A robust interactive approach to optimize correlated multiple responses

Abstract

Setting of process variables to meet the required specification of quality characteristics is a common problem in the process quality control. To obtain the most satisfactory solution, a decision maker's (DM) preference information on the trade-offs among the quality characteristics should be incorporated into the optimization procedure. In this regard, several multiple response surface optimization (MRO) techniques have been proposed in recent years. Most of these techniques require that all the preference information is specified in advance which is very difficult in practice. Furthermore, most of them assume independency of quality characteristics where their variances are constant over the experimental space. An interactive approach to optimize multiple responses is presented that does not require any information about DM's preference before solving process. This method aims to identify process variables to consider correlation among quality characteristics and minimize the variation in deviation of responses from their targets. It also accommodates dispersion effects and specification limits as well as location effects in a unified framework based on desirability functions. The features of the proposed method are investigated and the results are compared with some existing techniques through a real numerical example. Obtained results indicate the superiority of proposed methodology with respect to the major existing MRO techniques.