CONTINUOUS TAGUCHI - A MODEL-BASED APPROACH TO TAGUCHIS QUALITY BY DESIGN WITH ARBITRARY DISTRIBUTIONS

Statistical experimental design has been used in 'off-line' quality co ntrol to determine the optimal settings for a system even when the mat hematical model is known. Taguchi demonstrated how signal-to-noise rat ios could be used to improve the performance of a system through varia nce minimization. However, these statistical methods often do not use the full distribution information that may be available. Proposed in t his paper is an extension and complement to Taguchi's use of experimen tal design and signal-to-noise ratios for known system models. The use of a probability transformation method with the mathematical system m odel will allow designers to perform parameter and tolerance design si multaneously using a method of 'fast integration'. The result is a new method in the field of 'quality by design', which we call continuous Taguchi, that can handle both linear and non-linear systems, with comp onents of any distribution type, with or without correlation of the va riables. In addition, an interpretation of Taguchi's classification of factors is given in the context of our full distribution method. (C) 1998 John Wiley & Sons, Ltd.