Importance measure of probabilistic common cause failures under system hybrid uncertainty based on Bayesian network

verfasst von

Jinhua Mi, Yan-Feng Li, Michael Beer, Matteo Broggi, Yuhua Cheng

Abstract

When dealing with modern complex systems, the relationship existing between components can lead to the appearance of various dependencies between component failures, where multiple items of the system fail simultaneously in unpredictable fashions. These probabilistic common cause failures affect greatly the performance of these critical systems. In this paper a novel methodology is developed to quantify the importance of common cause failures when hybrid uncertainties are presented in systems. First, the probabilistic common cause failures are modeled with Bayesian networks and are incorporated into the system exploiting the α factor model. Then, probability-boxes (bound analysis method) are introduced to model the hybrid uncertainties and quantify the effect of uncertainties on system reliability. Furthermore, an extended Birnbaum importance measure is defined to identify the critical common cause failure events and coupling impact factors when uncertainties are expressed by probability-boxes. Finally, the effectiveness of the method is demonstrated through a numerical example.

Organisationseinheit(en)

Institut für Risiko und Zuverlässigkeit

Externe Organisation(en)

University of Electronic Science and Technology of China

Typ

Artikel

Journal

Eksploatacja i Niezawodnosc

Band

22

Seiten

112-120

Anzahl der Seiten

9

ISSN

1507-2711

Publikationsdatum

2020

Publikationsstatus

Veröffentlicht

Peer-reviewed

Ja

ASJC Scopus Sachgebiete

Sicherheit, Risiko, Zuverlässigkeit und Qualität, Wirtschaftsingenieurwesen und Fertigungstechnik

Elektronische Version(en)

https://doi.org/10.17531/ein.2020.1.13 (Zugang: Geschlossen)