IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v204y2020ics0951832020306268.html
   My bibliography  Save this article

A generalized model for recurrent failures prediction

Author

Listed:
  • Yevkin, Alexander
  • Krivtsov, Vasiliy

Abstract

There is a variety of models available for repairable systems with general repairs. Most popular are the Kijima models (reflecting the generalized renewal process of recurrent failures) and the Lam model (reflecting the geometric process). The Kijima models relating system's real and virtual ages can be thought of as the time shift transformation, whereas the Lam model – as the time scale transformation. In this paper, a new model is proposed that combines these two fundamental transformations within a new probabilistic formulation. Besides probabilistic aspect of the model, the maximum likelihood estimation of model parameters is discussed, and its performance is illustrated through several numerical examples using both simulated and real–life data. The efficient Monte Carlo calculation method is suggested for the expected number of recurrent events, unavailability, and the failure intensity function.

Suggested Citation

  • Yevkin, Alexander & Krivtsov, Vasiliy, 2020. "A generalized model for recurrent failures prediction," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:reensy:v:204:y:2020:i:c:s0951832020306268
    DOI: 10.1016/j.ress.2020.107125
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832020306268
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2020.107125?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. Shaomin Wu, 2018. "Doubly geometric processes and applications," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(1), pages 66-77, January.
    2. Wu, Shaomin, 2019. "A failure process model with the exponential smoothing of intensity functions," European Journal of Operational Research, Elsevier, vol. 275(2), pages 502-513.
    3. Tanwar, Monika & Rai, Rajiv N. & Bolia, Nomesh, 2014. "Imperfect repair modeling using Kijima type generalized renewal process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 24-31.
    4. W. John Braun & Wei Li & Yiqiang Q. Zhao, 2005. "Properties of the geometric and related processes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(7), pages 607-616, October.
    5. Maxim Finkelstein, 2008. "Failure Rate Modelling for Reliability and Risk," Springer Series in Reliability Engineering, Springer, number 978-1-84800-986-8, March.
    6. D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
    7. Doyen, Laurent & Gaudoin, Olivier & Syamsundar, Annamraju, 2017. "On geometric reduction of age or intensity models for imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 40-52.
    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. Hu, Wei & Westerlund, Per & Hilber, Patrik & Chen, Chuanhai & Yang, Zhaojun, 2022. "A general model, estimation, and procedure for modeling recurrent failure process of high-voltage circuit breakers considering multivariate impacts," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    2. Chehade, Abdallah & Savargaonkar, Mayuresh & Krivtsov, Vasiliy, 2022. "Conditional Gaussian mixture model for warranty claims forecasting," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    3. Hu, Wei & Yang, Zhaojun & Chen, Chuanhai & Wu, Yue & Xie, Qunya, 2021. "A Weibull-based recurrent regression model for repairable systems considering double effects of operation and maintenance: A case study of machine tools," Reliability Engineering and System Safety, Elsevier, vol. 213(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. Syamsundar, A. & Naikan, V.N.A. & Wu, Shaomin, 2021. "Extended Arithmetic Reduction of Age Models for the Failure Process of a Repairable System," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    2. Maxim Finkelstein & Ji Hwan Cha, 2022. "Reducing degradation and age of items in imperfect repair modeling," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(4), pages 1058-1081, December.
    3. Ait Mokhtar, El Hassene & Laggoune, Radouane & Chateauneuf, Alaa, 2023. "Imperfect maintenance modeling and assessment of repairable multi-component systems," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Jinyang Wang & Piao Chen & Zhisheng Ye, 2022. "Efficient semiparametric estimation of time‐censored intensity‐reduction models for repairable systems," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1860-1888, December.
    5. Beutner, Eric, 2023. "A review of effective age models and associated non- and semiparametric methods," Econometrics and Statistics, Elsevier, vol. 28(C), pages 105-119.
    6. Serguei Maximov & Consuelo de J. Cortes-Penagos, 2020. "A long-time asymptotic solution to the g-renewal equation for underlying distributions with nondecreasing hazard functions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 92(2), pages 311-341, October.
    7. Syamsundar, A. & Naikan, V.N.A. & Wu, Shaomin, 2020. "Alternative scales in reliability models for a repairable system," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    8. Zantek, Paul F. & Hanson, Timothy & Damien, Paul & Popova, Elmira, 2015. "A decision dependent stochastic process model for repairable systems with applications," Operations Research Perspectives, Elsevier, vol. 2(C), pages 73-80.
    9. Maxim Finkelstein & Ji Hwan Cha, 2021. "On degradation-based imperfect repair and induced generalized renewal processes," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(4), pages 1026-1045, December.
    10. Mingjuan Sun & Qinglai Dong & Zihan Gao, 2022. "An Imperfect Repair Model with Delayed Repair under Replacement and Repair Thresholds," Mathematics, MDPI, vol. 10(13), pages 1-15, June.
    11. Junyuan Wang & Jimin Ye, 2022. "A new repair model and its optimization for cold standby system," Operational Research, Springer, vol. 22(1), pages 105-122, March.
    12. Maxim Finkelstein & Gregory Levitin & Oleg A Stepanov, 2019. "On operation termination for degrading systems with two types of failures," Journal of Risk and Reliability, , vol. 233(3), pages 419-426, June.
    13. Nafisah, Ibrahim & Shrahili, Mansour & Alotaibi, Naif & Scarf, Phil, 2019. "Virtual series-system models of imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 604-613.
    14. Doyen, Laurent & Gaudoin, Olivier & Syamsundar, Annamraju, 2017. "On geometric reduction of age or intensity models for imperfect maintenance," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 40-52.
    15. Arnold, Richard & Chukova, Stefanka & Hayakawa, Yu & Marshall, Sarah, 2020. "Geometric-Like Processes: An Overview and Some Reliability Applications," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    16. Levitin, Gregory & Finkelstein, Maxim & Xiang, Yanping, 2021. "Optimal abort rules for additive multi-attempt missions," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    17. Wu, Shaomin, 2019. "A failure process model with the exponential smoothing of intensity functions," European Journal of Operational Research, Elsevier, vol. 275(2), pages 502-513.
    18. Yang, Duo & He, Zhen & He, Shuguang, 2016. "Warranty claims forecasting based on a general imperfect repair model considering usage rate," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 147-154.
    19. Na Cai & Wenbin Lu & Hao Helen Zhang, 2012. "Time-Varying Latent Effect Model for Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 68(4), pages 1093-1102, December.
    20. Julie K. Furberg & Per K. Andersen & Sofie Korn & Morten Overgaard & Henrik Ravn, 2023. "Bivariate pseudo-observations for recurrent event analysis with terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 256-287, April.

    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:204:y:2020:i:c:s0951832020306268. 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.