Characterizing Performance Variation of Product Designs

Quality and reliability design practitioners have utilized Taguchi's methodology of matrix experimentation to generate computer simulation data for characterizing performance variation of product designs. However, the sampling strategy employed renders computer implementation of matrix experimentation cumbersome and statistically invalid. Weaknesses of this approach also include sample size limitation and overestimation of performance variation. An alternative approach that combines Monte Carlo simulation with the strategies of independent sampling across runs and correlated sampling between runs is presented. An application case study shows that the proposed approach constitutes an improvement on the matrix approach with respect to statistical validity and estimation accuracy.