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A practical approach for reliability prediction of pipeline systems

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  • Sun, Yong
  • Ma, Lin
  • Morris, Jon

Abstract

Pipelines play an important role in the modern society. Failures of pipelines can have great impacts on economy, environment and community. Preventive maintenance (PM) is often conducted to improve the reliability of pipelines. Modern asset management practice requires accurate predictability of the reliability of pipelines with multiple PM actions, especially when these PM actions involve imperfect repairs. To address this issue, a split system approach (SSA) based model is developed in this paper through an industrial case study. This new model enables maintenance personnel to predict the reliability of pipelines with different PM strategies and hence effectively assists them in making optimal PM decisions.

Suggested Citation

  • Sun, Yong & Ma, Lin & Morris, Jon, 2009. "A practical approach for reliability prediction of pipeline systems," European Journal of Operational Research, Elsevier, vol. 198(1), pages 210-214, October.
    • Handle: RePEc:eee:ejores:v:198:y:2009:i:1:p:210-214
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    References listed on IDEAS

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    1. Maes, M.A. & Dann, M. & Salama, M.M., 2008. "Influence of grade on the reliability of corroding pipelines," Reliability Engineering and System Safety, Elsevier, vol. 93(3), pages 447-455.
    2. Pham, Hoang & Wang, Hongzhou, 1996. "Imperfect maintenance," European Journal of Operational Research, Elsevier, vol. 94(3), pages 425-438, November.
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    Cited by:

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    2. ValinÄ ius, Mindaugas & ŽutautaitÄ—, Inga & Dundulis, Gintautas & RimkeviÄ ius, Sigitas & Janulionis, Remigijus & Bakas, Rimantas, 2015. "Integrated assessment of failure probability of the district heating network," Reliability Engineering and System Safety, Elsevier, vol. 133(C), pages 314-322.
    3. Xuejie Li & Yuan Xue & Yuxing Li & Qingshan Feng, 2022. "An Optimization Method for a Compressor Standby Scheme Based on Reliability Analysis," Energies, MDPI, vol. 15(21), pages 1-16, November.
    4. Rimkevicius, Sigitas & Kaliatka, Algirdas & Valincius, Mindaugas & Dundulis, Gintautas & Janulionis, Remigijus & Grybenas, Albertas & Zutautaite, Inga, 2012. "Development of approach for reliability assessment of pipeline network systems," Applied Energy, Elsevier, vol. 94(C), pages 22-33.
    5. Kraus, Mathias & Feuerriegel, Stefan & Oztekin, Asil, 2020. "Deep learning in business analytics and operations research: Models, applications and managerial implications," European Journal of Operational Research, Elsevier, vol. 281(3), pages 628-641.
    6. Dundulis, Gintautas & ŽutautaitÄ—, Inga & Janulionis, Remigijus & UÅ¡puras, Eugenijus & RimkeviÄ ius, Sigitas & Eid, Mohamed, 2016. "Integrated failure probability estimation based on structural integrity analysis and failure data: Natural gas pipeline case," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 195-202.
    7. Mortensen, Lasse Kappel & Shaker, Hamid Reza & Veje, Christian T., 2022. "Relative fault vulnerability prediction for energy distribution networks," Applied Energy, Elsevier, vol. 322(C).

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