IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v52y2005i3p276-284.html
   My bibliography  Save this article

A model to predict the residual life of aircraft engines based upon oil analysis data

Author

Listed:
  • Wenbin Wang
  • Wenjuan Zhang

Abstract

This paper reports on a study using the available oil monitoring information, such as the data obtained using the Spectrometric Oil Analysis Programme (SOAP), to predict the residual life of a set of aircraft engines. The relationship between oil monitoring information and the residual life is established using the concept of the proportional residual, which states that the predicted residual life may be proportional to the wear increment measured by the oil analysis programmes. Assuming such a relationship between wear and the residual life exists, we formulated a recursive prediction model for the item's residual life given measured oil monitoring information to date. A set of censored life data of 30 aircraft engines (right censored due to preventive overhaul) along with the history of their monitored metal concentration information are available to us. The metal concentration information includes many variables, such as Fe, Cu, Al, etc.; not all of them are useful, and some of them may be correlated. The principal component analysis (PCA) has been adopted to reduce the dimension of the original data set and to produce a new set of uncorrelated variables, which we shall use in the prediction model. The procedure associated with estimating model parameters is discussed. The model is fitted to the actual SOAP data from the aircraft engines, and the goodness‐of‐fit test has been carried out. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.

Suggested Citation

  • 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.
    • Handle: RePEc:wly:navres:v:52:y:2005:i:3:p:276-284
    DOI: 10.1002/nav.20072
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.20072
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nav.20072?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. Gong, Linguo & Tang, Kwei, 1997. "Monitoring machine operations using on-line sensors," European Journal of Operational Research, Elsevier, vol. 96(3), pages 479-492, February.
    2. W Wang & P A Scarf & M A J Smith, 2000. "On the application of a model of condition-based maintenance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(11), pages 1218-1227, November.
    3. A H Christer, 1999. "Developments in delay time analysis for modelling plant maintenance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(11), pages 1120-1137, November.
    4. 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. Pan, Yan & Liang, Bin & Yang, Lei & Liu, Houde & Wu, Tonghai & Wang, Shuo, 2024. "Spatial-temporal modeling of oil condition monitoring: A review," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. David Vališ & Libor Žák & Ondřej Pokora, 2015. "Contribution to system failure occurrence prediction and to system remaining useful life estimation based on oil field data," Journal of Risk and Reliability, , vol. 229(1), pages 36-45, February.
    3. Akram Khaleghei & Viliam Makis, 2015. "Model parameter estimation and residual life prediction for a partially observable failing system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(3), pages 190-205, April.
    4. W Wang, 2011. "Overview of a semi-stochastic filtering approach for residual life estimation with applications in condition based maintenance," Journal of Risk and Reliability, , vol. 225(2), pages 185-197, June.
    5. Liu, Yingchao & Hu, Xiaofeng & Zhang, Wenjuan, 2019. "Remaining useful life prediction based on health index similarity," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 502-510.
    6. Xiaosheng, Si & Li, Huiqin & Zhang, Zhengxin & Li, Naipeng, 2024. "A Wiener-process-inspired semi-stochastic filtering approach for prognostics," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    7. Ying Liao & Yisha Xiang & Min Wang, 2021. "Health assessment and prognostics based on higher‐order hidden semi‐Markov models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(2), pages 259-276, March.

    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. Xuejuan Liu & Wenbin Wang & Rui Peng & Fei Zhao, 2015. "A delay-time-based inspection model for parallel systems," Journal of Risk and Reliability, , vol. 229(6), pages 556-567, December.
    2. Cavalcante, C.A.V. & Lopes, R.S. & Scarf, P.A., 2018. "A general inspection and opportunistic replacement policy for one-component systems of variable quality," European Journal of Operational Research, Elsevier, vol. 266(3), pages 911-919.
    3. Wang, Wenbin, 2011. "An inspection model based on a three-stage failure process," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 838-848.
    4. Wang, Wenbin, 2012. "An overview of the recent advances in delay-time-based maintenance modelling," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 165-178.
    5. Hui-Ying Wang & Zhao-Qiang Wang, 2022. "A condition-based preventive replacement policy with imperfect manual inspection for a two-stage deterioration process," Journal of Risk and Reliability, , vol. 236(2), pages 225-236, April.
    6. Percy, David F., 2002. "Bayesian enhanced strategic decision making for reliability," European Journal of Operational Research, Elsevier, vol. 139(1), pages 133-145, May.
    7. Qinming Liu & Ming Dong & Wenyuan Lv & Chunming Ye, 2019. "Manufacturing system maintenance based on dynamic programming model with prognostics information," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1155-1173, March.
    8. Scarf, Philip A. & Cavalcante, Cristiano A.V., 2010. "Hybrid block replacement and inspection policies for a multi-component system with heterogeneous component lives," European Journal of Operational Research, Elsevier, vol. 206(2), pages 384-394, October.
    9. W Wang, 2003. "Modelling condition monitoring intervals: A hybrid of simulation and analytical approaches," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 273-282, March.
    10. 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.
    11. W Wang, 2007. "A prognosis model for wear prediction based on oil-based monitoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(7), pages 887-893, July.
    12. 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.
    13. Deprez, Laurens & Antonio, Katrien & Boute, Robert, 2021. "Pricing service maintenance contracts using predictive analytics," European Journal of Operational Research, Elsevier, vol. 290(2), pages 530-545.
    14. Zhang, Fengxia & Shen, Jingyuan & Liao, Haitao & Ma, Yizhong, 2021. "Optimal preventive maintenance policy for a system subject to two-phase imperfect inspections," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
    15. P A Scarf & H A Majid, 2011. "Modelling warranty extensions: a case study in the automotive industry," Journal of Risk and Reliability, , vol. 225(2), pages 251-265, June.
    16. 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.
    17. Wang, Wenbin & Banjevic, Dragan & Pecht, Michael, 2010. "A multi-component and multi-failure mode inspection model based on the delay time concept," Reliability Engineering and System Safety, Elsevier, vol. 95(8), pages 912-920.
    18. Driessen, J.P.C. & Peng, H. & van Houtum, G.J., 2017. "Maintenance optimization under non-constant probabilities of imperfect inspections," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 115-123.
    19. J Ansell & T Archibald & J Dagpunar & L Thomas & P Abell & D Duncalf, 2003. "Analysing maintenance data to gain insight into systems performance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(4), pages 343-349, April.
    20. 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.

    More about this item

    Statistics

    Access and download statistics

    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:wly:navres:v:52:y:2005:i:3:p:276-284. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.