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In this paper, a tolerance allocation approach is proposed which attempts to select tolerances for individual dimensional variables of a product in a way that minimizes the cost while maintaining critical design requirements. The algorithm uses a reciprocal power cost-tolerance function which incorporates variable sensitivities computed in a DLM-based tolerance analysis technique. The process capabilities are applied as constraints and the genetic algorithm is used to find the optimum solution. The method is applied to a heavy duty brake problem and its results are presented.

The design process always has some known or unknown uncertainties in the design variables and parameters. The aim of robust design is minimization of performance sensitivity to uncertainties. Tolerance allocation process can significantly affect quality and robustness of the product. In this paper, a methodology to minimize a product's sensitivity to uncertainties by allocating manufacturing tolerances is presented. The robust tolerance design problem is formulated as a multi-objective optimization based on the combined function-uncertainty-cost model. Genetic algorithm is utilized to solve the multi-objective optimization and a case study is presented to illustrate the methodology.