IDEAS home Printed from https://ideas.repec.org/a/sae/risrel/v227y2013i3p251-266.html
   My bibliography  Save this article

A track ballast maintenance and inspection model for a rail network

Author

Listed:
  • Darren Prescott
  • John Andrews

Abstract

The geometry of railway track governs the quality of the ride for passengers and, should it deteriorate to an extreme state, can become a safety concern with potential derailment. The geometry is dependent upon a number of different factors, among which is the condition of the ballast. Several options exist to control the condition of the ballast, including manual intervention, tamping and stoneblowing. Ballast condition is monitored implicitly by measuring the geometry of the railway lines using a specially equipped measurement train. By analysing the data collected by this train, the deterioration process of the railway geometry can be understood. Using this understanding, mathematical models can then be constructed, which take account of the possible maintenance and renewal options to predict the track state. This model enables decisions to be made on the best or optimal strategy for maintenance and renewal of the ballast. This article describes a model of the track maintenance process for a railway network. Owing to their flexibility, the model is formulated using a Petri net and combines the deterioration, maintenance and inspection processes for a railway network containing a number of regions. There are a limited number of maintenance machines in the network and the maintenance in each region is organised independently. The model also takes account of the fact that the maintenance of track sections with severe levels of ballast deterioration must take priority over all other maintenance in the network and allows for opportunistic maintenance to be analysed.

Suggested Citation

  • Darren Prescott & John Andrews, 2013. "A track ballast maintenance and inspection model for a rail network," Journal of Risk and Reliability, , vol. 227(3), pages 251-266, June.
  • Handle: RePEc:sae:risrel:v:227:y:2013:i:3:p:251-266
    DOI: 10.1177/1748006X13482848
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1748006X13482848
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1748006X13482848?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vileiniskis, Marius & Remenyte-Prescott, Rasa, 2017. "Quantitative risk prognostics framework based on Petri Net and Bow-Tie models," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 62-73.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Nilsson, Jan-Eric & Odolinski, Kristofer, 2020. "When should infrastructure assets be renewed?: the economic impact of cumulative tonnes on railway infrastructure," Papers 2020:4, Research Programme in Transport Economics.
    3. Wang, Wenbin, 2012. "An overview of the recent advances in delay-time-based maintenance modelling," Reliability Engineering and System Safety, Elsevier, vol. 106(C), pages 165-178.
    4. Gedik, Ridvan & Medal, Hugh & Rainwater, Chase & Pohl, Ed A. & Mason, Scott J., 2014. "Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 45-57.
    5. Li Yang & Yu Zhao & Xiaobing Ma & Qingan Qiu, 2018. "An optimal inspection and replacement policy for a two-unit system," Journal of Risk and Reliability, , vol. 232(6), pages 766-776, December.
    6. Sinisterra, Wilfrido Quiñones & Lima, Victor Hugo Resende & Cavalcante, Cristiano Alexandre Virginio & Aribisala, Adetoye Ayokunle, 2023. "A delay-time model to integrate the sequence of resumable jobs, inspection policy, and quality for a single-component system," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. Adrian Gill & Piotr Smoczyński, 2021. "Optimization of Safety System Structures in Railway Transport," Sustainability, MDPI, vol. 13(19), pages 1-15, September.
    8. Badía, F.G. & Berrade, M.D. & Lee, Hyunju, 2020. "An study of cost effective maintenance policies: Age replacement versus replacement after N minimal repairs," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    9. Jiang, R. & Chen, Zhigao, 2020. "A standard-based approach for multi-criteria performance evaluation of engineered systems," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    10. Ye, Zhisheng & Li, Zhizhong & Xie, Min, 2010. "Some improvements on adaptive genetic algorithms for reliability-related applications," Reliability Engineering and System Safety, Elsevier, vol. 95(2), pages 120-126.
    11. 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).
    12. 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).
    13. Rhayma, N. & Bressolette, Ph. & Breul, P. & Fogli, M. & Saussine, G., 2013. "Reliability analysis of maintenance operations for railway tracks," Reliability Engineering and System Safety, Elsevier, vol. 114(C), pages 12-25.
    14. 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.
    15. Macchi, Marco & Garetti, Marco & Centrone, Domenico & Fumagalli, Luca & Piero Pavirani, Gian, 2012. "Maintenance management of railway infrastructures based on reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 71-83.
    16. Yang, Li & Ma, Xiaobing & Peng, Rui & Zhai, Qingqing & Zhao, Yu, 2017. "A preventive maintenance policy based on dependent two-stage deterioration and external shocks," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 201-211.
    17. E Zio & M Librizzi & G Sansavini, 2008. "A combined Monte Carlo and cellular automata approach to the unreliability analysis of binary network systems," Journal of Risk and Reliability, , vol. 222(1), pages 31-38, March.
    18. Odolinski, Kristofer, 2019. "The impact of cumulative tonnes on track failures: An empirical approach," Papers 2019:1, Research Programme in Transport Economics.
    19. Hu, Shenping & Fang, Quangen & Xia, Haibo & Xi, Yongtao, 2007. "Formal safety assessment based on relative risks model in ship navigation," Reliability Engineering and System Safety, Elsevier, vol. 92(3), pages 369-377.
    20. Jones, B. & Jenkinson, I. & Wang, J., 2009. "Methodology of using delay-time analysis for a manufacturing industry," Reliability Engineering and System Safety, Elsevier, vol. 94(1), pages 111-124.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:risrel:v:227:y:2013:i:3:p:251-266. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.