Most of the literature concerning robust parameter design (RPD), a methodology introduced by Taguchi (1986), involves situations where the quality characteristic of interest (response) is a single quantity which has a specified optimal value. A recent trend in the industrial applications of RPD consists in consider complex systems which are called "systems with dynamic characteristics" or "dynamic systems", in Taguchi's terminology, or "signal-response systems", in this paper. Recently, modeling and analysis methods for the dynamic system have been developed. In this paper, three modeling approaches are compared by use of a real example: Performance Measure Modeling (PMM), Response Modeling (RM) and Response Function Modeling (RFM). It is shown that the RFM approach allows greater flexibility to investigate factor effects for the RPD experiment.
Robust parameter design; signal-response systems; signal-noise ratio
