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Abstract
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.
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