IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v236y2022i2p339-347.html
   My bibliography  Save this article

Optimal inspection and replacement strategy for 145 kV gas-insulated switchgear

Author

Listed:
  • Young Jin Han
  • Qian Qian Zhao
  • Won Young Yun

Abstract

We deal with an optimization problem of planning a maintenance strategy for 145 kV gas-insulated switchgear and apply reliability-centered maintenance approach to find an efficient and effective strategy. In a three-step sequential process, we use failure mode effects and criticality analysis to define the critical failure modes that cause the major failures of 145 kV gas-insulated switchgear, select the maintenance significant items to remove the major failure modes, and finally apply logic tree analysis to assign the appropriate maintenance task to each critical failure modes in the system. We then compare the assigned maintenance tasks with existing tasks in the installation, operation, and maintenance manuals developed in the system design and development phase. The assigned maintenance tasks in this study are compared with those in the system design and development phase by simulation, and a simple heuristic method is proposed to find optimal solutions.

Suggested Citation

  • Young Jin Han & Qian Qian Zhao & Won Young Yun, 2022. "Optimal inspection and replacement strategy for 145 kV gas-insulated switchgear," Journal of Risk and Reliability, , vol. 236(2), pages 339-347, April.
    • Handle: RePEc:sae:risrel:v:236:y:2022:i:2:p:339-347
    DOI: 10.1177/1748006X19893540
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X19893540
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1748006X19893540?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Xiao Liu & Jingrui Li & Khalifa Al-Khalifa & Abdelmagid Hamouda & David Coit & Elsayed Elsayed, 2013. "Condition-based maintenance for continuously monitored degrading systems with multiple failure modes," IISE Transactions, Taylor & Francis Journals, vol. 45(4), pages 422-435.
    3. Sovacool, Benjamin K. & Kryman, Matthew & Laine, Emily, 2015. "Profiling technological failure and disaster in the energy sector: A comparative analysis of historical energy accidents," Energy, Elsevier, vol. 90(P2), pages 2016-2027.
    4. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    5. Tian, Zhigang & Liao, Haitao, 2011. "Condition based maintenance optimization for multi-component systems using proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 581-589.
    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. Lirong Cui & David W Coit, 2022. "Guest Editorial: SMRLO-2019 Special Issue," Journal of Risk and Reliability, , vol. 236(2), pages 223-224, April.

    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. Liu, Xingchen & Sun, Qiuzhuang & Ye, Zhi-Sheng & Yildirim, Murat, 2021. "Optimal multi-type inspection policy for systems with imperfect online monitoring," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    2. Ece Zeliha Demirci & Joachim Arts & Geert-Jan Van Houtum, 2022. "A restless bandit approach for capacitated condition based maintenance scheduling," DEM Discussion Paper Series 22-01, Department of Economics at the University of Luxembourg.
    3. Azizi, Fariba & Salari, Nooshin, 2023. "A novel condition-based maintenance framework for parallel manufacturing systems based on bivariate birth/birth–death processes," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    4. KarabaÄŸ, Oktay & Eruguz, Ayse Sena & Basten, Rob, 2020. "Integrated optimization of maintenance interventions and spare part selection for a partially observable multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 200(C).
    5. Liu, Xinbao & Yang, Tianji & Pei, Jun & Liao, Haitao & Pohl, Edward A., 2019. "Replacement and inventory control for a multi-customer product service system with decreasing replacement costs," European Journal of Operational Research, Elsevier, vol. 273(2), pages 561-574.
    6. Vega, Manuel A. & Hu, Zhen & Todd, Michael D., 2020. "Optimal maintenance decisions for deteriorating quoin blocks in miter gates subject to uncertainty in the condition rating protocol," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    7. Kampitsis, Dimitris & Panagiotidou, Sofia, 2022. "A Bayesian condition-based maintenance and monitoring policy with variable sampling intervals," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    8. 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.
    9. Huynh, K.T., 2021. "An adaptive predictive maintenance model for repairable deteriorating systems using inverse Gaussian degradation process," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    10. Toon Vanderschueren & Robert Boute & Tim Verdonck & Bart Baesens & Wouter Verbeke, 2022. "Prescriptive maintenance with causal machine learning," Papers 2206.01562, arXiv.org.
    11. Wang, Liying & Song, Yushuang & Zhang, Wenhua & Ling, Xiaoliang, 2023. "Condition-based inspection, component reallocation and replacement optimization of two-component interchangeable series system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    12. Uit Het Broek, Michiel A.J. & Teunter, Ruud H. & de Jonge, Bram & Veldman, Jasper, 2021. "Joint condition-based maintenance and load-sharing optimization for two-unit systems with economic dependency," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1119-1131.
    13. Zhang, Wenyu & Zhang, Xiaohong & He, Shuguang & Zhao, Xing & He, Zhen, 2024. "Optimal condition-based maintenance policy for multi-component repairable systems with economic dependence in a finite-horizon," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    14. Duan, Chaoqun & Gong, Ting & Yan, Liangwen & Li, Xinmin, 2024. "Bi-level corrected residual life-based maintenance for deteriorating systems under competing risks," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    15. Zheng, Rui & Chen, Bingkun & Gu, Liudong, 2020. "Condition-based maintenance with dynamic thresholds for a system using the proportional hazards model," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    16. Zhao, Xiujie & Liu, Bin & Xu, Jianyu & Wang, Xiao-Lin, 2023. "Imperfect maintenance policies for warranted products under stochastic performance degradation," European Journal of Operational Research, Elsevier, vol. 308(1), pages 150-165.
    17. Huynh, K.T. & Vu, H.C. & Nguyen, T.D. & Ho, A.C., 2022. "A predictive maintenance model for k-out-of-n:F continuously deteriorating systems subject to stochastic and economic dependencies," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    18. Zheng, Rui & Wang, Jingjing & Zhang, Yingzhi, 2023. "A hybrid repair-replacement policy in the proportional hazards model," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1011-1021.
    19. Zhang, Nailong & Si, Wujun, 2020. "Deep reinforcement learning for condition-based maintenance planning of multi-component systems under dependent competing risks," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    20. Cholette, Michael E. & Yu, Hongyang & Borghesani, Pietro & Ma, Lin & Kent, Geoff, 2019. "Degradation modeling and condition-based maintenance of boiler heat exchangers using gamma processes," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 184-196.

    More about this item

    Keywords

    GIS; RCM; FMECA; LTA; simulation;
    All these keywords.

    Statistics

    Access and download statistics

    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:sae:risrel:v:236:y:2022:i:2:p:339-347. 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: SAGE Publications (email available below). General contact details of provider: .

    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.