Optimal Process Targets for Two Quality Characteristics under Considering the Variance of Empirical Loss

Abstract

For the manufacturer wants to get the lowest total costs, increase productivity and improve product quality, the selection of the optimal process target is one of the key research problems. The traditional method solving this problem involves using a quality loss function, for example regression analysis that based on historical data concerning customer loss associated with product performance. However, the influence of empirical loss's fluctuation on the optimal process target's selection is typically neglected. In this study, based on the previous research, we consider two quality characteristics under considering the variance of empirical loss. A bivariate empirical loss function is developed, in which, the empirical loss's fluctuation range is divided into several intervals and regard them as restrictions. Then we build the optimal model to find out the corresponding economical process targets, and explore the effect of the variance of empirical loss on the industrial production. The effectiveness of the proposed approach is illustrated by an example. The results show that the size of the variance of the empirical loss has a significant impact on the cost of the production process.