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
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Note
- thesisPartial requirement for: Ph.D., Arizona State University, 2013
- bibliographyIncludes bibliographical references (p. 177-183)
- Field of study: Industrial engineering
Citation and reuse
Statement of Responsibility
by Brian Stone