Optimization of robust design for multiple quality characteristics

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Abstract
The Taguchi method has recently been widely applied to variability reduction for increased quality and lower cost in many different industries. The traditional Taguchi method was focused on optimizing a single quality characteristic. A real problem in a product or process possesses multiple quality characteristics. The optimization methods of multiple quality characteristics design have thus become crucial issues for industry. Several articles have presented approaches to optimizing the parameter design with multiple quality characteristics. Few have focused primarily on optimizing the correlated multiple quality characteristics problem. This research presents an approach to optimizing the correlated multiple quality characteristics with asymmetric loss function by a mathematical programming model. The goal is minimizing the total average quality loss for experiments. This proposed procedure is illustrated with data from nine previously published articles. A numerical analysis of the model is provided and the results are compared with those of prior approaches.

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