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A stochastic model for railway track asset management

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  • Andrews, John
  • Prescott, Darren
  • De Rozières, Florian

Abstract

The determination of the strategy to ensure that the geometry for railway track is kept within acceptable limits, in a cost effective manner, is a complex process. It requires the simultaneous consideration of the activities which govern inspection, maintenance and renewal. In addition to this the geometry degradation process is dependent upon the maintenance history. The condition where the track geometry is shown to have deteriorated to a level where intervention is required can be improved using a tamping machine. Tamping is carried out by a special train which measures the geometry of the rails, predicts the correction needed, lifts the rails to the required position, inserts tines into the ballast either side of the sleepers and packs the ballast such that the correct rail position is attained. Whilst improving the geometry this process has the disadvantage that it also breaks the ballast which accelerates the track geometry degradation and reduces the time between interventions.

Suggested Citation

  • Andrews, John & Prescott, Darren & De Rozières, Florian, 2014. "A stochastic model for railway track asset management," Reliability Engineering and System Safety, Elsevier, vol. 130(C), pages 76-84.
    • Handle: RePEc:eee:reensy:v:130:y:2014:i:c:p:76-84
    DOI: 10.1016/j.ress.2014.04.021
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    References listed on IDEAS

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    1. Podofillini, Luca & Zio, Enrico & Vatn, Jørn, 2006. "Risk-informed optimisation of railway tracks inspection and maintenance procedures," Reliability Engineering and System Safety, Elsevier, vol. 91(1), pages 20-35.
    2. L M Quiroga & E Schnieder, 2012. "Monte Carlo simulation of railway track geometry deterioration and restoration," Journal of Risk and Reliability, , vol. 226(3), pages 274-282, June.
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    Cited by:

    1. Andrews, John & Tolo, Silvia, 2023. "Dynamic and dependent tree theory (D2T2): A framework for the analysis of fault trees with dependent basic events," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    2. Chiachío, Juan & Chiachío, Manuel & Prescott, Darren & Andrews, John, 2019. "A knowledge-based prognostics framework for railway track geometry degradation," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 127-141.
    3. Lee, Juseong & Mitici, Mihaela, 2020. "An integrated assessment of safety and efficiency of aircraft maintenance strategies using agent-based modelling and stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    4. Hui Shang & Christophe Bérenguer & John Andrews, 2017. "Delayed maintenance modelling considering speed restriction for a railway section," Journal of Risk and Reliability, , vol. 231(4), pages 411-428, August.
    5. Sedghi, Mahdieh & Kauppila, Osmo & Bergquist, Bjarne & Vanhatalo, Erik & Kulahci, Murat, 2021. "A taxonomy of railway track maintenance planning and scheduling: A review and research trends," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    6. Andrade, A.R. & Teixeira, P.F., 2015. "Statistical modelling of railway track geometry degradation using Hierarchical Bayesian models," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 169-183.
    7. Wang, Yifei & He, Rui & Tian, Zhigang, 2023. "Opportunistic condition-based maintenance optimization for electrical distribution systems," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    8. Alice Consilvio & José Solís-Hernández & Noemi Jiménez-Redondo & Paolo Sanetti & Federico Papa & Iñigo Mingolarra-Garaizar, 2020. "On Applying Machine Learning and Simulative Approaches to Railway Asset Management: The Earthworks and Track Circuits Case Studies," Sustainability, MDPI, vol. 12(6), pages 1-24, March.
    9. Fecarotti, Claudia & Andrews, John & Pesenti, Raffaele, 2021. "A mathematical programming model to select maintenance strategies in railway networks," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    10. Whiteley, M & Dunnett, S & Jackson, L, 2020. "Simulation of polymer electrolyte membrane fuel cell degradation using an integrated Petri Net and 0D model," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    11. Cheng, Ruijun & Zhou, Jin & Chen, Dewang & Song, Yongduan, 2016. "Model-based verification method for solving the parameter uncertainty in the train control system," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 169-182.
    12. Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    13. Andrews, John & Fecarotti, Claudia, 2017. "System design and maintenance modelling for safety in extended life operation," Reliability Engineering and System Safety, Elsevier, vol. 163(C), pages 95-108.
    14. Arthur H.A. Melani & Carlos A. Murad & Adherbal Caminada Netto & Gilberto F.M. Souza & Silvio I. Nabeta, 2019. "Maintenance Strategy Optimization of a Coal-Fired Power Plant Cooling Tower through Generalized Stochastic Petri Nets," Energies, MDPI, vol. 12(10), pages 1-28, May.
    15. Alice Consilvio & Angela Febbraro & Rossella Meo & Nicola Sacco, 2019. "Risk-based optimal scheduling of maintenance activities in a railway network," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 8(5), pages 435-465, December.
    16. Saleh, Ali & Remenyte-Prescott, Rasa & Prescott, Darren & Chiachío, Manuel, 2024. "Intelligent and adaptive asset management model for railway sections using the iPN method," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    17. Thorsten Neumann & Beate Dutschk & René Schenkendorf, 2019. "Analyzing uncertainties in model response using the point estimate method: Applications from railway asset management," Journal of Risk and Reliability, , vol. 233(5), pages 761-774, October.

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