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Optimization of a subsea production system for cost and reliability using its fault tree model

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  • Bhattacharyya, S.K.
  • Cheliyan, A.S.

Abstract

A method of optimizing the cost and reliability of a system represented by a fault tree is proposed which is useful in choosing the technology options for basic events that are available to the system designer. The problem of optimization is to minimize the overall system cost by exercising technology choices that will yield a prescribed probability of failure of the top event of the system. The well known non-dominated sorting genetic algorithm (NSGA-II) has been used for optimization. Both single and two objective optimization problems have been explored and their numerical convergence features discussed. The application problem treated is one of leakage in a subsea production system.

Suggested Citation

  • Bhattacharyya, S.K. & Cheliyan, A.S., 2019. "Optimization of a subsea production system for cost and reliability using its fault tree model," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 213-219.
    • Handle: RePEc:eee:reensy:v:185:y:2019:i:c:p:213-219
    DOI: 10.1016/j.ress.2018.12.030
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    References listed on IDEAS

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    1. Jelena Riauke & Lisa Bartlett, 2009. "Safety system design optimisation using a multi-objective genetic algorithm," International Journal of Reliability and Safety, Inderscience Enterprises Ltd, vol. 3(4), pages 397-412.
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    Cited by:

    1. Ding, Rui & Liu, Zehua & Xu, Jintao & Meng, Fanpeng & Sui, Yang & Men, Xinhong, 2021. "A novel approach for reliability assessment of residual heat removal system for HPR1000 based on failure mode and effect analysis, fault tree analysis, and fuzzy Bayesian network methods," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    2. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C., 2022. "Bayesian framework for reliability prediction of subsea processing systems accounting for influencing factors uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    3. Han, Zhong & Tian, Liting & Cheng, Lin, 2021. "A deducing-based reliability optimization for electrical equipment with constant failure rate components duration their mission profile," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    4. Silva, L.M.R. & Guedes Soares, C., 2023. "Robust optimization model of an offshore oil production system for cost and pipeline risk of failure," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    5. Tang, Ming & Liao, Huchang, 2021. "Failure mode and effect analysis considering the fairness-oriented consensus of a large group with core-periphery structure," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Huang, Chao & Li, Liang, 2020. "Architectural design and analysis of a steer-by-wire system in view of functional safety concept," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    7. Yufang Li & Honglin Zhao & Ning Xu & Xiaoyu Wang & Deguo Wang, 2020. "Study of the Installation Process of the Subsea Tree Passed Through the Splash Zone," Energies, MDPI, vol. 13(5), pages 1-14, February.
    8. Huang, Jia & You, Jian-Xin & Liu, Hu-Chen & Song, Ming-Shun, 2020. "Failure mode and effect analysis improvement: A systematic literature review and future research agenda," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    9. Kai Pan & Hui Liu & Xiaoqing Gou & Rui Huang & Dong Ye & Haining Wang & Adam Glowacz & Jie Kong, 2022. "Towards a Systematic Description of Fault Tree Analysis Studies Using Informetric Mapping," Sustainability, MDPI, vol. 14(18), pages 1-28, September.

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