IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v198y2009i1p210-214.html
   My bibliography  Save this article

A practical approach for reliability prediction of pipeline systems

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(08)00689-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. Yu, Weichao & Wen, Kai & Min, Yuan & He, Lei & Huang, Weihe & Gong, Jing, 2018. "A methodology to quantify the gas supply capacity of natural gas transmission pipeline system using reliability theory," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 128-141.
    4. 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.
    5. 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.
    6. 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.
    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Xiang, Yisha, 2013. "Joint optimization of X¯ control chart and preventive maintenance policies: A discrete-time Markov chain approach," European Journal of Operational Research, Elsevier, vol. 229(2), pages 382-390.
    2. Izquierdo, J. & Márquez, A. Crespo & Uribetxebarria, J. & Erguido, A., 2020. "On the importance of assessing the operational context impact on maintenance management for life cycle cost of wind energy projects," Renewable Energy, Elsevier, vol. 153(C), pages 1100-1110.
    3. Seyed Habib A. Rahmati & Abbas Ahmadi & Kannan Govindan, 2018. "A novel integrated condition-based maintenance and stochastic flexible job shop scheduling problem: simulation-based optimization approach," Annals of Operations Research, Springer, vol. 269(1), pages 583-621, October.
    4. Guo R. & Ascher H. & Love E., 2001. "Towards Practical and Synthetical Modelling of Repairable Systems," Stochastics and Quality Control, De Gruyter, vol. 16(1), pages 147-182, January.
    5. Raouf, BOUCEKKINE & Blanca, MARTINEZ & Cagri, SAGLAM, 2006. "Capital Maintenance Vs Technology Adopton under Embodied Technical Progress," Discussion Papers (ECON - Département des Sciences Economiques) 2006030, Université catholique de Louvain, Département des Sciences Economiques.
    6. Dewan, Isha & Dijoux, Yann, 2015. "Modelling repairable systems with an early life under competing risks and asymmetric virtual age," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 215-224.
    7. Zhengxin Zhang & Xiaosheng Si & Changhua Hu & Xiangyu Kong, 2015. "Degradation modeling–based remaining useful life estimation: A review on approaches for systems with heterogeneity," Journal of Risk and Reliability, , vol. 229(4), pages 343-355, August.
    8. Xiao, Lei & Zhang, Xinghui & Tang, Junxuan & Zhou, Yaqin, 2020. "Joint optimization of opportunistic maintenance and production scheduling considering batch production mode and varying operational conditions," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    9. Jackson, Canek & Pascual, Rodrigo, 2008. "Optimal maintenance service contract negotiation with aging equipment," European Journal of Operational Research, Elsevier, vol. 189(2), pages 387-398, September.
    10. Bebbington, Mark & Lai, Chin-Diew & Zitikis, RiÄ ardas, 2009. "Balancing burn-in and mission times in environments with catastrophic and repairable failures," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1314-1321.
    11. Wang, Ling & Xu, Hong & Yuan, Hua & Zhao, Wenjie & Chen, Xiai, 2015. "Optimizing the re-profiling strategy of metro wheels based on a data-driven wear model," European Journal of Operational Research, Elsevier, vol. 242(3), pages 975-986.
    12. Belyi, Dmitriy & Popova, Elmira & Morton, David P. & Damien, Paul, 2017. "Bayesian failure-rate modeling and preventive maintenance optimization," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1085-1093.
    13. Kurt, Murat & Kharoufeh, Jeffrey P., 2010. "Optimally maintaining a Markovian deteriorating system with limited imperfect repairs," European Journal of Operational Research, Elsevier, vol. 205(2), pages 368-380, September.
    14. Rajiv N Rai & Nomesh Bolia, 2014. "Availability-based optimal maintenance policies for repairable systems in military aviation by identification of dominant failure modes," Journal of Risk and Reliability, , vol. 228(1), pages 52-61, February.
    15. Liu, Yu & Chen, Yiming & Jiang, Tao, 2020. "Dynamic selective maintenance optimization for multi-state systems over a finite horizon: A deep reinforcement learning approach," European Journal of Operational Research, Elsevier, vol. 283(1), pages 166-181.
    16. Flage, Roger, 2014. "A delay time model with imperfect and failure-inducing inspections," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 1-12.
    17. Mitra, Amitava, 2021. "Warranty parameters for extended two-dimensional warranties incorporating consumer preferences," European Journal of Operational Research, Elsevier, vol. 291(2), pages 525-535.
    18. Richard Arnold & Stefanka Chukova & Yu Hayakawa & Sarah Marshall, 2019. "Warranty cost analysis with an alternating geometric process," Journal of Risk and Reliability, , vol. 233(4), pages 698-715, August.
    19. Alaswad, Suzan & Xiang, Yisha, 2017. "A review on condition-based maintenance optimization models for stochastically deteriorating system," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 54-63.
    20. Dai, Anshu & Wang, Xin & Li, Yu & Li, Ting & He, Shuguang, 2023. "Design of a performance-based warranty policy with replacement–repair strategy and cumulative cost threshold," International Journal of Production Economics, Elsevier, vol. 255(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:198:y:2009:i:1:p:210-214. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.