Response model analysis for robust design experiments
作者:
Anne C.. Shoemaker,
Kwok-Leung Tsui,
期刊:
Communications in Statistics - Simulation and Computation
(Taylor Available online 1993)
卷期:
Volume 22,
issue 4
页码: 1037-1064
ISSN:0361-0918
年代: 1993
DOI:10.1080/03610919308813141
出版商: Marcel Dekker, Inc.
关键词: Product array;loss model;response model;individual variability measure;CxN interaction plot
数据来源: Taylor
摘要:
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.
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