Statistical Science

Parameter design for signal-response systems: a different look at Taguchi's dynamic parameter design

Arden Miller and C.F.J. Wu

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A recent trend in the industrial applications of robust parameter design is to consider complex systems which are called "systems with dynamic characteristics" in Taguchi's terminology or signal-response systems in this paper. This potentially important tool in quality engineering lacks a solid basis on which to build a rigorous body of theory and methodology. The purpose of this paper is to provide such a basis. We classify signal-response systems into two broad types: measurement systems and multiple target systems. Three issues are then of fundamental importance. First, a proper performance measure needs to be chosen for system optimization, and this choice depends on the type of system. Taguchi's dynamic signal-to-noise ratio is shown to be appropriate for certain measurement systems but not for multiple target systems. Second, there are two strategies for modeling and analyzing data: performance measure modeling and response function modeling. Finally, the proper design of such experiments should take into account the modeling and analysis strategy. The proposed methodology is illustrated with a real experiment on injection molding.

Article information

Statist. Sci., Volume 11, Number 2 (1996), 122-136.

First available in Project Euclid: 27 November 2002

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Dynamic SN ratio measurement systems multiple target systems robust parameter design performance measures response function modeling


Miller, Arden; Wu, C.F.J. Parameter design for signal-response systems: a different look at Taguchi's dynamic parameter design. Statist. Sci. 11 (1996), no. 2, 122--136. doi:10.1214/ss/1038425656.

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