To improve traffic safety by reducing the number of failures of traction rolling stock, save time on maintenance and repairs, and reduce unproductive locomotive downtime.
To use Clover SmartMaintenance — a system for risk-based MRO management based on the actual condition of equipment, AI technologies and Big Data analytics.
It is necessary to reduce the number of failures on the line and the downtime at the maintenance service of electric locomotives of 2(3,4)ES5K series operated at the Eastern site of JSC Russian Railways.
Sequence of actions:
1. Providing automatic analysis of data received from the microprocessor control systems of electric locomotives for the purpose of assigning additional works and creating work orders before the locomotive arrives for service maintenance.
2. Adapting the forecast models of the technical condition of equipment to prevent failures on the line.
3. Ensuring automatic objective quality control for the execution of additional works and troubleshooting.
4. Ensuring the prioritization of sending the locomotives for service maintenance based on their technical condition.