Abstract
This paper presents a methodology to incorporate manufacturing and operational variances in the design optimization stage to achieve robust and optimal performance. The procedure uses Taguchi’s orthogonal arrays to approximate the expected value of performance during optimization. This approach reduces the number of function evaluations in problems that use computationally expensive performance simulation programs. Hence, the method allows incorporation of variances on many variables simultaneously. This paper uses two illustrative examples: 1) Design of helical gears that have minimum transmission error and at the same time are less sensitive to manufacturing errors, 2) Design of beverage cans where we minimize the effects of errors in tooling on can weight and structural requirements. The optimal robust design shows a considerable decrease in sensitivity to manufacturing and operational variances and, at the same time, has good performance.
