Robust design in industry is an a, pp.oach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise raio(SN) to achieve the a, pp.opriate set of operating conditions where variablity around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure in the two different experimental design(product array, combined array) a, pp.oaches.