IEEE Transactions on Reliability · 2013 · 64 citations · 43 references
ComputingSystems EngineeringDecision TheoryStochastic ModelingUncertainty QuantificationProbabilistic ModelingReliabilityReliability ModelingUncertainty AnalysisUncertainty EstimationUncertainty RepresentationBelief FunctionsEpistemic UncertaintyInterval ArithmeticMultistate Reliability ModelsProbabilistic Reliability AnalysisProbabilistic Reliability AssessmentSystem ReliabilitySystem Reliability Assessment
Many practical methods and different approaches have been proposed to assess Multi-State Systems (MSS) reliability measures. The universal generating function (UGF) method, introduced in 1986, is known to be a very efficient way of evaluating the availability of different types of MSSs. In this paper, we propose an extension of the UGF method considering epistemic uncertainties. This extended method allows one to model ill-known probabilities and transition rates, or to model both aleatory and epistemic uncertainty in a single model. It is based on the use of belief functions which are general models of uncertainty. We also compare this extension with UGF methods based on interval arithmetic operations performed on probabilistic bounds.
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Emad El-Neweihi, Frank Proschan, Jayaram Sethuraman · Journal of Applied Probability · 1978 · 350 citations