IDEAS home Printed from https://ideas.repec.org/a/pal/jorsoc/v60y2009i4d10.1057_palgrave.jors.2602561.html
   My bibliography  Save this article

Justification for the next generation of maintenance modelling techniques

Author

Listed:
  • E K Doyle

    (Bruce Power LP)

  • C-G Lee

    (University of Toronto)

  • D I Cho

    (Brock University)

Abstract

Variant forms of reliability centred maintenance (RCM) have been the maintenance improving tools of choice for the last 20 years. In this case study paper, justification is made for implementing, and a path is laid out to implement, Operations Research in the form of statistical modelling as the next step forward after RCM. The lack of failure data issue has been addressed by using elicitation protocols to provide component lifetime distributions. Graphical analysis and Crowe/AMSAA (Army Materials Systems Analysis Activity) methodologies are developed as a basis for justifying expenditures on maintenance improvement initiatives. A review of historical empirical—inferential techniques dating back to WWII is presented as well as discussions of the current applicability of the same. The deregulation of the Electrical Generation Industry has produced severe restraints on the publishing of failure data. Owing to a fortuitous set of circumstances, a limited amount of data became releasable, which allowed the promise of the method to be demonstrated.

Suggested Citation

  • E K Doyle & C-G Lee & D I Cho, 2009. "Justification for the next generation of maintenance modelling techniques," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(4), pages 461-470, April.
    • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:4:d:10.1057_palgrave.jors.2602561
    DOI: 10.1057/palgrave.jors.2602561
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palgrave.jors.2602561
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1057/palgrave.jors.2602561?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. Hugh J. Miser, 1998. "The Easy Chair: What Kinds of Papers Will Contribute to a Well-Rounded View of the Conditions and Craft of OR/MS Practice?," Interfaces, INFORMS, vol. 28(6), pages 63-70, December.
    2. Percy, David F., 2002. "Bayesian enhanced strategic decision making for reliability," European Journal of Operational Research, Elsevier, vol. 139(1), pages 133-145, May.
    3. Thomas S. Wallsten & David V. Budescu, 1983. "State of the Art---Encoding Subjective Probabilities: A Psychological and Psychometric Review," Management Science, INFORMS, vol. 29(2), pages 151-173, February.
    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. 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.

    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. Thomas W. Keelin & Bradford W. Powley, 2011. "Quantile-Parameterized Distributions," Decision Analysis, INFORMS, vol. 8(3), pages 206-219, September.
    2. Brenner, Lyle & Griffin, Dale & Koehler, Derek J., 2005. "Modeling patterns of probability calibration with random support theory: Diagnosing case-based judgment," Organizational Behavior and Human Decision Processes, Elsevier, vol. 97(1), pages 64-81, May.
    3. David V. Budescu & Timothy R. Johnson, 2011. "A model-based approach for the analysis of the calibration of probability judgments," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(8), pages 857-869, December.
    4. Mel W Khaw & Luminita Stevens & Michael Woodford, 2021. "Individual differences in the perception of probability," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-25, April.
    5. Wang, Hua & Whittington, Dale, 2005. "Measuring individuals' valuation distributions using a stochastic payment card approach," Ecological Economics, Elsevier, vol. 55(2), pages 143-154, November.
    6. Sun, Yong & Ma, Lin & Mathew, Joseph & Zhang, Sheng, 2006. "An analytical model for interactive failures," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 495-504.
    7. Jeryl L. Mumpower & Gary McClelland, 2002. "Measurement Error, Skewness, and Risk Analysis: Coping with the Long Tail of the Distribution," Risk Analysis, John Wiley & Sons, vol. 22(2), pages 277-290, April.
    8. Erin Baker & Olaitan Olaleye, 2013. "Combining Experts: Decomposition and Aggregation Order," Risk Analysis, John Wiley & Sons, vol. 33(6), pages 1116-1127, June.
    9. Yuyu Fan & David V. Budescu & David Mandel & Mark Himmelstein, 2019. "Improving Accuracy by Coherence Weighting of Direct and Ratio Probability Judgments," Decision Analysis, INFORMS, vol. 16(3), pages 197-217, September.
    10. Guillaume Hollard & Sébastien Massoni & Jean-Christophe Vergnaud, 2016. "In search of good probability assessors: an experimental comparison of elicitation rules for confidence judgments," Theory and Decision, Springer, vol. 80(3), pages 363-387, March.
    11. repec:cup:judgdm:v:16:y:2021:i:2:p:323-362 is not listed on IDEAS
    12. Ali E. Abbas & David V. Budescu & Yuhong (Rola) Gu, 2010. "Assessing Joint Distributions with Isoprobability Contours," Management Science, INFORMS, vol. 56(6), pages 997-1011, June.
    13. repec:cup:judgdm:v:9:y:2014:i:1:p:1-14 is not listed on IDEAS
    14. Saemi Park & David V. Budescu, 2015. "Aggregating multiple probability intervals to improve calibration," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 10(2), pages 130-143, March.
    15. repec:cup:judgdm:v:6:y:2011:i:8:p:857-869 is not listed on IDEAS
    16. James S. Dyer & James E. Smith, 2021. "Innovations in the Science and Practice of Decision Analysis: The Role of Management Science," Management Science, INFORMS, vol. 67(9), pages 5364-5378, September.
    17. repec:cup:judgdm:v:10:y:2015:i:2:p:130-143 is not listed on IDEAS
    18. Xiaohua Zhao & Yuhuang Zheng & Fang Wan, 0. "Unrelated efforts trigger wishful winning? The impact of extraneous efforts on judgments of winning probability among Chinese consumers," Asian Business & Management, Palgrave Macmillan, vol. 0, pages 1-22.
    19. Levitin, Gregory & Xing, Liudong & Dai, Yuanshun, 2015. "Optimal loading of system with random repair time," European Journal of Operational Research, Elsevier, vol. 247(1), pages 137-143.
    20. Brenner, Lyle A., 2003. "A random support model of the calibration of subjective probabilities," Organizational Behavior and Human Decision Processes, Elsevier, vol. 90(1), pages 87-110, January.
    21. William F. Wright, 1988. "Comparaison empirique des méthodes d'inférence de probabilités subjectives," Contemporary Accounting Research, John Wiley & Sons, vol. 5(1), pages 58-69, September.
    22. Matthias Meyer & Cathérine Grisar & Felix Kuhnert, 2011. "The impact of biases on simulation-based risk aggregation: modeling cognitive influences on risk assessment," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 22(1), pages 79-105, September.
    23. Peng, Weiwen & Huang, Hong-Zhong & Li, Yanfeng & Zuo, Ming J. & Xie, Min, 2013. "Life cycle reliability assessment of new products—A Bayesian model updating approach," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 109-119.
    24. Insua, David Rios & Ruggeri, Fabrizio & Soyer, Refik & Wilson, Simon, 2020. "Advances in Bayesian decision making in reliability," European Journal of Operational Research, Elsevier, vol. 282(1), pages 1-18.

    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:pal:jorsoc:v:60:y:2009:i:4:d:10.1057_palgrave.jors.2602561. 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.palgrave-journals.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.