Train Delay and Economic Impact of In-Service Failures of Railroad Rolling Stock

Abstract

Railcar condition directly affects the safety, the efficiency, and the reliability of freight railroad operations. Current railcar inspection practices are intended to identify defects before failure, but these practices generally do not enable preventive maintenance because manual, visual inspection is inherently limited. As a result, automated wayside condition-monitoring technologies have been developed to monitor rolling stock condition and facilitate predictive maintenance strategies. Improving the effectiveness of monitoring of railcar conditions could substantially reduce in-service failures and derailments, operational waste, and variability in rail operations and could enhance network productivity, capacity, and reliability. An analysis of the effect of lean production methods on main-line railway operations was conducted to determine the potential impact of improved railcar inspection and maintenance practices made possible by new, automated wayside technologies. Dispatch simulation software was used to quantify the magnitude and the variability of train delay as a function of both traffic level and severity of service outage. The results indicated that the annual cost caused by main-line delay was substantial compared with the annual cost of track and equipment damages from main-line derailments caused by mechanical causes. This work provided an analytical framework to assess the potential cost savings available through improved preventive maintenance strategies.