Bayesian reliability models of Weibull systems: State of the art

Abdelaziz Zaidi; Belkacem Ould Bouamama; Moncef Tagina

International Journal of Applied Mathematics and Computer Science (2012)

  • Volume: 22, Issue: 3, page 585-600
  • ISSN: 1641-876X

Abstract

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In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the use of fault trees and reliability diagrams is not possible. To overcome this problem, Bayesian approaches offer a considerable efficiency in this context. This paper introduces recent contributions in the field of reliability modeling with the Bayesian network approach. Bayesian reliability models are applied to systems with Weibull distribution of failure. To achieve the formulation of the reliability model, Bayesian estimation of Weibull parameters and the model's goodness-of-fit are evoked. The advantages of this modelling approach are presented in the case of systems with an unknown reliability structure, those with a common cause of failures and redundant ones. Finally, we raise the issue of the use of BNs in the fault diagnosis area.

How to cite

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Abdelaziz Zaidi, Belkacem Ould Bouamama, and Moncef Tagina. "Bayesian reliability models of Weibull systems: State of the art." International Journal of Applied Mathematics and Computer Science 22.3 (2012): 585-600. <http://eudml.org/doc/244063>.

@article{AbdelazizZaidi2012,
abstract = {In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the use of fault trees and reliability diagrams is not possible. To overcome this problem, Bayesian approaches offer a considerable efficiency in this context. This paper introduces recent contributions in the field of reliability modeling with the Bayesian network approach. Bayesian reliability models are applied to systems with Weibull distribution of failure. To achieve the formulation of the reliability model, Bayesian estimation of Weibull parameters and the model's goodness-of-fit are evoked. The advantages of this modelling approach are presented in the case of systems with an unknown reliability structure, those with a common cause of failures and redundant ones. Finally, we raise the issue of the use of BNs in the fault diagnosis area.},
author = {Abdelaziz Zaidi, Belkacem Ould Bouamama, Moncef Tagina},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {hierarchical modeling; reliability; Weibull; Bayesian networks; fault diagnosis; Weibull distributions},
language = {eng},
number = {3},
pages = {585-600},
title = {Bayesian reliability models of Weibull systems: State of the art},
url = {http://eudml.org/doc/244063},
volume = {22},
year = {2012},
}

TY - JOUR
AU - Abdelaziz Zaidi
AU - Belkacem Ould Bouamama
AU - Moncef Tagina
TI - Bayesian reliability models of Weibull systems: State of the art
JO - International Journal of Applied Mathematics and Computer Science
PY - 2012
VL - 22
IS - 3
SP - 585
EP - 600
AB - In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the use of fault trees and reliability diagrams is not possible. To overcome this problem, Bayesian approaches offer a considerable efficiency in this context. This paper introduces recent contributions in the field of reliability modeling with the Bayesian network approach. Bayesian reliability models are applied to systems with Weibull distribution of failure. To achieve the formulation of the reliability model, Bayesian estimation of Weibull parameters and the model's goodness-of-fit are evoked. The advantages of this modelling approach are presented in the case of systems with an unknown reliability structure, those with a common cause of failures and redundant ones. Finally, we raise the issue of the use of BNs in the fault diagnosis area.
LA - eng
KW - hierarchical modeling; reliability; Weibull; Bayesian networks; fault diagnosis; Weibull distributions
UR - http://eudml.org/doc/244063
ER -

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