ECONOMIC OPTIMIZATION IN PRODUCT DESIGN

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Abstract
Worldwide competition and rapid technological innovation have revitalized interest in efficient techniques for product design for quality and manufacturability. The Japanese approach, popularized by G. Taguchi, uses outcomes of statistical experiments to select settings for design parameters which yield desirable process mean and variance. In this paper we present mathematical models for incorporating the results of statistical performance models along with production costs into product design models. The objective of the models is to minimize the sum of quality loss, material and production costs. Costs are assumed to be functions of the design parameters. Statistical experiments are employed to aid in the development of quality performance models. Pertinent constraints include limits on the bias of the process mean and variance. The proposed approach permits a more general environment and utilizes a more direct, economic objective as compared to the Taguchi method. A product design example is presented.