Equipment Maintenance Intelligence
KEY IMPACT
SYSTEM DEPLOYED
- • Equipment sensors
- • Maintenance logs
- • Work orders
- • CMMS (Maintenance Management)
- • Telematics systems
- • Production tracking
SYSTEM ARCHITECTURE
Sensor Data → Intelligence Engine → Predictive Analytics
↘ Maintenance Alerts → Fleet ManagersTHE SITUATION
A mining contractor operating a large fleet of haul trucks, loaders, and excavators faced chronic unplanned downtime. Maintenance teams relied on scheduled intervals and reactive repairs when equipment failed. Maintenance logs, sensor data, and field reports were stored across multiple systems, making it difficult to detect early warning signs of equipment degradation. Downtime incidents often cascaded, delaying production schedules.
DEPLOYMENT
Mirage deployed agents that monitor equipment sensor data, maintenance logs, work orders, and field reports in real-time. Agents predict maintenance needs before failures occur, prioritize interventions based on production impact, and alert fleet managers when equipment shows signs of degradation. Maintenance workflows were integrated with existing CMMS systems.
RESULTS
Unplanned downtime fell by 64%. Maintenance cycle efficiency improved, reducing total maintenance hours by approximately 28%. Fleet productivity increased due to fewer emergency repairs interrupting production. Equipment lifespan extended as degradation was addressed proactively rather than reactively.