Bias-specified robust design optimization: A generalized mean squared error approach

The primary goal of robust design is to determine the best design points by minimizing variability of the performance of a manufacturing process and minimizing deviation of the performance from a target value of interest. In this paper, a generalization and improvement of the robust optimization approach, based on the mean squared error, is suggested and applied. The constraint on the process bias is further relaxed. Different response surface functions are evaluated and compared. As an example, different optimization approaches are illustrated with a numerical test case. The results are explained and discussed.