Details
| Original language | English |
|---|---|
| Article number | 106988 |
| Journal | Reliability engineering & system safety |
| Volume | 201 |
| Early online date | 8 May 2020 |
| Publication status | Published - Sept 2020 |
Abstract
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.
Keywords
- Common cause failure, Dual-axis pointing mechanism, Epistemic uncertainty, Hierarchical Bayesian inference, Reliability analysis, Survival signature
ASJC Scopus subject areas
- Engineering(all)
- Safety, Risk, Reliability and Quality
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Reliability engineering & system safety, Vol. 201, 106988, 09.2020.
Research output: Contribution to journal › Article › Research › peer review
}
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 -