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Developing an optimum maintenance policy by life cycle cost analysis – a case study

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  • Khaled El-Akruti
  • Tieling Zhang
  • Richard Dwight

Abstract

This paper focuses on developing maintenance policies for critical assets to improve the production performance based on life cycle cost (LCC) analysis. A general approach is adopted for conducting the LCC analysis. The investigation is based on a case study to demonstrate how an optimum maintenance policy is determined. The relevant LCC structure in the case study is defined for the decision process which involves determination of the optimum life, repair limit and selection of materials, and trade-off between repair and replacement. The LCC analysis is based on statistical data modelling which facilitates decision-making on the optimal replacement of an asset and its remaining life. Based on the optimization and remaining life criterion, the optimal maintenance policy can be made. The results obtained from this case study include selection of the best lining material for use, determination of the optimal time for refractory lining replacement, the hot repair sequence required for maintaining the optimum condition and the repair limit for doing cold repairs before replacement, for one type of electric arc furnaces used in the steel industry.

Suggested Citation

  • Khaled El-Akruti & Tieling Zhang & Richard Dwight, 2016. "Developing an optimum maintenance policy by life cycle cost analysis – a case study," International Journal of Production Research, Taylor & Francis Journals, vol. 54(19), pages 5946-5962, October.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:19:p:5946-5962
    DOI: 10.1080/00207543.2016.1193244
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    Cited by:

    1. Rajesh Kumar Singh & Ayush Gupta, 2020. "Framework for sustainable maintenance system: ISM–fuzzy MICMAC and TOPSIS approach," Annals of Operations Research, Springer, vol. 290(1), pages 643-676, July.
    2. Mohamed Larbi Rebaiaia & Daoud Ait-kadi & Afshin Jamshidi, 2017. "Periodic replacement strategies: optimality conditions and numerical performance comparisons," International Journal of Production Research, Taylor & Francis Journals, vol. 55(23), pages 7135-7152, December.

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