IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v93y2008i1p89-99.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832006002547
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2006.10.018?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. 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.
    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. 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.

    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. Ponchet, Amélie & Fouladirad, Mitra & Grall, Antoine, 2010. "Assessment of a maintenance model for a multi-deteriorating mode system," Reliability Engineering and System Safety, Elsevier, vol. 95(11), pages 1244-1254.
    2. Scott G. Frickenstein & Lyn R. Whitaker, 2003. "Age replacement policies in two time scales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(6), pages 592-613, September.
    3. Samrout, M. & Châtelet, E. & Kouta, R. & Chebbo, N., 2009. "Optimization of maintenance policy using the proportional hazard model," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 44-52.
    4. Van den Poel, Dirk & Lariviere, Bart, 2004. "Customer attrition analysis for financial services using proportional hazard models," European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
    5. Guo R. & Ascher H. & Love E., 2001. "Towards Practical and Synthetical Modelling of Repairable Systems," Stochastics and Quality Control, De Gruyter, vol. 16(1), pages 147-182, January.
    6. 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).
    7. Wenbin Wang & Wenjuan Zhang, 2005. "A model to predict the residual life of aircraft engines based upon oil analysis data," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(3), pages 276-284, April.
    8. Chrianna I Bharat & Kevin Murray & Edward Cripps & Melinda R Hodkiewicz, 2018. "Methods for displaying and calibration of Cox proportional hazards models," Journal of Risk and Reliability, , vol. 232(1), pages 105-115, February.
    9. M D Pandey & T Cheng & J A M van der Weide, 2011. "Finite-time maintenance cost analysis of engineering systems affected by stochastic degradation," Journal of Risk and Reliability, , vol. 225(2), pages 241-250, June.
    10. Quan, Gang & Greenwood, Garrison W. & Liu, Donglin & Hu, Sharon, 2007. "Searching for multiobjective preventive maintenance schedules: Combining preferences with evolutionary algorithms," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1969-1984, March.
    11. 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.
    12. Faisal I. Khan & Mahmoud M. Haddara & Subrata K. Bhattacharya, 2006. "Risk‐Based Integrity and Inspection Modeling (RBIIM) of Process Components/System," Risk Analysis, John Wiley & Sons, vol. 26(1), pages 203-221, February.
    13. Hong, H.P. & Zhou, W. & Zhang, S. & Ye, W., 2014. "Optimal condition-based maintenance decisions for systems with dependent stochastic degradation of components," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 276-288.
    14. Guo, Chiming & Wang, Wenbin & Guo, Bo & Si, Xiaosheng, 2013. "A maintenance optimization model for mission-oriented systems based on Wiener degradation," Reliability Engineering and System Safety, Elsevier, vol. 111(C), pages 183-194.
    15. Dongliang Lu & Mahesh D Pandey & Wei-Chau Xie, 2013. "An efficient method for the estimation of parameters of stochastic gamma process from noisy degradation measurements," Journal of Risk and Reliability, , vol. 227(4), pages 425-433, August.
    16. Esposito, Nicola & Mele, Agostino & Castanier, Bruno & GIORGIO, Massimiliano, 2023. "A hybrid maintenance policy for a deteriorating unit in the presence of three forms of variability," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    17. Mocellin, Paolo & Pilenghi, Lisa, 2023. "Semi-quantitative approach to prioritize risk in industrial chemical plants aggregating safety, economics and ageing: A case study," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    18. Saassouh, B. & Dieulle, L. & Grall, A., 2007. "Online maintenance policy for a deteriorating system with random change of mode," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1677-1685.
    19. Suo, Qinghui & Stewart, Mark G., 2009. "Corrosion cracking prediction updating of deteriorating RC structures using inspection information," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1340-1348.
    20. A Ławrynowicz, 2008. "Integration of production planning and scheduling using an expert system and a genetic algorithm," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(4), pages 455-463, April.

    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:93:y:2008:i:1:p:89-99. 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.