Simulated annealing algorithm for minimising assembly variation in nonlinear assembly

Precision assemblies need close tolerance components. A close tolerance component requires secondary operations, which increase the manufacturing cost considerably. Selective assembly (SA) methods like uniform grouping, equal probability, uniform tolerance etc., was discussed in the literature focus generally on reducing surplus parts or minimising clearance variation in the linear assembly. Moreover, the existing techniques use component's tolerance for obtaining the best bin combinations rather than using the component's dimension. The present work aims to obtain maximum number of products with closer assembly specification from wider tolerance sub components of a nonlinear assembly by mating their component's dimensions based on the best bin combinations. Overrunning clutch assembly (OCA) has been considered as an example problem, in which the sub components are manufactured with wide tolerance and partitioned into three to ten bins. Combinations of best bins have been obtained for various assembly specifications by implementing simulated annealing algorithm (SAA). The proposed method has proved its effectiveness by showing 24.9% of cost saving in making OCA.