Description
Nonregular screening designs can be an economical alternative to traditional resolution IV 2^(k-p) fractional factorials. Recently 16-run nonregular designs, referred to as no-confounding designs, were introduced in the literature. These designs have the property that no pair of main effect (ME) and two-factor interaction (2FI) estimates are completely confounded. In this dissertation, orthogonal arrays were evaluated with many popular design-ranking criteria in order to identify optimal 20-run and 24-run no-confounding designs. Monte Carlo simulation was used to empirically assess the model fitting effectiveness of the recommended no-confounding designs. The results of the simulation demonstrated that these new designs, particularly the 24-run designs, are successful at detecting active effects over 95% of the time given sufficient model effect sparsity. The final chapter presents a screening design selection methodology, based on decision trees, to aid in the selection of a screening design from a list of published options. The methodology determines which of a candidate set of screening designs has the lowest expected experimental cost.
Details
Title
- No-confounding designs of 20 and 24 runs for screening experiments and a design selection methodology
Contributors
- Stone, Brian (Author)
- Montgomery, Douglas C. (Thesis advisor)
- Silvestrini, Rachel T. (Committee member)
- Fowler, John W (Committee member)
- Borror, Connie M. (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2013
Subjects
Resource Type
Collections this item is in
Note
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thesisPartial requirement for: Ph.D., Arizona State University, 2013
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bibliographyIncludes bibliographical references (p. 177-183)
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Field of study: Industrial engineering
Citation and reuse
Statement of Responsibility
by Brian Stone