Optimization of design tolerance and asymmetric quality loss cost using pattern search algorithm

Tolerances have a significant impact on manufacturing cost and product quality. In the design of discrete part shapes, the specification of tolerance constraints can have major consequences for product quality and cost. Traditional methods for tolerance analysis and synthesis are time consuming and have limited applicability. A more scientific approach is often desirable for better performance to overcome this difficulty. In this paper, the objective is to examine the optimal tolerance allocation by considering both tolerance cost and manufacturing cost so that the total assembly cost is minimized. A new global nonlinear optimization technique called Pattern search algorithm has been implemented to find the optimal tolerance allocation and asymmetric total cost to overcome the shortcomings in the conventional tolerance allocation problem.