Decision support system (DSS) for rail maintenance in heavy haul line

Rail wear and rolling contact fatigue (RCF) in rails are major contributors of operational and maintenance cost in heavy haul lines. Collection of data, modelling degradation and estimation of parameter for failure models is necessary for accurate prediction of asset conditions. Failure to do so can lead to undetected rail breaks and unsafe track leading to derailments. There is a need for developing effective maintenance strategies for cost and risk reduction.This paper focuses on collection and analysis of field data over a period of time for maintenance cost model, estimation of parameter and decision support system applicable to heavy haul lines.