Designing simulation experiments: Taguchi methods and response surface metamodels

G. Taguchi (1987) has made an innovative contribution to quality planning activities through the integrated use of loss functions and orthogonal arrays. The authors focus on the improvement and implementation of some of these techniques in the simulation arena. The orthogonal arrays advocated by Taguchi are related to classical experimental designs, which have played important tactical roles in the exploration of mathematical metamodels for the simulation response surface. However, the loss function and the associated robust design philosophy provide fresh insights into the process of optimizing or improving the simulation's performance. The authors use examples to illustrate concepts such as the simultaneous treatment of variability and mean of performance measures, strategies for achieving system robustness, and implementation of noise through factorial designs. Relationships to other issues in designing and analyzing simulation experiments, such as response surface metamodels and variance reduction, are discussed.<
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