IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v149y2016icp76-87.html
   My bibliography  Save this article

Remaining useful lifetime estimation and noisy gamma deterioration process

Author

Listed:
  • Le Son, Khanh
  • Fouladirad, Mitra
  • Barros, Anne

Abstract

In many industrial issues where safety, reliability, and availability are considered of first importance, the lifetime prediction is a basic requirement. In this paper, by developing a prognostic probabilistic approach, a remaining lifetime distribution is associated to the system or component under consideration. More particularly, the system׳s deterioration is modelled by a non-homogeneous gamma process. The model considers a noisy observed degradation data and by using the Gibbs sampling technique, the hidden degradation states are approximated and afterwards the system׳s remaining useful lifetime distribution is estimated. Our proposed prognosis method is applied to the Prognostic and Health Management (PHM) 2008 conference challenge data and the interest of our probabilistic model is highlighted. To point out the interest of the prognostic, a maintenance decision rule based on the remaining lifetime estimation results is proposed.

Suggested Citation

  • Le Son, Khanh & Fouladirad, Mitra & Barros, Anne, 2016. "Remaining useful lifetime estimation and noisy gamma deterioration process," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 76-87.
    • Handle: RePEc:eee:reensy:v:149:y:2016:i:c:p:76-87
    DOI: 10.1016/j.ress.2015.12.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015003683
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2015.12.016?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. Le Son, Khanh & Fouladirad, Mitra & Barros, Anne & Levrat, Eric & Iung, Benoît, 2013. "Remaining useful life estimation based on stochastic deterioration models: A comparative study," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 165-175.
    2. Dongliang Lu & Mahesh D Pandey & Wei-Chau Xie, 2013. "An efficient method for the estimation of parameters of stochastic gamma process from noisy degradation measurements," Journal of Risk and Reliability, , vol. 227(4), pages 425-433, August.
    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. Chen, Jinglong & Jing, Hongjie & Chang, Yuanhong & Liu, Qian, 2019. "Gated recurrent unit based recurrent neural network for remaining useful life prediction of nonlinear deterioration process," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 372-382.
    2. Zhang, Nan & Fouladirad, Mitra & Barros, Anne & Zhang, Jun, 2020. "Condition-based maintenance for a K-out-of-N deteriorating system under periodic inspection with failure dependence," European Journal of Operational Research, Elsevier, vol. 287(1), pages 159-167.
    3. Wang, Xiaofei & Wang, Bing Xing & Hong, Yili & Jiang, Pei Hua, 2021. "Degradation data analysis based on gamma process with random effects," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1200-1208.
    4. Duan, Chaoqun & Li, Yifan & Pu, Huayan & Luo, Jun, 2022. "Adaptive monitoring scheme of stochastically failing systems under hidden degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Liu, Xingheng & Matias, José & Jäschke, Johannes & Vatn, Jørn, 2022. "Gibbs sampler for noisy Transformed Gamma process: Inference and remaining useful life estimation," Reliability Engineering and System Safety, Elsevier, vol. 217(C).
    6. Hazra, Indranil & Pandey, Mahesh D. & Manzana, Noldainerick, 2020. "Approximate Bayesian computation (ABC) method for estimating parameters of the gamma process using noisy data," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    7. Hao, Songhua & Yang, Jun & Berenguer, Christophe, 2019. "Degradation analysis based on an extended inverse Gaussian process model with skew-normal random effects and measurement errors," Reliability Engineering and System Safety, Elsevier, vol. 189(C), pages 261-270.
    8. Xia, Tangbin & Dong, Yifan & Xiao, Lei & Du, Shichang & Pan, Ershun & Xi, Lifeng, 2018. "Recent advances in prognostics and health management for advanced manufacturing paradigms," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 255-268.
    9. Li, Jing & Stones, Rebecca J. & Wang, Gang & Liu, Xiaoguang & Li, Zhongwei & Xu, Ming, 2017. "Hard drive failure prediction using Decision Trees," Reliability Engineering and System Safety, Elsevier, vol. 164(C), pages 55-65.
    10. Tao, Xin & Mårtensson, Jonas & Warnquist, Håkan & Pernestål, Anna, 2022. "Short-term maintenance planning of autonomous trucks for minimizing economic risk," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    11. Chatenet, Q. & Remy, E. & Gagnon, M. & Fouladirad, M. & Tahan, A.S., 2021. "Modeling cavitation erosion using non-homogeneous gamma process," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    12. Li, Naipeng & Gebraeel, Nagi & Lei, Yaguo & Fang, Xiaolei & Cai, Xiao & Yan, Tao, 2021. "Remaining useful life prediction based on a multi-sensor data fusion model," Reliability Engineering and System Safety, Elsevier, vol. 208(C).
    13. Moradi, Ramin & Groth, Katrina M., 2020. "Modernizing risk assessment: A systematic integration of PRA and PHM techniques," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    14. Xu, Ancha & Shen, Lijuan, 2018. "Improved on-line estimation for gamma process," Statistics & Probability Letters, Elsevier, vol. 143(C), pages 67-73.
    15. Xiaojie Ke & Zhengguo Xu & Wenhai Wang & Youxian Sun, 2017. "Remaining useful life prediction for non-stationary degradation processes with shocks," Journal of Risk and Reliability, , vol. 231(5), pages 469-480, October.
    16. Chen, Zhen & Li, Yaping & Xia, Tangbin & Pan, Ershun, 2019. "Hidden Markov model with auto-correlated observations for remaining useful life prediction and optimal maintenance policy," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 123-136.
    17. Dong, Qinglai & Cui, Lirong, 2019. "A study on stochastic degradation process models under different types of failure Thresholds," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 202-212.

    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. Zhang, Jian-Xun & Hu, Chang-Hua & He, Xiao & Si, Xiao-Sheng & Liu, Yang & Zhou, Dong-Hua, 2017. "Lifetime prognostics for deteriorating systems with time-varying random jumps," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 338-350.
    2. 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).
    3. Zhou, Shirong & Tang, Yincai & Xu, Ancha, 2021. "A generalized Wiener process with dependent degradation rate and volatility and time-varying mean-to-variance ratio," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    4. Yan, Bingxin & Ma, Xiaobing & Yang, Li & Wang, Han & Wu, Tianyi, 2020. "A novel degradation-rate-volatility related effect Wiener process model with its extension to accelerated ageing data analysis," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    5. Nguyen, Khanh T.P. & Medjaher, Kamal, 2019. "A new dynamic predictive maintenance framework using deep learning for failure prognostics," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 251-262.
    6. Wang, Xiaolin & Balakrishnan, Narayanaswamy & Guo, Bo, 2014. "Residual life estimation based on a generalized Wiener degradation process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 13-23.
    7. Hu, Changhua & Xing, Yuanxing & Du, Dangbo & Si, Xiaosheng & Zhang, Jianxun, 2023. "Remaining useful life estimation for two-phase nonlinear degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    8. Do, M. Hung & Söffker, Dirk, 2021. "State-of-the-art in integrated prognostics and health management control for utility-scale wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    9. Xiaojie Ke & Zhengguo Xu & Wenhai Wang & Youxian Sun, 2017. "Remaining useful life prediction for non-stationary degradation processes with shocks," Journal of Risk and Reliability, , vol. 231(5), pages 469-480, October.
    10. 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.
    11. Zhang, Zhengxin & Si, Xiaosheng & Hu, Changhua & Lei, Yaguo, 2018. "Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods," European Journal of Operational Research, Elsevier, vol. 271(3), pages 775-796.
    12. Cai, Xiao & Li, Naipeng & Xie, Min, 2024. "RUL prediction for two-phase degrading systems considering physical damage observations," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    13. Qin, H. & Zhou, W. & Zhang, S., 2015. "Bayesian inferences of generation and growth of corrosion defects on energy pipelines based on imperfect inspection data," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 334-342.
    14. Estelle Deloux & Mitra Fouladirad & Christophe Bérenguer, 2016. "Health-and-usage-based maintenance policies for a partially observable deteriorating system," Journal of Risk and Reliability, , vol. 230(1), pages 120-129, February.
    15. Zhang, Fode & Ng, Hon Keung Tony & Shi, Yimin, 2020. "Mis-specification analysis of Wiener degradation models by using f-divergence with outliers," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    16. Malinowski, Simon & Chebel-Morello, Brigitte & Zerhouni, Noureddine, 2015. "Remaining useful life estimation based on discriminating shapelet extraction," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 279-288.
    17. He, Jiabei & Tian, Yi & Wu, Lifeng, 2022. "A hybrid data-driven method for rapid prediction of lithium-ion battery capacity," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    18. Al-Dahidi, Sameer & Di Maio, Francesco & Baraldi, Piero & Zio, Enrico, 2016. "Remaining useful life estimation in heterogeneous fleets working under variable operating conditions," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 109-124.
    19. González, Esteban Le Maitre & Desforges, Xavier & Archimède, Bernard, 2018. "Assessment method of the multicomponent systems future ability to achieve productive tasks from local prognoses," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 403-415.
    20. Huynh, K.T. & Grall, A. & Bérenguer, C., 2017. "Assessment of diagnostic and prognostic condition indices for efficient and robust maintenance decision-making of systems subject to stress corrosion cracking," Reliability Engineering and System Safety, Elsevier, vol. 159(C), pages 237-254.

    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:149:y:2016:i:c:p:76-87. 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.