IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v184y2019icp181-192.html
   My bibliography  Save this article

Life-cycle maintenance cost analysis framework considering time-dependent false and missed alarms for fault diagnosis

Author

Listed:
  • Yoon, Joung Taek
  • Youn, Byeng D.
  • Yoo, Minji
  • Kim, Yunhan
  • Kim, Sooho

Abstract

Fault diagnosis aims to diagnose system failures and to enable timely maintenance that, in turn, can minimize system maintenance costs. In order to evaluate and maximize the benefits from fault diagnosis, the life†cycle maintenance cost should be analyzed. This paper presents a framework for life†cycle maintenance cost analysis that considers time†dependent false and missed alarms in fault diagnosis. First, time†dependent false and missed alarms are proposed. The false and missed alarm rates are not static but vary depending on the health state of the engineered system, which changes over time. Second, a life†cycle maintenance cost analysis framework is proposed. This is based upon a stochastic simulation method that can incorporate time†dependent false and missed alarm rates and various uncertainties, such as health degradation and health restoration through maintenance. Third, a fault diagnosis model design method is proposed, based upon the proposed life†cycle maintenance cost analysis framework. The proposed method incorporates optimal false and missed alarm weights into the life†cycle maintenance cost. As a result, the proposed ideas enable accurate estimation and minimization of the overall life†cycle maintenance cost. The effectiveness of the proposed methods is demonstrated via a numerical example and an electro†hydrostatic actuator case study.

Suggested Citation

  • Yoon, Joung Taek & Youn, Byeng D. & Yoo, Minji & Kim, Yunhan & Kim, Sooho, 2019. "Life-cycle maintenance cost analysis framework considering time-dependent false and missed alarms for fault diagnosis," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 181-192.
  • Handle: RePEc:eee:reensy:v:184:y:2019:i:c:p:181-192
    DOI: 10.1016/j.ress.2018.06.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832017310918
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ress.2018.06.006?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
    ---><---

    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. Mauricio Sánchez-Silva & Georgia-Ann Klutke, 2016. "Reliability and Life-Cycle Analysis of Deteriorating Systems," Springer Series in Reliability Engineering, Springer, number 978-3-319-20946-3, September.
    2. Yoon, Joung Taek & Youn, Byeng D. & Yoo, Minji & Kim, Yunhan, 2017. "A newly formulated resilience measure that considers false alarms," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 417-427.
    3. Khan, Samir & Phillips, Paul & Jennions, Ian & Hockley, Chris, 2014. "No Fault Found events in maintenance engineering Part 1: Current trends, implications and organizational practices," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 183-195.
    4. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    5. 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.
    6. Yang Hu & Piero Baraldi & Francesco Di Maio & Enrico Zio, 2017. "A Systematic Semi-Supervised Self-adaptable Fault Diagnostics approach in an evolving environment," Post-Print hal-01652242, HAL.
    7. Janssen, Hans, 2013. "Monte-Carlo based uncertainty analysis: Sampling efficiency and sampling convergence," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 123-132.
    8. Khan, Samir & Phillips, Paul & Hockley, Chris & Jennions, Ian, 2014. "No Fault Found events in maintenance engineering Part 2: Root causes, technical developments and future research," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 196-208.
    9. Wu, Fan & Niknam, Seyed A. & Kobza, John E., 2015. "A cost effective degradation-based maintenance strategy under imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 234-243.
    10. Bilal M. Ayyub, 2014. "Systems Resilience for Multihazard Environments: Definition, Metrics, and Valuation for Decision Making," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 340-355, February.
    11. Oh, Hyunseok & Choi, Seunghyuk & Kim, Keunsu & Youn, Byeng D. & Pecht, Michael, 2015. "An empirical model to describe performance degradation for warranty abuse detection in portable electronics," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 92-99.
    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. Levitin, Gregory & Finkelstein, Maxim & Huang, Hong-Zhong, 2019. "Scheduling of imperfect inspections for reliability critical systems with shock-driven defects and delayed failures," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 89-98.
    2. Bode, Gerrit & Thul, Simon & Baranski, Marc & Müller, Dirk, 2020. "Real-world application of machine-learning-based fault detection trained with experimental data," Energy, Elsevier, vol. 198(C).
    3. Cláudia Ferreira & Ana Silva & Jorge de Brito & Ilídio S. Dias & Inês Flores-Colen, 2021. "Condition-Based Maintenance Strategies to Enhance the Durability of ETICS," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    4. Li, Jiahui & Qi, Xiaogang & He, Yi & Liu, Lifang, 2024. "SDN candidate and protection path selection for link failure protection in hybrid SDNs," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    5. Wang, Run-Zi & Gu, Hang-Hang & Zhu, Shun-Peng & Li, Kai-Shang & Wang, Ji & Wang, Xiao-Wei & Hideo, Miura & Zhang, Xian-Cheng & Tu, Shan-Tung, 2022. "A data-driven roadmap for creep-fatigue reliability assessment and its implementation in low-pressure turbine disk at elevated temperatures," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    6. Compare, Michele & Antonello, Federico & Pinciroli, Luca & Zio, Enrico, 2022. "A general model for life-cycle cost analysis of Condition-Based Maintenance enabled by PHM capabilities," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    7. Zhang, Wei-Heng & Qin, Jianjun & Lu, Da-Gang & Liu, Min & Faber, Michael H., 2023. "Quantification of the value of condition monitoring system with time-varying monitoring performance in the context of risk-based inspection," Reliability Engineering and System Safety, Elsevier, vol. 231(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. 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.
    2. de Jonge, Bram & Scarf, Philip A., 2020. "A review on maintenance optimization," European Journal of Operational Research, Elsevier, vol. 285(3), pages 805-824.
    3. 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).
    4. 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).
    5. Wang, Weikai & Chen, Xian, 2023. "Piecewise deterministic Markov process for condition-based imperfect maintenance models," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    6. 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.
    7. Esposito, Nicola & Mele, Agostino & Castanier, Bruno & GIORGIO, Massimiliano, 2023. "A hybrid maintenance policy for a deteriorating unit in the presence of three forms of variability," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    8. Mottahedi, Adel & Sereshki, Farhang & Ataei, Mohammad & Qarahasanlou, Ali Nouri & Barabadi, Abbas, 2021. "Resilience estimation of critical infrastructure systems: Application of expert judgment," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    9. Yi, He & Cui, Lirong & Shen, Jingyuan & Li, Yan, 2018. "Stochastic properties and reliability measures of discrete-time semi-Markovian systems," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 162-173.
    10. 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).
    11. Han, Changwoon & Park, Seungil & Lee, Hyeonseok, 2019. "Intermittent failure in electrical interconnection of avionics system," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 61-71.
    12. Giorgio, Massimiliano & Pulcini, Gianpaolo, 2024. "The effect of model misspecification of the bounded transformed gamma process on maintenance optimization," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    13. Michiel A. J. uit het Broek & Ruud H. Teunter & Bram de Jonge & Jasper Veldman & Nicky D. Van Foreest, 2020. "Condition-Based Production Planning: Adjusting Production Rates to Balance Output and Failure Risk," Manufacturing & Service Operations Management, INFORMS, vol. 22(4), pages 792-811, July.
    14. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    15. 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).
    16. Ahmet Erkoyuncu, John & Khan, Samir & Hussain, Syed Mohammed Fazal & Roy, Rajkumar, 2016. "A framework to estimate the cost of No-Fault Found events," International Journal of Production Economics, Elsevier, vol. 173(C), pages 207-222.
    17. Prakash Chandra & Yogesh Mani Tripathi & Liang Wang & Chandrakant Lodhi, 2023. "Estimation for Kies distribution with generalized progressive hybrid censoring under partially observed competing risks model," Journal of Risk and Reliability, , vol. 237(6), pages 1048-1072, December.
    18. Mosayebi Omshi, E. & Grall, A. & Shemehsavar, S., 2020. "A dynamic auto-adaptive predictive maintenance policy for degradation with unknown parameters," European Journal of Operational Research, Elsevier, vol. 282(1), pages 81-92.
    19. Pedersen, Tom Ivar & Vatn, Jørn, 2022. "Optimizing a condition-based maintenance policy by taking the preferences of a risk-averse decision maker into account," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    20. Li, Rui & Verhagen, Wim J.C. & Curran, Richard, 2020. "A systematic methodology for Prognostic and Health Management system architecture definition," Reliability Engineering and System Safety, Elsevier, vol. 193(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:reensy:v:184:y:2019:i:c:p:181-192. 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: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.