An integrated joint optimization procedure for robust and tolerance design

Many manufacturers have discovered that optimizing design parameters is a cost-effective means of improving product quality and being competitive in the world market. In this regard, the issues of robust design (RD) and tolerance design (TD) are clearly important, but then is significant room for improvement. The primary objective of this payer is to propose a set of enhanced optimization strategies by combining RD and TD. To be more specific, first, we consider an alternative experimental scheme using response surface methodology, while avoiding the use of controversial tools for RD such as orthogonal arrays and signal-to-noise ratios. Secondly, we discuss an enhanced optimization model by simultaneously considering both the process mean and variance, and then show that this model provides a better (or at least equal) solution in terms of the control factor settings. Thirdly, we show how the response functions for the process mean and variance, which are estimated by using an RD principle, are transmitted into the TD stage. Fourthly, we propose an optimization model for TD and present closed-form solutions for optimum tolerance limits. Finally, we study the possible effects of major cost components, and observe the behaviour of the optimum control parameter settings and the tolerance limits by carrying out sensitivity analysis.