Abstract:

A satisfactory parameter design approach based on confidence interval is proposed to solve the model uncertainty problem of multivariate quality characteristics. The response models of mean and standard deviation are built by using the dual response surface method, and then their confidence interval expressions are obtained. The satisfactory sets which make each quality characteristic satisfies the respective constraint are defined based on the confidence intervals, and the constraint relaxed strategy is then designed. The consistency set that satisfies all constraints is obtained through consistency analysis. A numerical example shows that the proposed method can reduce the effect of model uncertainty and the satisfactory parameter is more reliable than the robust parameter which is obtained through the current method.