Simultaneous optimization of robust parameter and tolerance design based on generalized linear models

Robust parameter design (RPD) and tolerance design (TD) are two important stages in design process for quality improvement. Simultaneous optimization of RPD and TD is well established on the basis of linear models with constant variance assumption. However, little attention has been paid to RPD and TD with non-constant variance of residuals or non-normal responses. In order to obtain further quality improvement and cost reduction, a hybrid approach for simultaneous optimization of RPD and TD with non-constant variance or non-normal responses is proposed from generalized linear models (GLMs). First, the mathematical relationship among the process mean, process variance and control factors, noise factors and tolerances is derived from a dual-response approach based on GLMs, and the quality loss function integrating with tolerance is developed. Second, the total cost model for RPD-TD concurrent optimization based on GLMs is proposed to determine the best control factors settings and the optimal tolerance values synchronously, which is solved by genetic algorithm in detail. Finally, the proposed approach is applied into an example of electronic circuit design with non-constant variance, and the results show that the proposed approach performs better on quality improvement and cost reduction.