Multi-objective circuit quality optimization using hierarchical/adaptive fuzzy set theory approach

Abstract

A new methodology based on the use of fuzzy sets theory and intended to be applied to the design of products having a number of performance requirements is outlined. Initially motivated by the intention to generalize the Taguchi methodology for off-line quality control to an arbitrary number of outputs and statistical measures, it allows the designer to specify an ordering of the performances to be optimized during the optimization process. In such a way it fits into what has become lately known as design for quality. It relies heavily on the notions of dynamically altered membership functions and aggregation procedures. It also makes strong usage of history information to guide both the search procedure in the optimization space as well as to control the dynamically altered membership function and the way they are aggregated. An example is included describing an application of the methodology to a multi-output, multistatistics OPAMP, where the authors' approach was very successful in minimizing variability and maximizing yield, results that could not be obtained by other procedures. The methodology is applicable to the generic class of design situations where the product under study has to satisfy a number of dependent or independent criteria, which can but do not need to be of statistical nature.<>