The motivation for this dissertation is the resolution of a long-standing practical problem in reliability engineering, namely that of tracking reliability growth. The dissertation's essential output is the development of a coherent framework for casting the reliability growth problem as one of filtering, prediction, and tracking. This constitutes a paradigm shift in how reliability is monitored, namely as a dynamic system. The two by-products of this dissertation are: a probabilistic competing risk model and a reconsideration of the foundations of reliability via Popper's notion of propensity.
Some files may require a special program or browser plug-in. More Information
|Advisor:||Singpurwalla, Nozer D.|
|Commitee:||Bose, Sudip, Bura, Efstathia, Cohen, Michael, Nayak, Tapan K.|
|School:||The George Washington University|
|School Location:||United States -- District of Columbia|
|Source:||DAI-B 73/05, Dissertation Abstracts International|
|Subjects:||Epistemology, Statistics, Engineering|
|Keywords:||Competing risk, Filtering reliability, Kalman filter, Propensity, Reliability growth, Tracking survivability|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be