Journal ArticleDOI
A graph-aided method for planning two-level experiments when certain interactions are important
Chien-Fu Wu,Youyi Chen +1 more
TLDR
In this paper, a graph-aided method is proposed to solve the problem of fractional factorial factorial experiment planning, where prior knowledge may suggest that some interactions are potentially important and should therefore be estimated free of the main effects.Abstract:
In planning a fractional factorial experiment prior knowledge may suggest that some interactions are potentially important and should therefore be estimated free of the main effects. In this article, we propose a graph-aided method to solve this problem for two-level experiments. First, we choose the defining relations for a 2 n–k design according to a goodness criterion such as the minimum aberration criterion. Then we construct all of the nonisomorphic graphs that represent the solutions to the problem of simultaneous estimation of main effects and two-factor interactions for the given defining relations. In each graph a vertex represents a factor and an edge represents the interaction between the two factors. For the experiment planner, the job is simple: Draw a graph representing the specified interactions and compare it with the list of graphs obtained previously. Our approach is a substantial improvement over Taguchi's linear graphs.read more
Citations
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Journal ArticleDOI
Taguchi's parameter design: a panel discussion
Bovas Abraham,Jock MacKay,George E. P. Box,Raghu N. Kacker,Thomas J. Lorenzen,James M. Lucas,Raymond H. Myers,G. Geoffrey Vining,John A. Nelder,M. S. Phadke,Jerome Sacks,William J. Welch,Anne C. Shoemaker,Kwok L. Tsui,Shin Taguchi,C. F. Jeff Wu,Vijayan N. Nair +16 more
TL;DR: A group of practitioners and researchers discuss the role of parameter design and Taguchi's methodology for implementing it and the importance of parameter-design principles with well-established statistical techniques.
Journal ArticleDOI
An overview of taguchi method and newly developed statistical methods for robust design
TL;DR: In this article, the authors summarized the statistical methods for planning and analyzing robust design experiments originally proposed by Taguchi; then reviewed newly developed statistical methods and identified areas and problems where more researches are needed.
Journal ArticleDOI
A catalogue of two-level and three-level fractional factorial designs with small runs
TL;DR: In this paper, the algebraic structure of fractional factorial (FF) designs with minimum aberration is explored and an algorithm for constructing complete sets of FF designs is proposed.
Proceedings ArticleDOI
Metamodels for simulation input-output relations
TL;DR: A state of the art review of recent developments in metarnodels, which discusses seven alternative modeling strategies that are active topics in the current literature.
Book
A Comprehensive Guide to Factorial Two-Level Experimentation
TL;DR: Fractional Factorial Design Examples: The basics of fractional factorial designs are discussed in detail in this article, where the authors present an analysis of full-factorial experiments with two-level factors.
References
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Journal ArticleDOI
Interaction Graphs: Graphical Aids for Planning Experiments
Raghu N. Kacker,Kwok-Leung Tsui +1 more
TL;DR: Interaction graphs are graphical aids to plan fractional factorial experiments as discussed by the authors, which can be used to generate a plan from an orthogonal array by selecting certain columns of the orthogonality and deleting the rest.