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Modelling in the absence of data: a case study of fleet maintenance in a developing country

Author

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  • M I Desa

    (Universiti Teknologi Malaysia)

  • A H Christer

    (University of Salford)

Abstract

Adequate and relevant objective data for modelling maintenance decision problems are often incomplete or not readily accessible. This is particularly true in developing countries. In this paper the experience gained between 1991–95 in conducting a maintenance study of an inter-city express bus fleet in a developing country is presented. The lack of available maintenance records and operating data rendered the study the most data-starved maintenance modelling exercise the authors have met before or since. The study required the use of subjective methods to both define the problem and to estimate parameters, and the application of recently developed concepts in maintenance modelling along with snapshot analysis and delay time modelling. This imposed a structured approach to problem recognition and problem solution. The study contributed both directly and indirectly to a change in work culture and to a reduction in bus breakdown rate. The company was re-visited 5 years later specifically to seek evidence of lasting impact. Some evidence existed and is reported in the paper.

Suggested Citation

  • M I Desa & A H Christer, 2001. "Modelling in the absence of data: a case study of fleet maintenance in a developing country," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(3), pages 247-260, March.
    • Handle: RePEc:pal:jorsoc:v:52:y:2001:i:3:d:10.1057_palgrave.jors.2601107
    DOI: 10.1057/palgrave.jors.2601107
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    Citations

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    Cited by:

    1. J Guarnieri & A W Johnson & S M Swartz, 2006. "A maintenance resources capacity estimator," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(10), pages 1188-1196, October.
    2. van Oosterom, C.D. & Elwany, A.H. & Çelebi, D. & van Houtum, G.J., 2014. "Optimal policies for a delay time model with postponed replacement," European Journal of Operational Research, Elsevier, vol. 232(1), pages 186-197.
    3. Sounderpandian, Jayavel & Prasad, Sameer & Madan, Manu, 2008. "Supplies from developing countries: Optimal order quantities under loss risks," Omega, Elsevier, vol. 36(1), pages 122-130, February.
    4. Nafisah, Ibrahim & Shrahili, Mansour & Alotaibi, Naif & Scarf, Phil, 2019. "Virtual series-system models of imperfect repair," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 604-613.
    5. Percy, David F., 2002. "Bayesian enhanced strategic decision making for reliability," European Journal of Operational Research, Elsevier, vol. 139(1), pages 133-145, May.
    6. Ajith Tom James & O. P. Gandhi & S. G. Deshmukh, 2017. "Assessment of failures in automobiles due to maintenance errors," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(4), pages 719-739, December.

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