• DocumentCode
    2344088
  • Title

    Time Based Predictive Maintenance Management of UK Rail Track

  • Author

    Faiz, R.B. ; Singh, S.

  • Author_Institution
    Dept. of Comput. Sci., Loughborough Univ., Loughborough, UK
  • fYear
    2009
  • fDate
    2-4 April 2009
  • Firstpage
    376
  • Lastpage
    383
  • Abstract
    Time based preventive maintenance not only helps in uncovering defects but also commencement of these defects resulting in defects mitigation. Time based preventive maintenance helps in identifying defects in track geometry and can prevent them happening in future. Such effective time based maintenance helps in identifying trends for track geometry. One such way for effective predictive condition monitoring is by developing an efficient regression model that minimizing prediction error. Time based preventive maintenance helps in answering fundamental questions which can be either what maintenance actions to take or to replace or to repair the system to a specific state or to leave it as is or when is the next inspection to take place. The results of such research has the potential to bring benefits in terms of reducing effort and time consumed in rail track maintenance and improving reliability of train arrivals which ultimately adds in better maintenance [2].
  • Keywords
    condition monitoring; railways; regression analysis; UK rail track maintenance; defects mitigation; predictive condition monitoring; regression model; time-based predictive maintenance management; track geometry; train arrival reliability; Condition monitoring; Conference management; Geometry; Inspection; Predictive maintenance; Preventive maintenance; Rails; Railway engineering; Railway safety; Wheels;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Engineering and Information, 2009. ICC '09. International Conference on
  • Conference_Location
    Fullerton, CA
  • Print_ISBN
    978-0-7695-3538-8
  • Type

    conf

  • DOI
    10.1109/ICC.2009.70
  • Filename
    5328219