Advanced Equipment Monitoring
The most sophisticated way to oversee your fleet, using high-fidelity data to ensure peak performance and reliability.
Learn moreIMMEE develops predictive maintenance technology for large mining equipment using machine learning models that analyse operational sensor data together with laboratory oil analysis results.
The platform has been developed through ongoing research and development work in collaboration with Cranfield University in the United Kingdom and is currently deployed in operational mining environments where it monitors heavy equipment units within active fleets.
IMMEE's predictive maintenance technology has been developed in collaboration with researchers from Cranfield University and combines oil analysis, equipment sensor data, and machine learning models to detect early signs of component degradation in large earth-moving equipment.
Initial deployments focused on CAT 994 loader fleets used during the early development and validation phase. The technology has since expanded to additional equipment categories, including haul trucks, and continues to evolve as part of IMMEE's ongoing predictive maintenance research program.
One of the UK's leading applied science and technology universities, internationally recognised for aerospace, defence, and industrial research.
Our AI-driven platform combines oil sample analysis, machine sensor connectivity, and executive dashboards to deliver predictive maintenance that increases equipment lifespan across your entire operation.
The most sophisticated way to oversee your fleet, using high-fidelity data to ensure peak performance and reliability.
Learn moreMonitor your equipment 24/7 with intuitive dashboards and intelligent alerts that keep you informed.
Learn moreEnsure maximum availability and peak performance across your fleet with our advanced monitoring capabilities.
Learn moreProtect your team by identifying risky conditions before they become incidents.
Learn moreOur platform fuses multiple data sources through patent-pending machine learning models to deliver precise, actionable predictions before failures occur.
IMMEE predictive maintenance technology is designed for the largest and most demanding equipment categories in the mining industry.
Initial validation performed on CAT 994 loader fleets. Continuous oil and sensor monitoring for drive trains, hydraulics, and powertrain systems.
Expanded deployment covering high-capacity haul trucks. Real-time engine, transmission, and suspension health monitoring across active fleets.
Bulldozers, graders, and scrapers operating in demanding open-pit and surface mining environments with high duty cycles.
Multi-unit fleet management for construction and infrastructure operators requiring enterprise-level reliability and uptime.
The IMMEE platform is currently monitoring approximately 30 heavy mining equipment units across multiple mining sites, providing real operational environments for the development and validation of predictive maintenance models.
IMMEE works with international commercial partners to distribute its predictive maintenance platform to equipment operators worldwide.
International Distribution Partner
Strategic partner for the distribution of IMMEE's predictive maintenance platform to mining equipment operators across international markets.
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