A Dual-Response Approach to Robust Parameter Design for a Generalized Linear Model

Robust Parameter Design (RPD) has been used extensively in industrial experiments since its introduction by Genichi Taguchi. RPD has been studied and applied, in most cases, assuming a linear model under standard assumptions. More recently, RPD has been considered in a generalized linear model (GLM) setting. In this paper, we apply a general dual-response approach when using RPD in the case of a GLM. We motivate the need for exploring both the process mean and process variance by discussing situations when a compromise between the two is necessary. Several examples are provided in order to further motivate the need for applying a dual-response approach when applying RPD in the case of a GLM.

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