Minimising Equipment Downtime
OreNet Asset Intelligence uses machine learning on your existing mine data to give maintenance teams weeks of warning before critical pump and motor failures occur — no new sensors, no new hardware, no disruption.
The OreNet Difference
| Capability | Breakdown | Condition Monitoring | OreNet Asset Intelligence |
|---|---|---|---|
| Warning Time | None | Hours to Days | 2 to 8 Weeks |
| Planning Ability | Emergency Only | Very Limited | Full Planned Intervention |
| Data Required | None | Live Sensors | Existing Historian Data |
| Cost Impact | Maximum | Reduced | Minimised |
What We Do
Predictive Failure Analytics
We analyse your existing SCADA and historian data to predict pump and motor failures 2 to 8 weeks in advance.
Learn MoreML Model Development
Custom machine learning models built on your specific assets, failure history and operational data.
Learn MoreAsset Health Monitoring
Ongoing monthly monitoring with early warning alerts and health reports delivered to your maintenance team.
Learn MoreWho We Serve
OreNet partners with mining operations across Southern Africa. Our solutions are built for process plants running critical rotating equipment — specifically pumps and motors where unplanned failure carries the highest operational cost. We work with maintenance planners, reliability engineers and plant managers who need more than reactive maintenance.
Proven Results
Slurry Pump Bearing Failure
Northern Cape Mining Operation | Manganese Circuit
41-day average warning lead time on recurring bearing failures. All replacements converted from emergency callouts to planned production-window maintenance.
Read Case StudyMill Motor Winding Failure
Limpopo Platinum Concentrator | Primary Mill Circuit
Retrospective analysis identified a planned rewind 4 months prior would have cost a fraction of the emergency rewind — which, combined with 4 days of lost production, represented a significant financial loss on a single motor.
Read Case Study