STOCHASTIC MODEL FOR COMMON CAUSE FAILURES AND HUMAN ERROR

V.S.S. Yadavalli, A. Bekker

Abstract


ENGLISH ABSTRACT: A consistent asymptotic normal (CAN) estimator and confidence limits for the steady-state availability of series and parallel systems subject to unit failures, common-cause shock (CCS) failures and human error are studied. This paper also deals with the estimation from a Bayesian viewpoint with a number of prior distributions assumed for the unknown parameters in the system, which reflect different degrees of belief on the failure mechanisms. A Monte Carlo simulation is used to derive the posterior distribution for the steady-state availability and subsequently the highest posterior density (HPD) intervals. A numerical example illustrates the results.

AFRIKAANSE OPSOMMING: 'n Konsekwente asimptotiese normaalberamer en vertroueintervalle vir die ewewigstoestandsbeskikbaarheid van stelsels in serie en parallel, wat onderworpe is aan eenheids-, gemeenskaplike skok- en menslike foutfalings, word bestudeer. In die artikel word ook 'n Bayes-benadering gevolg vir die beraming deur 'n aantal a priori-verdelings vir die onbekende parameters in die stelsel, wat verskillende grade van vertroue in die falingsmeganismes weerspie, te aanvaar. Monte Carlo-simulasie word gebruik om die a posteriori-verdeling vir die ewewigstoestandsbeskikbaarheid en daarna die hoogste a posteriori-digtheidsintervalle (HPD) af te lei. 'n Numeriese voorbeeld illustreer die resultate.


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DOI: https://doi.org/10.7166/16-1-177

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