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Finite-time maintenance cost analysis of engineering systems affected by stochastic degradation

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  • M D Pandey
  • T Cheng
  • J A M van der Weide

Abstract

The performance and reliability of engineering systems and structures are usually affected by uncertain degradation that occurs in service as a result of various physical and environmental processes, such as corrosion, erosion, fatigue, and creep. To maintain reliability of degrading systems, periodic inspection and preventive maintenance programmes are adopted. In the literature, the optimization of a maintenance programme is typically based on the minimization of the asymptotic cost rate. However, many engineering systems operate in a relatively short and finite time horizon in which the application of the asymptotic approximation becomes questionable. This paper presents an accurate formulation for computing the expected value and variance of the cost of a condition-based maintenance programme over a defined time horizon. A stochastic gamma process is used to model uncertain degradation. This paper emphasizes that the consideration of variance of the cost is of utmost importance in maintenance optimization, because it helps to identify a more robust (less uncertain) solution in a set of competing optimum solutions based on expected cost.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:risrel:v:225:y:2011:i:2:p:241-250
    DOI: 10.1177/1748007810393826
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    References listed on IDEAS

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    1. Nicolai, Robin P. & Dekker, Rommert & van Noortwijk, Jan M., 2007. "A comparison of models for measurable deterioration: An application to coatings on steel structures," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1635-1650.
    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. Nakagawa, T. & Mizutani, S., 2009. "A summary of maintenance policies for a finite interval," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 89-96.
    4. 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.
    5. Toshio Nakagawa, 2005. "Maintenance Theory of Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-221-8, February.
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    Citations

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    Cited by:

    1. N. C. Caballé & I. T. Castro, 2019. "Assessment of the maintenance cost and analysis of availability measures in a finite life cycle for a system subject to competing failures," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(1), pages 255-290, March.
    2. Cheng, Tianjin & Pandey, Mahesh D. & van der Weide, J.A.M., 2012. "The probability distribution of maintenance cost of a system affected by the gamma process of degradation: Finite time solution," Reliability Engineering and System Safety, Elsevier, vol. 108(C), pages 65-76.
    3. 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.
    4. Shafiee, Mahmood & Finkelstein, Maxim, 2015. "An optimal age-based group maintenance policy for multi-unit degrading systems," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 230-238.
    5. Yi Yang & John Dalsgaard Sørensen, 2019. "Cost-Optimal Maintenance Planning for Defects on Wind Turbine Blades," Energies, MDPI, vol. 12(6), pages 1-16, March.

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