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Perspectives on trading cost and availability for corrective maintenance at the equipment type level

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  • Erkoyuncu, John Ahmet
  • Khan, Samir
  • Eiroa, Alexandre López
  • Butler, Nigel
  • Rushton, Keith
  • Brocklebank, Simon

Abstract

Characterising maintenance costs has always been challenging due to a lack of accurate prior cost data and the uncertainties around equipment usage and reliability. Since preventive maintenance does not completely prevent corrective repairs in demanding environments, any unscheduled maintenance can have a large impact on the overall maintenance costs. This introduces the requirement to set up support contracts with minimum baseline solutions that warrant the target demand within certain costs and risks. This article investigates a process that has been developed to estimate performance based support contract costs attributed to corrective maintenance. These can play a dominant role in the through-life support of high values assets. The case context for the paper is the UK Ministry of Defence. The developed approach allows benchmarking support contract solutions, and enabling efficient planning decisions. Emphasis is placed on learning from feedback, testing and validating current methodologies for estimating corrective maintenance costs and availability at the Equipment Type level. These are interacting sub-equipment's that have unique availability requirements and hence have a much larger impact on the capital maintenance expenditure. The presented case studies demonstrate the applicability of the approach towards adequate savings and improved availability estimates.

Suggested Citation

  • Erkoyuncu, John Ahmet & Khan, Samir & Eiroa, Alexandre López & Butler, Nigel & Rushton, Keith & Brocklebank, Simon, 2017. "Perspectives on trading cost and availability for corrective maintenance at the equipment type level," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 53-69.
    • Handle: RePEc:eee:reensy:v:168:y:2017:i:c:p:53-69
    DOI: 10.1016/j.ress.2017.05.041
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    References listed on IDEAS

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    1. K. Sadananda Upadhya & N. K. Srinivasan, 2005. "System simulation for availability of weapon systems under various missions," Systems Engineering, John Wiley & Sons, vol. 8(4), pages 309-322.
    2. Khan, Samir & Phillips, Paul & Jennions, Ian & Hockley, Chris, 2014. "No Fault Found events in maintenance engineering Part 1: Current trends, implications and organizational practices," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 183-195.
    3. Ahmet Erkoyuncu, John & Khan, Samir & Hussain, Syed Mohammed Fazal & Roy, Rajkumar, 2016. "A framework to estimate the cost of No-Fault Found events," International Journal of Production Economics, Elsevier, vol. 173(C), pages 207-222.
    4. de Jonge, Bram & Klingenberg, Warse & Teunter, Ruud & Tinga, Tiedo, 2016. "Reducing costs by clustering maintenance activities for multiple critical units," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 93-103.
    5. Faccio, M. & Persona, A. & Sgarbossa, F. & Zanin, G., 2014. "Industrial maintenance policy development: A quantitative framework," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 85-93.
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    Citations

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    Cited by:

    1. Vrignat, Pascal & Kratz, Frédéric & Avila, Manuel, 2022. "Sustainable manufacturing, maintenance policies, prognostics and health management: A literature review," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Stevan Djenadic & Dragan Ignjatovic & Milos Tanasijevic & Ugljesa Bugaric & Ivan Jankovic & Tomislav Subaranovic, 2019. "Development of the Availability Concept by Using Fuzzy Theory with AHP Correction, a Case Study: Bulldozers in the Open-Pit Lignite Mine," Energies, MDPI, vol. 12(21), pages 1-18, October.
    3. Li, Yao & He, Yihai & Liao, Ruoyu & Zheng, Xin & Dai, Wei, 2022. "Integrated predictive maintenance approach for multistate manufacturing system considering geometric and non-geometric defects of products," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    4. Youssef Sadraoui & Mohamed Er-ratby & Moulay Saddik Kadiri & Abdessamad Kobi, 2024. "Optimization of Quality Process Control and Preventive Maintenance Strategy: A Case Study," SN Operations Research Forum, Springer, vol. 5(4), pages 1-58, December.
    5. Wu, Shaomin & Do, Phuc, 2017. "Editorial," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 1-3.
    6. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    7. Tao, Xin & Mårtensson, Jonas & Warnquist, Håkan & Pernestål, Anna, 2022. "Short-term maintenance planning of autonomous trucks for minimizing economic risk," Reliability Engineering and System Safety, Elsevier, vol. 220(C).
    8. Shi, Yan & Lu, Zhenzhou & Huang, Hongzhong & Liu, Yu & Li, Yanfeng & Zio, Enrico & Zhou, Yicheng, 2022. "A new preventive maintenance strategy optimization model considering lifecycle safety," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    9. Jingyi Zhao & Chunhai Gao & Tao Tang, 2022. "A Review of Sustainable Maintenance Strategies for Single Component and Multicomponent Equipment," Sustainability, MDPI, vol. 14(5), pages 1-22, March.

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