Optimisation of the reliability based preventive maintenance strategy

Conference paper


The Reliability Based Preventive Maintenance (RBPM) strategy is commonly used in industry to improve the reliability of engineering assets. In RBPM, a reliability threshold is predefined for a particular engineering asset. Whenever the reliability of the asset falls to this level, a preventive maintenance action is conducted to improve the asset’s reliability. As preventive maintenance is costly, finding optimal RBPM strategies for engineering assets, especially over a long term with multiple maintenance cycles, is of strategic importance to their owners, so as to increase their market competitiveness. Selecting an optimal RBPM strategy usually involves finding an optimal reliability threshold which enables the total expected cost, including repair cost, preventive maintenance cost and production loss, to be minimised. A number of factors such as required minimal mission time, customer satisfaction, human resources and acceptable risk levels can limit the ability of an organisation to achieve this objective. These factors are usually termed as constraints and have different influences on decision making. However, an effective tool which enables industries to make optimal RBPM decisions with consideration of the effects of these factors is still lacking. To address this issue, here we investigate these factors and identify critical constraints. Furthermore we develop an effective approach for determining the optimal RBPM strategy within the identified multiple constraints.


Preventive Maintenance Mission Time Reliability Threshold Total Expected Cost Conditional Reliability 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Sun Y, Ma L & Morris J. (2009) A practical approach for reliability prediction of pipeline systems. European Journal of Operational Research, 198(1), 210-214.MATHCrossRefGoogle Scholar
  2. 2.
    Ma L, Sun Y & Mathew J. (2007) Effects of Preventive Maintenance on the Reliability of Production Lines. In M. Xie (Eds) Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management, Singapore. pp.631-635. IEEE.Google Scholar
  3. 3.
    Sun Y, Ma L & Mathew J. (2006) Determination of optimal preventive maintenance strategy for serial production lines. In J. Mathew (Eds) Proceedings of The 1st World Congress on Engineering Asset Management, Gold Coast, Australia. pp.paper 22. Springer-Verlag.Google Scholar
  4. 4.
    Yeh RH, Kao K-C & Chang WL. (2009) Optimal preventive maintenance policy for leased equipment using failure rate reduction. Computers & Industrial Engineering, 57(1), 304-309.CrossRefGoogle Scholar
  5. 5.
    Ebeling CE. (1997) An Introduction to Reliability and Maintainability Engineering. New York: The McGraw-Hill Company, Inc.Google Scholar
  6. 6.
    Chareonsuk C, Nagarur N & Tabucanon MT. (1997) A multicriteria approach to the selection of preventive maintenance intervals. Int. J. of Production Economics, 49(1), 55-64.CrossRefGoogle Scholar
  7. 7.
    Percy DF, Kobbacy KAH & Fawzi BB. (1997) Setting preventive maintenance schedules when data are sparese. Int. J. of Production Economics, 51(2), 223-234.CrossRefGoogle Scholar
  8. 8.
    Sun Y, Ma L & Mathew J. (2004) Reliability prediction of repairable systems for single component repair. In J. Lee (Eds) Proceedings of International Conference on Intelligent Maintenance System, Arles, France. pp.S3-D. IMS.Google Scholar
  9. 9.
    Kim MJ & Makis V. (2009) Optimal maintenance policy for a multi-state deteriorating system with two types of failures under general repair. Computers & Industrial Engineering, 57(1), 298-303.CrossRefGoogle Scholar
  10. 10.
    Sun Y, Ma L & Mathew J. (2007) Prediction of system reliability for multiple component repairs. In M. Helander, M. Xie, R. Jiao & K. C. Tan (Eds) Proceedings of The 2007 IEEE International Conference on Industrial Engineering and Engineering Management, Singapore. pp.1186-1190. IEEE.Google Scholar
  11. 11.
    Holloway CA. (1979) Decision Making under Uncertainty: Models and Choices. Englewood Cliffs, NJ: Prentice-Hall, Inc.Google Scholar

Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.CRC for Integrated Engineering Asset Management, School of Engineering SystemsQueensland University of TechnologyBrisbaneAustralia
  2. 2.Faculty of Information TechnologyQueensland University of TechnologyBrisbaneAustralia

Personalised recommendations