IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v203y2020ics095183202030555x.html
   My bibliography  Save this article

Virtual age models with time-dependent covariates: A framework for simulation, parametric inference and quality of estimation

Author

Listed:
  • Brenière, Léa
  • Doyen, Laurent
  • Bérenguer, Christophe

Abstract

A repairable system faces some failures and imperfect maintenances throughout its lifetime. If several identical and independent systems are considered together, some differences may arise between the systems, such as the geographical location or the maintenance team for example, which are constant information, or the weather conditions, which vary with time. This observed heterogeneity will influence more or less the failure process. In this paper, we include these data in a generalized virtual age model with the use of covariates. Then we estimate simultaneously the effect of the maintenances, that of the covariates, and the intrinsic wear of the systems. We also propose two simulation methods as well as a numerical estimation procedure. Then we assess the quality of the estimation of the parameters with a thorough simulation study.

Suggested Citation

  • Brenière, Léa & Doyen, Laurent & Bérenguer, Christophe, 2020. "Virtual age models with time-dependent covariates: A framework for simulation, parametric inference and quality of estimation," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    • Handle: RePEc:eee:reensy:v:203:y:2020:i:c:s095183202030555x
    DOI: 10.1016/j.ress.2020.107054
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183202030555X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2020.107054?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. Peng, Weiwen & Shen, Lijuan & Shen, Yan & Sun, Qiuzhuang, 2018. "Reliability analysis of repairable systems with recurrent misuse-induced failures and normal-operation failures," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 87-98.
    2. MERCIER, Sophie & CASTRO, I.T., 2019. "Stochastic comparisons of imperfect maintenance models for a gamma deteriorating system," European Journal of Operational Research, Elsevier, vol. 273(1), pages 237-248.
    3. Qiang Zhou & Junbo Son & Shiyu Zhou & Xiaofeng Mao & Mutasim Salman, 2014. "Remaining useful life prediction of individual units subject to hard failure," IISE Transactions, Taylor & Francis Journals, vol. 46(10), pages 1017-1030, October.
    4. Giorgio, M. & Guida, M. & Pulcini, G., 2014. "Repairable system analysis in presence of covariates and random effects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 271-281.
    5. Miao Han & Liuquan Sun & Yutao Liu & Jun Zhu, 2018. "Joint analysis of recurrent event data with additive–multiplicative hazards model for the terminal event time," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 81(5), pages 523-547, July.
    6. Li, Li & Hanson, Timothy E., 2014. "A Bayesian semiparametric regression model for reliability data using effective age," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 177-188.
    7. Wu, Shaomin & Scarf, Philip, 2015. "Decline and repair, and covariate effects," European Journal of Operational Research, Elsevier, vol. 244(1), pages 219-226.
    8. Gongjun Xu & Sy Han Chiou & Chiung-Yu Huang & Mei-Cheng Wang & Jun Yan, 2017. "Joint Scale-Change Models for Recurrent Events and Failure Time," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(518), pages 794-805, April.
    9. Poulami Maitra & Leila D. A. F. Amorim & Jianwen Cai, 2020. "Multiplicative rates model for recurrent events in case-cohort studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 134-157, January.
    10. Dijoux, Yann & Fouladirad, Mitra & Nguyen, Dinh Tuan, 2016. "Statistical inference for imperfect maintenance models with missing data," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 84-96.
    11. Li-An Lin & Sheng Luo & Barry R. Davis, 2018. "Bayesian regression model for recurrent event data with event-varying covariate effects and event effect," Journal of Applied Statistics, Taylor & Francis Journals, vol. 45(7), pages 1260-1276, May.
    12. Yang, Li & Ye, Zhi-sheng & Lee, Chi-Guhn & Yang, Su-fen & Peng, Rui, 2019. "A two-phase preventive maintenance policy considering imperfect repair and postponed replacement," European Journal of Operational Research, Elsevier, vol. 274(3), pages 966-977.
    13. He, Haijin & Pan, Deng & Sun, Liuquan & Li, Yimei & Robison, Leslie L. & Song, Xinyuan, 2017. "Analysis of a fixed center effect additive rates model for recurrent event data," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 186-197.
    14. Per Kragh Andersen & Jules Angst & Henrik Ravn, 2019. "Modeling marginal features in studies of recurrent events in the presence of a terminal event," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(4), pages 681-695, October.
    15. 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. Wu, Shaomin, 2021. "Two methods to approximate the superposition of imperfect failure processes," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    3. 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.
    4. Brenière, Léa & Doyen, Laurent & Bérenguer, Christophe, 2023. "Optimization of preventive replacements dates and covariate inspections for repairable systems in varying environments," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1126-1141.
    5. 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).
    6. 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).
    7. 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).

    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. Mosayebi Omshi, E. & Grall, A., 2021. "Replacement and imperfect repair of deteriorating system: Study of a CBM policy and impact of repair efficiency," 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. 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.
    4. 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.
    5. Shi, Yue & Xiang, Yisha & Xiao, Hui & Xing, Liudong, 2021. "Joint optimization of budget allocation and maintenance planning of multi-facility transportation infrastructure systems," European Journal of Operational Research, Elsevier, vol. 288(2), pages 382-393.
    6. 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.
    7. Slimacek, Vaclav & Lindqvist, Bo Henry, 2017. "Nonhomogeneous Poisson process with nonparametric frailty and covariates," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 75-83.
    8. Zhou, Yu & Kou, Gang & Xiao, Hui & Peng, Yi & Alsaadi, Fawaz E., 2020. "Sequential imperfect preventive maintenance model with failure intensity reduction with an application to urban buses," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    9. Zhang, Fengxia & Shen, Jingyuan & Ma, Yizhong, 2020. "Optimal maintenance policy considering imperfect repairs and non-constant probabilities of inspection errors," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    10. Khac Tuan Huynh & Antoine Grall, 2020. "A condition-based maintenance model with past-dependent imperfect preventive repairs for continuously deteriorating systems," Journal of Risk and Reliability, , vol. 234(2), pages 333-358, April.
    11. 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.
    12. Hsiang Yu & Yu‐Jen Cheng & Ching‐Yun Wang, 2018. "Methods for multivariate recurrent event data with measurement error and informative censoring," Biometrics, The International Biometric Society, vol. 74(3), pages 966-976, September.
    13. Zhang, Fengxia & Shen, Jingyuan & Liao, Haitao & Ma, Yizhong, 2021. "Optimal preventive maintenance policy for a system subject to two-phase imperfect inspections," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    14. Wu, Shaomin & Scarf, Philip, 2017. "Two new stochastic models of the failure process of a series system," European Journal of Operational Research, Elsevier, vol. 257(3), pages 763-772.
    15. Xiaowei Sun & Jieli Ding & Liuquan Sun, 2020. "A semiparametric additive rates model for the weighted composite endpoint of recurrent and terminal events," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 471-492, July.
    16. Ali Nouri Qarahasanlou & Ali Zamani & Abbas Barabadi & Mahdi Mokhberdoran, 2021. "Resilience Assessment: A Performance-Based Importance Measure," Energies, MDPI, vol. 14(22), pages 1-16, November.
    17. Xiaoyu Wang & Liuquan Sun, 2023. "Joint modeling of generalized scale-change models for recurrent event and failure time data," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(1), pages 1-33, January.
    18. Jahani, Salman & Zhou, Shiyu & Veeramani, Dharmaraj, 2021. "Stochastic prognostics under multiple time-varying environmental factors," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    19. Zhang, Jian-Xun & Si, Xiao-Sheng & Du, Dang-Bo & Hu, Chang-Hua & Hu, Chen, 2020. "A novel iterative approach of lifetime estimation for standby systems with deteriorating spare parts," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    20. Wu, Shaomin & Do, Phuc, 2017. "Editorial," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 1-3.

    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:203:y:2020:i:c:s095183202030555x. 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.