Combining Taguchi and Response Surface Philosophies: A Dual Response Approach

TLDR

Taguchi’s experimental design methods aim to optimize mean responses while reducing variance, yet critics challenge the use of signal‑to‑noise ratios in these techniques. This paper demonstrates that a dual‑response strategy can realize Taguchi’s objectives within a more rigorous statistical framework. The dual‑response approach simultaneously optimizes a primary response and imposes constraints on a secondary response. An illustrative example confirms the effectiveness of this method.

Abstract

G. Taguchi and his school have made significant advances in the use of experimental design and analysis in industry. Of particular significance is their promotion of the use of statistical methods to achieve certain objectives in a mean response while simultaneously minimizing the variance. Unfortunately, many statisticians criticize the Taguchi techniques of analysis, particularly those based on the signal-to-noise ratio. This paper shows how the dual response approach of optimizing a "primary response" function while satisfying conditions on a "secondary response" function can be used to achieve the goals of the Taguchi philosophy within a more rigorous statistical methodology. An example illustrates this point.