Research thrust 03

Utilisation, Performance and Condition Monitoring of Mechanised Mining Equipment

Using condition monitoring, hybrid models and digital twins to turn equipment data into actionable insight on utilisation, performance, health and safety.

This thrust uses equipment measurements to understand how mechanised mining machines are being used, how well they are performing and how their condition is changing. RAMMS combines condition monitoring, physics-based models, machine intelligence and operational data to make that evidence interpretable.

Digital twins are a recurring implementation framework. Rather than static digital replicas, the twins are synchronised with measurements and directed toward an actionable intervention: safer braking, better maintenance, improved productivity or more reliable navigation.

Research spans LHD and engine models, machine vision, terrain-aware traction estimation, shaft-conveyance dynamics, conveyor systems and fault-sensitive equipment models. Those digital twins also feed the other two thrusts with better representations of machine capability and rock-machine interaction.