article

Performance evaluation of subsea BOP control systems using dynamic Bayesian networks with imperfect repair and preventive maintenance

Authors:

Xin DongAuthors Info & Claims

Engineering Applications of Artificial Intelligence, Volume 26, Issue 10

Pages 2661 - 2672

https://doi.org/10.1016/j.engappai.2013.08.011

Published: 01 November 2013 Publication History

Abstract

The work presents a dynamic Bayesian networks (DBN) modeling of series, parallel and 2-out-of-3 (2oo3) voting systems, taking account of common-cause failure, imperfect coverage, imperfect repair and preventive maintenance. Seven basic events of one, two or three component failure are proposed to model the common-cause failure of the three-components-systems. The imperfect coverage is modeled in the conditional probability table by defining a coverage factor. A multi-state degraded component is used to model the imperfect repair and preventive maintenance. Using the proposed method, a DBN modeling of a subsea blowout preventer (BOP) control system is built, and the reliability and availability are evaluated. The mutual information is researched in order to assess the important degree of basic events. The effects of degradation probability, failure rate and mean time to repair (MTTR) on the performances are studied. The results show that the repairs and maintenance can improve the system performance significantly, whereas the imperfect repair cannot degrade the system performance significantly in comparison with the perfect repair, and the preventive maintenance can improve the system performance slightly in comparison with the imperfect repair. In order to improve the performance of subsea BOP control system, the single surface components and the components with all-common-cause failure should given more attention. The influence of degradation probability on the performance is in the order of PLC, PC and ES. The influence of failure rate and MTTR on the performance is in the order of PLC, ES, PC, DO, DI and AI.

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Cited By

Wang JZhou ZNing PLiu SZhou XZhao Y(2023)Inference and analysis of a new evidential reasoning rule-based performance evaluation modelEngineering Applications of Artificial Intelligence10.1016/j.engappai.2022.105789119:COnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.engappai.2022.105789
Wu SLi BZhou YChen MLiu YZhang L(2022)Hybrid Dynamic Bayesian network method for performance analysis of safety barriers considering multi-maintenance strategiesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2021.104624109:COnline publication date: 23-May-2022
https://dl.acm.org/doi/10.1016/j.engappai.2021.104624
Qin JLi ZZhu Y(2021)Protection Mechanism in Reliability Evaluation Approach to Multistate System with Common Cause FailureComplexity10.1155/2021/66913622021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6691362
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Performance evaluation of subsea BOP control systems using dynamic Bayesian networks with imperfect repair and preventive maintenance
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis

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cover image Engineering Applications of Artificial Intelligence

Engineering Applications of Artificial Intelligence Volume 26, Issue 10

November, 2013

430 pages

ISSN:0952-1976

Issue’s Table of Contents

Copyright © Elsevier Ltd © 2013.

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Pergamon Press, Inc.

United States

Publication History

Published: 01 November 2013

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Cited By

Wang JZhou ZNing PLiu SZhou XZhao Y(2023)Inference and analysis of a new evidential reasoning rule-based performance evaluation modelEngineering Applications of Artificial Intelligence10.1016/j.engappai.2022.105789119:COnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.engappai.2022.105789
Wu SLi BZhou YChen MLiu YZhang L(2022)Hybrid Dynamic Bayesian network method for performance analysis of safety barriers considering multi-maintenance strategiesEngineering Applications of Artificial Intelligence10.1016/j.engappai.2021.104624109:COnline publication date: 23-May-2022
https://dl.acm.org/doi/10.1016/j.engappai.2021.104624
Qin JLi ZZhu Y(2021)Protection Mechanism in Reliability Evaluation Approach to Multistate System with Common Cause FailureComplexity10.1155/2021/66913622021Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1155/2021/6691362
El Afia ASarhani MLazaar MTabii YChrayah MAl Achhab M(2017)Particle Swarm Optimization for Model Selection of Aircraft Maintenance Predictive ModelsProceedings of the 2nd international Conference on Big Data, Cloud and Applications10.1145/3090354.3090402(1-12)Online publication date: 29-Mar-2017
https://dl.acm.org/doi/10.1145/3090354.3090402

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