Full metadata
Title
Design of Experiments and Reliability Growth on Repairable Systems
Description
Reliability growth is not a new topic in either engineering or statistics and has been a major focus for the past few decades. The increasing level of high-tech complex systems and interconnected components and systems implies that reliability problems will continue to exist and may require more complex solutions. The most heavily used experimental designs in assessing and predicting a systems reliability are the "classical designs", such as full factorial designs, fractional factorial designs, and Latin square designs. They are so heavily used because they are optimal in their own right and have served superbly well in providing efficient insight into the underlying structure of industrial processes. However, cases do arise when the classical designs do not cover a particular practical situation. Repairable systems are such a case in that they usually have limitations on the maximum number of runs or too many varying levels for factors. This research explores the D-optimal design criteria as it applies to the Poisson Regression model on repairable systems, with a number of independent variables and under varying assumptions, to include the total time tested at a specific design point with fixed parameters, the use of a Bayesian approach with unknown parameters, and how the design region affects the optimal design. In applying experimental design to these complex repairable systems, one may discover interactions between stressors and provide better failure data. Our novel approach of accounting for time and the design space in the early stages of testing of repairable systems should, theoretically, in the final engineering design improve the system's reliability, maintainability and availability.
Date Created
2023
Contributors
- TAYLOR, DUSTIN (Author)
- Montgomery, Douglas (Thesis advisor)
- Pan, Rong (Thesis advisor)
- Rigdon, Steve (Committee member)
- Freeman, Laura (Committee member)
- Iquebal, Ashif (Committee member)
- Arizona State University (Publisher)
Topical Subject
Resource Type
Extent
98 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Handle
https://hdl.handle.net/2286/R.2.N.189289
Level of coding
minimal
Cataloging Standards
Note
Partial requirement for: Ph.D., Arizona State University, 2023
Field of study: Industrial Engineering
System Created
- 2023-08-28 04:59:08
System Modified
- 2023-08-28 04:59:12
- 1 year 2 months ago
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