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Abstract:
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Assessing the reliability of a complex system involves many challenges. One of the more difficult aspects of system reliability assessment is integrating multiple sources of information, including component, subsystem, and full-system data, as well as possible previous test data or subject-matter expert opinion. The Bayesian paradigm is tailor-made for these types of situations, allowing for the combination of multiple sources of data and variability in order to obtain more robust reliability estimates and uncertainty quantification. Approaches for system reliability assessments under this paradigm are illustrated with examples from operational testing of Department of Defense systems.
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