Multi-Response Optimization Using Multiple Regression-Based Weighted Signal-to-Noise Ratio (MRWSN)

Several methods for optimization of multiple responses have been developed. Most of them have mathematical complexities and are not easily implemented by engineers. In this article, we propose a new method that integrates multiple regression technique and Taguchi's signal-to-noise (SN) ratio concept and is also easily implemented. Two sets of experimental data are analyzed using the proposed method. The proposed method is found to be superior to other methods with respect to total SN ratio as well as closeness of individual responses to their respective target values, which are reflected in the expected mean square error (MSE) values for the individual responses.