Robust design for unconstrained optimization problems using the Taguchi method

Abstract

Engineering optimization has been developed for the economic design of engineering systems. The conventional optimum is determined without considering noise factors. Thus, applications to practical problems may be limited. Within current design practice, noises tend to be allowed for by specification of closer tolerances, or the use of safety factors. However, these approaches may be economically infeasible. Thus, the inclusion of design-variable noises is required for practical design in optimization. A method is developed to find robust solutions for unconstrained optimization problems. The method is applied to problems with discrete variables. The orthogonal array based on the Taguchi concept is utilized to arrange the discrete variables. Through several examples, it is verified that the solutions from the suggested method are more insensitive to noise than the conventional optimum within the range of variations for design variables.