An integrated approach based on principal component and multivariate process capability for simultaneous optimization of location and dispersion for correlated multiple response problems

Abstract

Product quality is generally defined by a family of critical characteristics, or so-called responses. In this article, a new integrated approach is proposed that has the ability to reduce the response space dimensionality and also considers both location and dispersion effects in a correlated multiple response optimization problem. The proposed approach uses a principal component (PC)-based multivariate process capability index (MCpmk;PC) as an objective function for optimization. In addition, the nonlinear search algorithm can efficiently determine the best trade-off solution in the orthogonal PC space. Three different cases are selected to illustrate the effectiveness of the new proposed approach compared to a few selected existing approaches.