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Rolling stock maintenance strategy selection, spares parts' estimation, and replacements' interval calculation

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  • Cheng, Yung-Hsiang
  • Tsao, Hou-Lei

Abstract

The purpose of this paper is to permit an approach for: (1) selecting a maintenance strategy for rolling stock and (2) obtaining possible spare parts' quantities and replacement intervals for the components of rolling stock. The methodology adopts an analytic network process (ANP) technique for the strategy evaluation, because ANP considers the important interactions among evaluation factors. The ANP's result decides upon a proper rolling stock maintenance strategy formed by various combinations of preventive maintenance (PM) and corrective maintenance (CM). The ratio PM/CM, obtained by ANP, can help to predict spare parts' quantities of the components of rolling stock. The empirical result also indicates that preventive maintenance should be much more valued than corrective maintenance. In addition, safety is considered the most crucial factor for the selection of a rolling stock maintenance strategy. The fruit of this study serves as a reference for railway system operators when evaluating their rolling stock maintenance strategy and also when estimating their spare parts' quantities and replacement intervals for specific components of the rolling stock.

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  • Cheng, Yung-Hsiang & Tsao, Hou-Lei, 2010. "Rolling stock maintenance strategy selection, spares parts' estimation, and replacements' interval calculation," International Journal of Production Economics, Elsevier, vol. 128(1), pages 404-412, November.
    • Handle: RePEc:eee:proeco:v:128:y:2010:i:1:p:404-412
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    1. Yun, Won Young & Ferreira, Luis, 2003. "Prediction of the demand of the railway sleepers: A simulation model for replacement strategies," International Journal of Production Economics, Elsevier, vol. 81(1), pages 589-595, January.
    2. Teixeira de Almeida, Adiel, 2001. "Multicriteria decision making on maintenance: Spares and contracts planning," European Journal of Operational Research, Elsevier, vol. 129(2), pages 235-241, March.
    3. Sun, Kaibiao & Li, Hongxing, 2010. "Scheduling problems with multiple maintenance activities and non-preemptive jobs on two identical parallel machines," International Journal of Production Economics, Elsevier, vol. 124(1), pages 151-158, March.
    4. Sarkis, Joseph, 2003. "Quantitative models for performance measurement systems--alternate considerations," International Journal of Production Economics, Elsevier, vol. 86(1), pages 81-90, October.
    5. J. J. McCall, 1963. "Operating Characteristics of Opportunistic Replacement and Inspection Policies," Management Science, INFORMS, vol. 10(1), pages 85-97, October.
    6. Jardine, A. K. S. & Buzacott, J. A., 1985. "Equipment reliability and maintenance," European Journal of Operational Research, Elsevier, vol. 19(3), pages 285-296, March.
    7. Sarkis, Joseph & Sundarraj, R. P., 2002. "Hub location at Digital Equipment Corporation: A comprehensive analysis of qualitative and quantitative factors," European Journal of Operational Research, Elsevier, vol. 137(2), pages 336-347, March.
    8. Qiao, Hongzhu & Tsokos, Chris P., 1995. "Estimation of the three parameter Weibull probability distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 39(1), pages 173-185.
    9. Chelbi, Anis & Ait-Kadi, Daoud, 2001. "Spare provisioning strategy for preventively replaced systems subjected to random failure," International Journal of Production Economics, Elsevier, vol. 74(1-3), pages 183-189, December.
    10. Wang, Ling & Chu, Jian & Wu, Jun, 2007. "Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process," International Journal of Production Economics, Elsevier, vol. 107(1), pages 151-163, May.
    11. Cho, Danny I. & Parlar, Mahmut, 1991. "A survey of maintenance models for multi-unit systems," European Journal of Operational Research, Elsevier, vol. 51(1), pages 1-23, March.
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    3. Hu, Qiwei & Boylan, John E. & Chen, Huijing & Labib, Ashraf, 2018. "OR in spare parts management: A review," European Journal of Operational Research, Elsevier, vol. 266(2), pages 395-414.
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    5. Zahedi-Hosseini, Farhad & Scarf, Philip & Syntetos, Aris, 2017. "Joint optimisation of inspection maintenance and spare parts provisioning: a comparative study of inventory policies using simulation and survey data," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 306-316.
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    7. Kheybari, Siamak & Rezaie, Fariba Mahdi & Farazmand, Hadis, 2020. "Analytic network process: An overview of applications," Applied Mathematics and Computation, Elsevier, vol. 367(C).
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    9. Mahmood Shafiee & Ashraf Labib & Jhareswar Maiti & Andrew Starr, 2019. "Maintenance strategy selection for multi-component systems using a combined analytic network process and cost-risk criticality model," Journal of Risk and Reliability, , vol. 233(2), pages 89-104, April.
    10. Francesco Corman & Sander Kraijema & Milinko Godjevac & Gabriel Lodewijks, 2017. "Optimizing preventive maintenance policy: A data-driven application for a light rail braking system," Journal of Risk and Reliability, , vol. 231(5), pages 534-545, October.
    11. Carpitella, Silvia & Mzougui, Ilyas & Benítez, Julio & Carpitella, Fortunato & Certa, Antonella & Izquierdo, Joaquín & La Cascia, Marco, 2021. "A risk evaluation framework for the best maintenance strategy: The case of a marine salt manufacture firm," Reliability Engineering and System Safety, Elsevier, vol. 205(C).
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