Rail Hot Box Detector Analytics for improved safety
Advanced analytics with predictive models help railroads to move from unplanned to planned maintenance
A leading north American Class I railroads wanted to improve their rail safety by predicting bearing failures. Early warning and detection of the derailment can significantly save costs. CloudMoyo designed a solution to harness data from all hot box detectors to provide real-time alerts around temperature to the rail mechanical desk, enabling prediction of wheel bearing failures for pre-bad ordering of cars.
The Hot Box detector analytics solution helped them overcome challenges like:
1. High frequency of inspection
2. Manual inspection
3. Equipment failure
4. Poor detection of derailment
5. Unnecessary delays caused by false alarm
Download this case study to know more about how CloudMoyo solution for hot box detector helped to improve rail safety
Get a detailed case study here:
CloudMoyo empowers rail and transportation companies to gain greater insights, unlock efficiencies, and improve agility in operations, revenue and asset management as well as critical areas of safety, crew scheduling and maintenance. Combined with deep rail industry expertise, our cloud-based, AI-driven solutions leverage cutting edge technology to reimagine railroad digitization.
14711 NE 29th Pl, Suite 111, Bellevue, WA – 98007 U.S.