Multiresponse Robust Engineering: Case with Errors in Factor Levels

Abstract

The model-based robust approach for improving the quality of the process is successfully applied to different industrial processes. In the case of multiple correlated responses the estimation of the mean and variance models of the quality characteristics in production conditions, taking into account the correlation between the multiple responses, together with the heteroscedasticity of the observations due to errors in the factor levels is considered at multivariate regression fit, robust engineering modeling and the optimization stages. The application of the proposed method gives the possibility to use raw industrial data for mean and variance models estimation and leads to reduction of the predicted variance of the responses in production conditions. The proposed approach is applied for electron beam melting and refining experiments.