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 Article
Supplemental Material: A Note on Dominating Fractional Factorial Two-Level Designs with Clear Two-Factor Interactions
TL;DR: In this paper, Gromping discusses dominating fractional factorial two-level designs with clear two-factor interactions. But their focus is on the design of fractional Factorial Two-Level Designs with Clear Two-Factor Interactions.
Journal ArticleDOI
A simple method to obtain minimum aberration split-plot designs
TL;DR: In this article, a simple, easy-to-operate approach was proposed by using two ordered sequences of columns from two orthogonal arrays in obtaining minimum aberration split-plot designs for experiments of sizes 16 and 32.
Journal ArticleDOI
General Minimum Lower-Order Confounding Designs with Multi-Block Variables
TL;DR: The present paper considers the blocking problem of multi-block variables, which is an efficient way to reduce the influence of systematic sources on the estimations of treatment effects.
Journal ArticleDOI
Some properties of general minimum lower-order confounding designs
Qi Zhou,Xue Yang,Ziyang Yang +2 more
TL;DR: In this paper, the general minimum lower order confounding (GMC) criterion was proposed to select factorial designs, called GMC designs, and the theory of constructing GMC 2n-m designs with 5N/16+1≤n≤N−1 was studied.
References
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Book
Quality Engineering Using Robust Design
TL;DR: This book offers a complete blueprint for structuring projects to achieve rapid completion with high engineering productivity during the research and development phase to ensure that high quality products can be made quickly and at the lowest possible cost.
Journal ArticleDOI
The graph isomorphism disease
Ronald C. Read,Derek G. Corneil +1 more
TL;DR: The present state of the art of isomorphism testing is surveyed, its relationship to NP-completeness is discussed, and some of the difficulties inherent in this particularly elusive and challenging problem are indicated.
Journal ArticleDOI
Minimum Aberration 2 k–p Designs
Arthur Fries,William G. Hunter +1 more
TL;DR: In this article, the concept of aberration is proposed as a way of selecting the best designs from those with maximum resolution, and algorithms are presented for constructing these minimum aberration designs.
Minimum Aberration 2k-p Designs
Arthur Fries,William G. Hunter +1 more
TL;DR: The concept of resolution was introduced by Box and Hunter as discussed by the authors, who defined the resolution of a two-level fractional factorial design as the length of the shortest word in the defining relation.