IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v140y2015icp22-36.html
   My bibliography  Save this article

A modeling framework for deteriorating control system and predictive maintenance of actuators

Author

Listed:
  • Langeron, Y.
  • Grall, A.
  • Barros, A.

Abstract

Actuators play a central role in industrial automation systems. They are costly, and therefore studying their dependability needs all attention. Usually, an actuator is inserted in a feedback control system, and its mission is to implement a control action delivered by a controller. In this paper, a monotonic actuator deterioration is considered and it is assumed that a relationship exists between the control action and the physical actuator׳s deterioration. A modeling framework is proposed including a non-decreasing stochastic degradation process driving the inability for an actuator to fully implement its role. The prognosis of the actuator׳s residual useful lifetime is derived and used to update the controller׳s setting. The controller reconfiguration completes the maintenance corrective and preventive actions. This new action is suggested as an alternative for maintenance strategy.

Suggested Citation

  • Langeron, Y. & Grall, A. & Barros, A., 2015. "A modeling framework for deteriorating control system and predictive maintenance of actuators," Reliability Engineering and System Safety, Elsevier, vol. 140(C), pages 22-36.
    • Handle: RePEc:eee:reensy:v:140:y:2015:i:c:p:22-36
    DOI: 10.1016/j.ress.2015.03.028
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832015000940
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2015.03.028?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. Haitao Liao & Zhigang Tian, 2013. "A framework for predicting the remaining useful life of a single unit under time-varying operating conditions," IISE Transactions, Taylor & Francis Journals, vol. 45(9), pages 964-980.
    2. F. Guenab & P. Weber & D. Theilliol & Y.M. Zhang, 2011. "Design of a fault tolerant control system incorporating reliability analysis and dynamic behaviour constraints," International Journal of Systems Science, Taylor & Francis Journals, vol. 42(1), pages 219-233.
    3. Zhao, Xuejing & Fouladirad, Mitra & Bérenguer, Christophe & Bordes, Laurent, 2010. "Condition-based inspection/replacement policies for non-monotone deteriorating systems with environmental covariates," Reliability Engineering and System Safety, Elsevier, vol. 95(8), pages 921-934.
    4. Moghaddass, Ramin & Zuo, Ming J., 2014. "An integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process," Reliability Engineering and System Safety, Elsevier, vol. 124(C), pages 92-104.
    5. Ariane Lorton & Mitra Fouladirad & Antoine Grall, 2013. "Computation of remaining useful life on a physic-based model and impact of a prognosis on the maintenance process," Journal of Risk and Reliability, , vol. 227(4), pages 434-449, August.
    6. van Noortwijk, J.M., 2009. "A survey of the application of gamma processes in maintenance," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 2-21.
    7. Domínguez-García, Alejandro D. & Kassakian, John G. & Schindall, Joel E. & Zinchuk, Jeffrey J., 2008. "An integrated methodology for the dynamic performance and reliability evaluation of fault-tolerant systems," Reliability Engineering and System Safety, Elsevier, vol. 93(11), pages 1628-1649.
    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. Singh, Gurmeet & Anil Kumar, T.Ch. & Naikan, V.N.A., 2019. "Efficiency monitoring as a strategy for cost effective maintenance of induction motors for minimizing carbon emission and energy consumption," Reliability Engineering and System Safety, Elsevier, vol. 184(C), pages 193-201.
    2. Yiwei Wang & Christian Gogu & Nicolas Binaud & Christian Bes & Raphael T Haftka & Nam-Ho Kim, 2018. "Predictive airframe maintenance strategies using model-based prognostics," Journal of Risk and Reliability, , vol. 232(6), pages 690-709, December.
    3. Yves Langeron & Khac Tuan Huynh & Antoine Grall, 2021. "A root location-based framework for degradation modeling of dynamic systems with predictive maintenance perspective," Journal of Risk and Reliability, , vol. 235(2), pages 253-267, April.
    4. 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.

    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. Peng, Weiwen & Li, Yan-Feng & Mi, Jinhua & Yu, Le & Huang, Hong-Zhong, 2016. "Reliability of complex systems under dynamic conditions: A Bayesian multivariate degradation perspective," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 75-87.
    2. Jahani, Salman & Zhou, Shiyu & Veeramani, Dharmaraj, 2021. "Stochastic prognostics under multiple time-varying environmental factors," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    3. 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.
    4. Marwa Belhaj Salem & Mitra Fouladirad & Estelle Deloux, 2021. "Prognostic and Classification of Dynamic Degradation in a Mechanical System Using Variance Gamma Process," Mathematics, MDPI, vol. 9(3), pages 1-25, January.
    5. Zhang, Nan & Deng, Yingjun & Liu, Bin & Zhang, Jun, 2023. "Condition-based maintenance for a multi-component system in a dynamic operating environment," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    6. N. C. Caballé & I. T. Castro, 2019. "Assessment of the maintenance cost and analysis of availability measures in a finite life cycle for a system subject to competing failures," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(1), pages 255-290, March.
    7. Liu, Bin & Zhao, Xiujie & Liu, Guoquan & Liu, Yiqi, 2020. "Life cycle cost analysis considering multiple dependent degradation processes and environmental influence," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    8. 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.
    9. 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.
    10. Nguyen, Khanh T.P. & Fouladirad, Mitra & Grall, Antoine, 2018. "Model selection for degradation modeling and prognosis with health monitoring data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 105-116.
    11. Caballé, N.C. & Castro, I.T. & Pérez, C.J. & Lanza-Gutiérrez, J.M., 2015. "A condition-based maintenance of a dependent degradation-threshold-shock model in a system with multiple degradation processes," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 98-109.
    12. 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.
    13. Chen, Nan & Ye, Zhi-Sheng & Xiang, Yisha & Zhang, Linmiao, 2015. "Condition-based maintenance using the inverse Gaussian degradation model," European Journal of Operational Research, Elsevier, vol. 243(1), pages 190-199.
    14. Si, Xiao-Sheng & Wang, Wenbin & Hu, Chang-Hua & Zhou, Dong-Hua, 2011. "Remaining useful life estimation - A review on the statistical data driven approaches," European Journal of Operational Research, Elsevier, vol. 213(1), pages 1-14, August.
    15. Linmiao Zhang & Yong Lei & Houcai Shen, 2016. "How heterogeneity influences condition-based maintenance for gamma degradation process," International Journal of Production Research, Taylor & Francis Journals, vol. 54(19), pages 5829-5841, October.
    16. Song, Kai & Shi, Jian & Yi, Xiaojian, 2020. "A time-discrete and zero-adjusted gamma process model with application to degradation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 560(C).
    17. Thomas Michael Welte & Iver Bakken Sperstad & Espen Høegh Sørum & Magne Lorentzen Kolstad, 2017. "Integration of Degradation Processes in a Strategic Offshore Wind Farm O&M Simulation Model," Energies, MDPI, vol. 10(7), pages 1-18, July.
    18. Finkelstein, Maxim & Cha, Ji Hwan & Langston, Amy, 2023. "Improving classical optimal age-replacement policies for degrading items," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    19. Lin, Yan-Hui & Li, Yan-Fu & Zio, Enrico, 2018. "A comparison between Monte Carlo simulation and finite-volume scheme for reliability assessment of multi-state physics systems," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 1-11.
    20. Phuc Do & Christophe Bérenguer, 2022. "Residual life-based importance measures for predictive maintenance decision-making," Journal of Risk and Reliability, , vol. 236(1), pages 98-113, February.

    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:140:y:2015:i:c:p:22-36. 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.