is minimized. Experimental results demonstrate that hybrid NM-PSO is extremely effective and efficient in locating best-practice optimal solutions compared to geometric programming (GP), genetic algorithm (GA), and particle swarm optimization (PSO) methods.