Response model analysis for robust design experiments

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

25 Scopus Citations
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Author(s)

  • Kwok-Leung Tsui

Detail(s)

Original languageEnglish
Pages (from-to)1037-1064
Journal / PublicationCommunications in Statistics - Simulation and Computation
Volume22
Issue number4
Publication statusPublished - 1 Jan 1993
Externally publishedYes

Abstract

Taguchi’s robust design technique, also known as parameter design, focuses on making product and process designs insensitive (i.e., robust) to hard-to-control variations. In some applications, however, his approach of modeling expected loss and the resulting “product array” experimental format leads to unnecessarily expensive and less informative experiments. The response model approach to robust design proposed by Welch, Ku, Yang, and Sacks (1990), Box and Jones (1990), Lucas (1989), and Shoemaker, Tsui and Wu (1991) offers more flexibility and economy in experiment planning and more informative modeling. This paper develops a formal basis for the graphical data-analytic approach presented in Shoemaker et al. In particular, we decompose overall response variation into components representing the variability contributed by each noise factor, and show when this decomposition allows us to use individual control-by-noise interaction plots to minimize response variation. We then generalize the control-by-noise interaction plots to extend their usefulness, and develop a formal analysis strategy using these plots to minimize response variation. © 1993, Taylor & Francis Group, LLC. All rights reserved.

Research Area(s)

  • and Phrases, CxN interaction plot, individual variability measure, loss model, Product array, response model

Citation Format(s)

Response model analysis for robust design experiments. / Tsui, Kwok-Leung.
In: Communications in Statistics - Simulation and Computation, Vol. 22, No. 4, 01.01.1993, p. 1037-1064.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review