TY - JOUR

T1 - Reliability and importance analysis of uncertain system with common cause failures based on survival signature

AU - Mi, Jinhua

AU - Beer, Michael

AU - Li, Yan-Feng

AU - Broggi, Matteo

AU - Cheng, Yuhua

N1 - Funding information: This work was partially supported by the National Natural Science Foundation of China under contract No. 51805073 and U1830207 , the Chinese Universities Scientific Fund under contract No. ZYGX2018J061, and the China Postdoctoral Science Foundation under contract No. 2015M582536 . Jinhua Mi wishes to acknowledge the financial support of the China Scholarship Council.

PY - 2020/9

Y1 - 2020/9

N2 - Redundant design has become the commonly used technique for ensuring the reliability of complex systems, which calls for great concern to common cause failure problems in such systems. Incomplete data in combination with vague judgments from experts introduce imprecision and epistemic uncertainties in the performance characterization of components. These issues need to be taken into account for assessing the system reliability. In this paper, a comprehensive reliability assessment method is presented by adopting the concept of survival signature to estimate the reliability of complex systems with multiple types of components. Particular attention is devoted to common cause failures (CCFs), which are modeled and quantified by decomposed partial α-decomposition method. Uncertainties caused by incomplete data for CCF events are reduced by hierarchical Bayesian inference. The component importance measure is enhanced to assess the importance of various possible CCF scenarios and to identify their potential impact on system reliability. The presented method is used to analyze the reliability of a dual-axis pointing mechanism for communication satellite, which is a commonly used satellite antenna control mechanism. The engineering application demonstrates the effectiveness of the method.

AB - Redundant design has become the commonly used technique for ensuring the reliability of complex systems, which calls for great concern to common cause failure problems in such systems. Incomplete data in combination with vague judgments from experts introduce imprecision and epistemic uncertainties in the performance characterization of components. These issues need to be taken into account for assessing the system reliability. In this paper, a comprehensive reliability assessment method is presented by adopting the concept of survival signature to estimate the reliability of complex systems with multiple types of components. Particular attention is devoted to common cause failures (CCFs), which are modeled and quantified by decomposed partial α-decomposition method. Uncertainties caused by incomplete data for CCF events are reduced by hierarchical Bayesian inference. The component importance measure is enhanced to assess the importance of various possible CCF scenarios and to identify their potential impact on system reliability. The presented method is used to analyze the reliability of a dual-axis pointing mechanism for communication satellite, which is a commonly used satellite antenna control mechanism. The engineering application demonstrates the effectiveness of the method.

KW - Common cause failure

KW - Dual-axis pointing mechanism

KW - Epistemic uncertainty

KW - Hierarchical Bayesian inference

KW - Reliability analysis

KW - Survival signature

UR - http://www.scopus.com/inward/record.url?scp=85085249185&partnerID=8YFLogxK

U2 - 10.1016/j.ress.2020.106988

DO - 10.1016/j.ress.2020.106988

M3 - Article

AN - SCOPUS:85085249185

VL - 201

JO - Reliability engineering & system safety

JF - Reliability engineering & system safety

SN - 0951-8320

M1 - 106988

ER -