BNSF: Automatic Train Identification: Multidisciplinary Approach to Improve Safety and Efficiency
BNSF Railway has invested significant capital on various track-side detectors to monitor the condition of critical mechanical parts including wheels and bearings to enable proactive maintenance of assets. Among others, we have 1200 Hot Box Detectors (HBD’s) which measure wheel bearing temperature as trains pass by and generate 25,000 messages daily. Many HBD’s are in locations which lack Automatic Equipment Identification (AEI) devices. This presents the unique challenge of accurately matching HBD measurements with the corresponding train, car, and axle. The Operations Research team at BNSF developed a suite of descriptive, predictive, and prescriptive analytics tools that significantly improved train matching efficiency and accuracy. Compared to the legacy system, the new system has improved train matching rates from 75% to 98% and reduced processing time by 70 seconds. Additionally, these algorithms directly eliminated the need to install AEI devices (approximately $150 million) near HBD’s across our network.
BNSF Railways is competing as a 2018 Innovative Applications in Analytics Award Finalist, to see other finalists, click here.
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