Case Study: DataMind AI™ Detects Lubrication Fault in Ventilation Fan
July 2, 2025
At a large coal mining operation, DataMind AI™ identified early-stage friction in a ventilation fan responsible for maintaining airflow to underground areas – well before any conventional alarms were triggered.
Using sensor fusion and advanced envelope analysis, the system pinpointed the root cause: a jammed grease cartridge that left the bearing unlubricated. This failure mode – undetectable through standard monitoring – was flagged automatically and escalated to a critical alert.
As a result, the site avoided 7 hours of unplanned downtime, saved approximately $210,000, and preserved the safe operation of critical ventilation systems -showcasing the power of precise diagnostics and timely intervention when it matters most.
Conclusion
This case demonstrates how DataMind AI™ empowers mining operations with real-time diagnostics that go beyond detection – delivering accurate root cause insights, preventing equipment failure, and enabling smarter, safer maintenance decisions.
