IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v71y2019i3d10.1007_s10463-018-0650-4.html
   My bibliography  Save this article

Reliability analysis of a k-out-of-n:F system under a linear degradation model with calibrations

Author

Listed:
  • Ensiyeh Nezakati

    (Ferdowsi University of Mashhad)

  • Mostafa Razmkhah

    (Ferdowsi University of Mashhad)

  • Firoozeh Haghighi

    (University of Tehran)

Abstract

A k-out-of-n:F system with both of soft and hard failures is considered such that its components degrade through internal and external factors. A linear model is considered for degradation path of each component. Reliability function of the system is derived and the effect of varying the parameters are studied on reliability function for some systems. Moreover, the effect of calibration on reliability and maximum working time of such a system is investigated. The optimal number of calibrations is also determined for some special cases.

Suggested Citation

  • Ensiyeh Nezakati & Mostafa Razmkhah & Firoozeh Haghighi, 2019. "Reliability analysis of a k-out-of-n:F system under a linear degradation model with calibrations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(3), pages 537-552, June.
  • Handle: RePEc:spr:aistmt:v:71:y:2019:i:3:d:10.1007_s10463-018-0650-4
    DOI: 10.1007/s10463-018-0650-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10463-018-0650-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10463-018-0650-4?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. 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.
    2. Firoozeh Haghighi & Mikhail Nikulin, 2010. "On the linear degradation model with multiple failure modes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1499-1507.
    3. Zhibing Xu & Yili Hong & Ran Jin, 2016. "Nonlinear general path models for degradation data with dynamic covariates," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 32(2), pages 153-167, March.
    4. Silvia Rodríguez-Narciso & J. Andrés Christen, 2016. "Optimal sequential Bayesian analysis for degradation tests," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(3), pages 405-428, July.
    5. Tavangar, Mahdi & Bairamov, Ismihan, 2015. "On conditional residual lifetime and conditional inactivity time of k-out-of-n systems," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 225-233.
    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. Saberzadeh, Zahra & Razmkhah, Mostafa, 2022. "Reliability of degrading complex systems with two dependent components per element," Reliability Engineering and System Safety, Elsevier, vol. 222(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. 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).
    2. 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.
    3. Saberzadeh, Zahra & Razmkhah, Mostafa, 2022. "Reliability of degrading complex systems with two dependent components per element," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    4. 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).
    5. 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.
    6. 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).
    7. 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.
    8. Wang, Xiaolin & Liu, Bin & Zhao, Xiujie, 2021. "A performance-based warranty for products subject to competing hard and soft failures," International Journal of Production Economics, Elsevier, vol. 233(C).
    9. Nicolai, R.P. & Frenk, J.B.G. & Dekker, R., 2007. "Modelling and Optimizing Imperfect Maintenance of Coatings on Steel Structures," ERIM Report Series Research in Management ERS-2007-043-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    10. Jahani, Salman & Zhou, Shiyu & Veeramani, Dharmaraj, 2021. "Stochastic prognostics under multiple time-varying environmental factors," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    11. Lin Wang & Zhiqiang Lu & Yifei Ren, 2019. "A rolling horizon approach for production planning and condition-based maintenance under uncertain demand," Journal of Risk and Reliability, , vol. 233(6), pages 1014-1028, December.
    12. Liang, Qingzhu & Yang, Yinghao & Peng, Changhong, 2023. "A reliability model for systems subject to mutually dependent degradation processes and random shocks under dynamic environments," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    13. Shen, Jingyuan & Cui, Lirong & Ma, Yizhong, 2019. "Availability and optimal maintenance policy for systems degrading in dynamic environments," European Journal of Operational Research, Elsevier, vol. 276(1), pages 133-143.
    14. Chi, Zhexiang & Chen, Ruoran & Huang, Simin & Li, Yan-Fu & Zhou, Bin & Zhang, Wenjuan, 2020. "Multi-State System Modeling and Reliability Assessment for Groups of High-speed Train Wheels," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    15. Safaei, Fatemeh & Taghipour, Sharareh, 2024. "Integrated degradation-based burn-in and maintenance model for heterogeneous and highly reliable items," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    16. 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.
    17. Lu, Biao & Zhou, Xiaojun, 2017. "Opportunistic preventive maintenance scheduling for serial-parallel multistage manufacturing systems with multiple streams of deterioration," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 116-127.
    18. Xudan Chen & Guoxun Ji & Xinli Sun & Zhen Li, 2019. "Inverse Gaussian–based model with measurement errors for degradation analysis," Journal of Risk and Reliability, , vol. 233(6), pages 1086-1098, December.
    19. 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).
    20. Giorgio, Massimiliano & Pulcini, Gianpaolo, 2018. "A new state-dependent degradation process and related model misidentification problems," European Journal of Operational Research, Elsevier, vol. 267(3), pages 1027-1038.

    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:spr:aistmt:v:71:y:2019:i:3:d:10.1007_s10463-018-0650-4. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.