| Abstract: | Statistical experimental design has been used in ‘off-line’ quality control to determine the optimal settings for a system even when the mathematical model is known. Taguchi demonstrated how signal-to-noise ratios could be used to improve the performance of a system through variance minimization. However, these statistical methods often do not use the full distribution information that may be available. Proposed in this paper is an extension and complement to Taguchi's use of experimental design and signal-to-noise ratios for known system models. The use of a probability transformation method with the mathematical system model will allow designers to perform parameter and tolerance design simultaneously 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 components of any distribution type, with or without correlation of the variables. In addition, an interpretation of Taguchi's classification of factors is given in the context of our full distribution method. © 1998 John Wiley & Sons, Ltd. |
