Stochastic modelling for the maintenance of life cycle cost of rails using Monte Carlo simulation

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dc.contributor.author Vandoorne, Rick
dc.contributor.author Grabe, P.J. (Hannes)
dc.date.accessioned 2018-05-02T06:13:28Z
dc.date.available 2018-05-02T06:13:28Z
dc.date.issued 2018-04
dc.description.abstract The need for decision support systems to guide maintenance and renewal decisions for infrastructure is growing due to tighter budget requirements and the concurrent need to satisfy reliability, availability and safety requirements. The rail of the railway track is one of the most important components of the entire track structure and can significantly influence maintenance costs throughout the life cycle of the track. Estimation of life cycle cost is a popular decision support system. A calculated life cycle cost has inherent uncertainty associated with the reliability of the input data used in such a model. A stochastic life cycle cost model was developed for the rail of the railway track incorporating imperfect inspections. The model was implemented using Monte Carlo simulation in order to allow quantification of the associated uncertainty within the life cycle cost calculated. For a given set of conditions, an optimal renewal tonnage exists at which the rail should be renewed in order to minimise the mean life cycle cost. The optimal renewal tonnage and minimum attainable mean life cycle cost are dependent on the length of inspection interval, weld type used for maintenance as well as the cost of maintenance and inspection activities. It was found that the distribution of life cycle cost for a fixed renewal tonnage followed a log-normal probability distribution. The standard deviation of this distribution can be used as a metric to quantify uncertainty. Uncertainty increases with an increase in the length of inspection interval for a fixed rail renewal tonnage. With all other conditions fixed, it was found that the uncertainty in life cycle cost increases with an increase in the rail renewal tonnage. The relative contribution of uncertainty of the planned and unplanned maintenance costs towards the uncertainty in total life cycle cost was found to be dependent on the length of inspection interval. en_ZA
dc.description.department Civil Engineering en_ZA
dc.description.librarian hj2018 en_ZA
dc.description.sponsorship Transnet Freight Rail and the Railway Safety Regulator. en_ZA
dc.description.uri http://journals.sagepub.com/home/pif en_ZA
dc.identifier.citation Vandoorne, R. & Grabe, P.J. 2018, 'Stochastic modelling for the maintenance of life cycle cost of rails using Monte Carlo simulation', Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, vol. 232, no. 4, pp. 1240-1251 en_ZA
dc.identifier.issn 0954-4097 (print)
dc.identifier.issn 2041-3017 (online)
dc.identifier.other 10.1177/0954409717714645
dc.identifier.uri http://hdl.handle.net/2263/64744
dc.language.iso en en_ZA
dc.publisher Sage en_ZA
dc.rights © IMechE 2017 en_ZA
dc.subject Maintenance en_ZA
dc.subject Monte Carlo simulation en_ZA
dc.subject Life cycle cost (LCC) en_ZA
dc.subject Modelling en_ZA
dc.subject Rail en_ZA
dc.subject Uncertainty en_ZA
dc.title Stochastic modelling for the maintenance of life cycle cost of rails using Monte Carlo simulation en_ZA
dc.type Postprint Article en_ZA


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