STOCHASTIC MODEL FOR COMMON CAUSE FAILURES AND HUMAN ERROR

Authors

  • V.S.S. Yadavalli Department of Industrial and System Engineering, University of Pretoria
  • A. Bekker Department of Statistics, University of South Africa

DOI:

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

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

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Published

2011-11-05

How to Cite

Yadavalli, V., & Bekker, A. (2011). STOCHASTIC MODEL FOR COMMON CAUSE FAILURES AND HUMAN ERROR. The South African Journal of Industrial Engineering, 16(1). https://doi.org/10.7166/16-1-177

Issue

Vol. 16 No. 1 (2005)

Section

General Articles

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