Case Study: U.S. transportation company achieves $10M in savings and prevents nearly 100 locomotive failures with Aspen Technology (Aspen Mtell)

US Railway Saves Millions by Preventing Line of Road Failures

US Transportation Company, a U.S. railway responsible for delivering customer goods safely and on time, was suffering catastrophic, undetected line-of-road (LoR) locomotive failures that can cost over $1 million each. To address this, the company engaged Aspen Technology and deployed the Aspen Mtell predictive-maintenance solution to analyze engine lube-oil laboratory data.

Aspen Technology used Aspen Mtell’s multivariate machine-learning analysis—training models on 30 “bad” actors and running Agents on up to 600 locomotives in a pilot, then scaling to more than 4,000. Within four months Aspen Technology’s solution produced 10 “saves” worth over $10 million, and after scaling detected failures on 96 engines, preventing multiple major LoR failures and associated costs.