Mining Operations
Common Types
- Conveyor belt motor current, speed, and load
- Crusher vibration and temperature monitoring
- Ore flow rate and tonnage tracking
- Environmental dust monitoring
Uncommon/Advanced Types
- Acoustic emission monitoring for early bearing/crusher damage detection
- Belt misalignment and wear detection using thermal/vision sensors
- Real-time ore size distribution via imaging systems
- Predictive lubrication scheduling based on actual wear conditions
Possible Insights
- Preventing catastrophic crusher or conveyor failures
- Reducing unplanned downtime with predictive maintenance
- Optimizing throughput by adjusting crusher settings based on ore size feedback
- Improving worker safety through dust exposure reduction
Quarries & Cement Plants
Common Types
- Temperature and vibration data from mills, kilns, and crushers
- Dust particle concentration measurements
- Motor load monitoring for fans, crushers, and conveyors
Uncommon/Advanced Types
- Kiln thermal imaging for refractory wear detection
- Real-time material moisture analysis for quality control
- Automated dust suppression system control based on sensor feedback
- AI-based energy optimization for kiln and grinding operations
Possible Insights
- Extending kiln and mill life through early defect detection
- Reducing product variability by controlling feed and process conditions
- Minimizing environmental fines by automating dust suppression
- Lowering fuel and electricity costs with process optimization
Construction Companies
Common Types
- GPS location & movement history for machinery
- Fuel consumption tracking
- Engine hours and maintenance logs
- Operator access/usage logging
Uncommon/Advanced Types
- Real-time machine health scoring using vibration, oil quality, and hydraulic pressure
- Geo-fencing alerts to prevent unauthorized use or theft
- Idle-time analysis to reduce fuel waste and emissions
- Integrated weather/environmental condition sensors for on-site safety
Possible Insights
- Lowering fuel and maintenance costs through data-driven fleet management
- Reducing theft and misuse with location and access control
- Increasing uptime through predictive maintenance alerts
- Improving safety and productivity by adapting operations to environmental conditions