Design for circuit quality: yield maximization, minimax, and Taguchi approach

A relationship between yield optimization, deterministic minimax design, and the Taguchi 'on-target' design with variability reduction is established. It is shown that all these and other design approaches can be combined into one coherent methodology, using the same statistical optimization algorithms and the same generic gradient evaluation formulas. A specific choice is controlled by the selection of the generalized membership function w(.) of the acceptability region, and a sequence of the values of the smoothing parameter beta . Moreover, any 'intermediate' approach between the basic types introduced can be defined in a sense similar to the one used in Zadeh's (1968) fuzzy set theory. As a result, circuit quality can be optimized within the same basic methodology, using different design strategies and investigating different trade-offs, e.g., between the performance and yield. Test examples, as well as a practical CMOS circuit are investigated. Convolution smoothing techniques, and the stochastic approximation approach to statistical optimization are utilized.<>