abstract: 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. / Dissertation/Thesis / Ph.D. Industrial Engineering 2013
| Identifer | oai:union.ndltd.org:asu.edu/item:18754 |
| Date | January 2013 |
| Contributors | Stone, Brian B. (Author), Montgomery, Douglas C (Advisor), Silvestrini, Rachel T (Committee member), Fowler, John W (Committee member), Borror, Connie M (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Doctoral Dissertation |
| Format | 219 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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