IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v222y2008i4p553-560.html
   My bibliography  Save this article

Maintenance modelling and scheduling in fault-tolerant control

Author

Listed:
  • H Li
  • Q Zhao

Abstract

The present paper studies the modelling and scheduling problem of maintenance strategies in fault-tolerant control systems (FTCSs) using a stochastic modelling method. In FTCSs, the controller reconfigures itself to accommodate the occurrence of critical faults based on the information obtained from a fault detection and identification (FDI) scheme. Discrete semi-Markov chains are constructed to describe the operation of FTCSs with their unique characteristics incorporated. Two different maintenance strategies are discussed: FDI-dependent and FDI-independent periodic strategies, classified based on the use of FDI information in maintenance decision making. For each strategy, methods are presented for calculating the stationary availability and determining the optimal maintenance strategy to achieve the best availability. Two examples are given to demonstrate the proposed methods for both FDI-dependent and -independent cases.

Suggested Citation

  • H Li & Q Zhao, 2008. "Maintenance modelling and scheduling in fault-tolerant control," Journal of Risk and Reliability, , vol. 222(4), pages 553-560, December.
    • Handle: RePEc:sae:risrel:v:222:y:2008:i:4:p:553-560
    DOI: 10.1243/1748006XJRR93
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1243/1748006XJRR93
    Download Restriction: no
    File URL: https://libkey.io/10.1243/1748006XJRR93?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
    ---><---

    References listed on IDEAS

    as
    1. Chen, Dongyan & Trivedi, Kishor S., 2005. "Optimization for condition-based maintenance with semi-Markov decision process," Reliability Engineering and System Safety, Elsevier, vol. 90(1), pages 25-29.
    2. Ciriaco Valdez‐Flores & Richard M. Feldman, 1989. "A survey of preventive maintenance models for stochastically deteriorating single‐unit systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(4), pages 419-446, August.
    Full references (including those not matched with items on IDEAS)

    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. Maria Chiara Magnanini & Tullio Tolio, 2020. "Switching- and hedging- point policy for preventive maintenance with degrading machines: application to a two-machine line," Flexible Services and Manufacturing Journal, Springer, vol. 32(2), pages 241-271, June.
    2. Alaa H. Elwany & Nagi Z. Gebraeel & Lisa M. Maillart, 2011. "Structured Replacement Policies for Components with Complex Degradation Processes and Dedicated Sensors," Operations Research, INFORMS, vol. 59(3), pages 684-695, June.
    3. Oguzhan Alagoz & Lisa M. Maillart & Andrew J. Schaefer & Mark S. Roberts, 2007. "Determining the Acceptance of Cadaveric Livers Using an Implicit Model of the Waiting List," Operations Research, INFORMS, vol. 55(1), pages 24-36, February.
    4. Park, Chong Hyun & Lim, Heejong, 2021. "A parametric approach to integer linear fractional programming: Newton’s and Hybrid-Newton methods for an optimal road maintenance problem," European Journal of Operational Research, Elsevier, vol. 289(3), pages 1030-1039.
    5. Wooseung Jang & J. George Shanthikumar, 2002. "Stochastic allocation of inspection capacity to competitive processes," Naval Research Logistics (NRL), John Wiley & Sons, vol. 49(1), pages 78-94, February.
    6. Huixia Huo, 2024. "Optimal Corrective Maintenance Policies via an Availability-Cost Hybrid Factor for Software Aging Systems," Mathematics, MDPI, vol. 12(5), pages 1-14, February.
    7. David T. Abdul‐Malak & Jeffrey P. Kharoufeh & Lisa M. Maillart, 2019. "Maintaining systems with heterogeneous spare parts," Naval Research Logistics (NRL), John Wiley & Sons, vol. 66(6), pages 485-501, September.
    8. Zhao, Yunfei & Huang, Linan & Smidts, Carol & Zhu, Quanyan, 2020. "Finite-horizon semi-Markov game for time-sensitive attack response and probabilistic risk assessment in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    9. V. Makis & X. Jiang & K. Cheng, 2000. "Optimal Preventive Replacement Under Minimal Repair and Random Repair Cost," Mathematics of Operations Research, INFORMS, vol. 25(1), pages 141-156, February.
    10. Zhou, Zhi-Jie & Hu, Chang-Hua & Xu, Dong-Ling & Chen, Mao-Yin & Zhou, Dong-Hua, 2010. "A model for real-time failure prognosis based on hidden Markov model and belief rule base," European Journal of Operational Research, Elsevier, vol. 207(1), pages 269-283, November.
    11. Panagiotidou, S. & Tagaras, G., 2012. "Optimal integrated process control and maintenance under general deterioration," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 58-70.
    12. 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.
    13. Alberto Reyes & L. Enrique Sucar & Pablo H. Ibargüengoytia & Eduardo F. Morales, 2020. "Planning Under Uncertainty Applications in Power Plants Using Factored Markov Decision Processes," Energies, MDPI, vol. 13(9), pages 1-17, May.
    14. Patrick H. Liu, 2000. "A comparative study of three tool replacement/operation sequencing strategies in a flexible manufacturing system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(6), pages 479-499, September.
    15. Zhu, Xiaoyan & Wang, Jun & Yuan, Tao, 2019. "Design and maintenance for the data storage system considering system rebuilding process," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. Olde Keizer, Minou & Teunter, Ruud, 2014. "Opportunistic condition-based maintenance and aperiodic inspections for a two-unit series system," Research Report 14033-OPERA, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    17. Badía, F.G. & Berrade, M.D. & Cha, Ji Hwan & Lee, Hyunju, 2018. "Optimal replacement policy under a general failure and repair model: Minimal versus worse than old repair," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 362-372.
    18. 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.
    19. Girish Kumar & Vipul Jain & Umang Soni, 2019. "Modelling and simulation of repairable mechanical systems reliability and availability," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(5), pages 1221-1233, October.
    20. Yi Ding & Anatoly Lisnianski & Ilia Frenkel & Lev Khvatskin, 2009. "Optimal corrective maintenance contract planning for aging multi‐state system," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 25(5), pages 612-631, September.

    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:sae:risrel:v:222:y:2008:i:4:p:553-560. 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: SAGE Publications (email available below). General contact details of provider: .

    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.