Analysis of cascading probabilistic common cause failures
Common cause failures may contribute significantly to the reliability of a system and has attracted considerable research attentions. However, the existing models often assumed deterministic failures of components affected by the common cause (CC) and no cascading effects. This paper contributes by...
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| Published in | Quality and reliability engineering international Vol. 39; no. 6; pp. 2476 - 2495 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
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Bognor Regis
Wiley Subscription Services, Inc
01.10.2023
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| Online Access | Get full text |
| ISSN | 0748-8017 1099-1638 |
| DOI | 10.1002/qre.3357 |
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| Abstract | Common cause failures may contribute significantly to the reliability of a system and has attracted considerable research attentions. However, the existing models often assumed deterministic failures of components affected by the common cause (CC) and no cascading effects. This paper contributes by modeling cascading probabilistic common cause failures (CPCCFs), where a CC may cause multiple system components to fail with different probabilities and some components may fail in a domino chain manner. An explicit, analytical method is proposed for the reliability analysis of systems subject to CPCCFs, which may be triggered by external or internal CCs. The complex cascading effects are modeled using a directed acyclic graph structure. The proposed method has no limitation on the component time‐to‐failure distributions. Applications and advantages of the proposed method are illustrated through a detailed case study of a safety instrumented system for oil and gas transportation. Correctness of the proposed method is verified by Monte Carlo simulations. The time and space complexity of the method is also studied. |
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| AbstractList | Common cause failures may contribute significantly to the reliability of a system and has attracted considerable research attentions. However, the existing models often assumed deterministic failures of components affected by the common cause (CC) and no cascading effects. This paper contributes by modeling cascading probabilistic common cause failures (CPCCFs), where a CC may cause multiple system components to fail with different probabilities and some components may fail in a domino chain manner. An explicit, analytical method is proposed for the reliability analysis of systems subject to CPCCFs, which may be triggered by external or internal CCs. The complex cascading effects are modeled using a directed acyclic graph structure. The proposed method has no limitation on the component time‐to‐failure distributions. Applications and advantages of the proposed method are illustrated through a detailed case study of a safety instrumented system for oil and gas transportation. Correctness of the proposed method is verified by Monte Carlo simulations. The time and space complexity of the method is also studied. |
| Author | Xing, Liudong Guan, Quanlong Wang, Chaonan Yang, Chunhui Lie, Yingxi Yu, Min |
| Author_xml | – sequence: 1 givenname: Chaonan surname: Wang fullname: Wang, Chaonan organization: College of Information Science and Technology Jinan University Guangzhou China, Guangdong Key Laboratory of Data Security and Privacy Preserving Guangzhou China – sequence: 2 givenname: Yingxi surname: Lie fullname: Lie, Yingxi organization: College of Information Science and Technology Jinan University Guangzhou China – sequence: 3 givenname: Liudong orcidid: 0000-0003-1606-1644 surname: Xing fullname: Xing, Liudong organization: Electrical & Computer Engineering Department University of Massachusetts Dartmouth USA – sequence: 4 givenname: Quanlong surname: Guan fullname: Guan, Quanlong organization: College of Information Science and Technology Jinan University Guangzhou China – sequence: 5 givenname: Chunhui surname: Yang fullname: Yang, Chunhui organization: China Electronic Product Reliability & Environmental Testing Research Institute Guangzhou China – sequence: 6 givenname: Min surname: Yu fullname: Yu, Min organization: China Electronic Product Reliability & Environmental Testing Research Institute Guangzhou China |
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| Title | Analysis of cascading probabilistic common cause failures |
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