 Piecewise deterministic Markov processes and dynamic reliabilityH Zhang, F Dufour, Y Dutuit and K Gonzalez Journal of Risk and Reliability, 2008, vol. 222, issue 4, 545-551 Abstract: If the reliability community remains interested in dynamic reliability theory, it is not really convinced by the ability of already available approaches to treating current problems from within the operational domain, even if the methodological quality of these approaches is undeniable. This paper is in keeping with two papers presented in earlier conferences. Its aim is to show the potentialities of a method that combines the high modelling capacity of the piecewise-deterministic processes with the great computing power inherent in the Monte Carlo simulation. This method has been applied to a well-known test-case example to test its ability to solve common dynamic reliability problems. Two sets of results have been obtained. The first one has been compared to those coming from a Petri-net model to obtain a preliminary validation of the proposed method. The second one, related to a more complex case, has been compared to already published results found in the literature. Contrary to already existing methods, the approach here is an exact Monte Carlo sampling method; it does not need time-space discretization. Keywords: dynamic reliability; piecewise deterministic Markov processes; Petri nets (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:sae:risrel:v:222:y:2008:i:4:p:545-551 Access Statistics for this article More articles in Journal of Risk and Reliability |
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