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

ABSTRACT

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.

KEYWORDS:

• mean square error
• multi-response
• multiple regression
• Taguchi method
• weighted signal-to-noise ratio

ACKNOWLEDGMENT

The authors thank the referees for their helpful comments and suggestions, which have substantially improved the content and presentation of the article.

Notes

Note. Starting levels are shown in bold.