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Health state evaluation of an item: A general framework and graphical representation

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  • Jiang, R.
  • Jardine, A.K.S.

Abstract

This paper presents a general theoretical framework to evaluate the health state of an item based on condition monitoring information. The item's health state is defined in terms of its relative health level and overall health level. The former is evaluated based on the relative magnitude of the composite covariate and the latter is evaluated using a fractile life of the residual life distribution at the decision instant. In addition, a method is developed to graphically represent the degradation model, failure threshold model, and the observation history of the composite covariate. As a result, the health state of the monitored item can be intuitively presented and the evaluated result can be subsequently used in a condition-based maintenance optimization decision model, which is amenable to computer modeling. A numerical example is included to illustrate the proposed approach and its appropriateness.

Suggested Citation

  • Jiang, R. & Jardine, A.K.S., 2008. "Health state evaluation of an item: A general framework and graphical representation," Reliability Engineering and System Safety, Elsevier, vol. 93(1), pages 89-99.
    • Handle: RePEc:eee:reensy:v:93:y:2008:i:1:p:89-99
    DOI: 10.1016/j.ress.2006.10.018
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    References listed on IDEAS

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    1. Jiang, R. & Jardine, A.K.S., 2006. "Composite scale modeling in the presence of censored data," Reliability Engineering and System Safety, Elsevier, vol. 91(7), pages 756-764.
    2. Kallen, M.J. & van Noortwijk, J.M., 2005. "Optimal maintenance decisions under imperfect inspection," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 177-185.
    3. Kordonsky, Kh. B. & Gertsbakh, I. B., 1993. "Choice of the best time scale for system reliability analysis," European Journal of Operational Research, Elsevier, vol. 65(2), pages 235-246, March.
    4. Percy, David F. & Kobbacy, Khairy A. H., 2000. "Determining economical maintenance intervals," International Journal of Production Economics, Elsevier, vol. 67(1), pages 87-94, August.
    5. Kumar, Dhananjay & Westberg, Ulf, 1997. "Maintenance scheduling under age replacement policy using proportional hazards model and TTT-plotting," European Journal of Operational Research, Elsevier, vol. 99(3), pages 507-515, June.
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    Cited by:

    1. Salazar, Jean C. & Weber, Philippe & Nejjari, Fatiha & Sarrate, Ramon & Theilliol, Didier, 2017. "System reliability aware Model Predictive Control framework," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 663-672.
    2. Fatemeh Karimi Pour & Vicenç Puig & Gabriela Cembrano, 2019. "Economic Health-Aware LPV-MPC Based on System Reliability Assessment for Water Transport Network," Energies, MDPI, vol. 12(15), pages 1-21, August.
    3. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    4. Kozłowski Edward & Kowalska Beata & Kowalski Dariusz & Mazurkiewicz Dariusz, 2019. "Survival Function in the Analysis of the Factors Influencing the Reliability of Water Wells Operation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(14), pages 4909-4921, November.
    5. Yaping Li & Enrico Zio & Ershun Pan, 2021. "An MEWMA-based segmental multivariate hidden Markov model for degradation assessment and prediction," Journal of Risk and Reliability, , vol. 235(5), pages 831-844, October.
    6. A Brint & J Bridgeman & M Black, 2009. "The rise, current position and future direction of asset management in utility industries," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 106-113, May.
    7. Jiang, R., 2010. "Optimization of alarm threshold and sequential inspection scheme," Reliability Engineering and System Safety, Elsevier, vol. 95(3), pages 208-215.
    8. Chen, Xingyu & Yang, Qingyu & Wu, Xin, 2022. "Nonlinear degradation model and reliability analysis by integrating image covariate," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    9. Jiang, R., 2013. "A multivariate CBM model with a random and time-dependent failure threshold," Reliability Engineering and System Safety, Elsevier, vol. 119(C), pages 178-185.

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