The value of an ore body lies in its contained metal, but capturing that value depends on getting the right material to the right destination. Ore tracking technology is closing the gap between geological models and material handling reality, delivering measurable improvements in recovery and grade.

The Dilution Problem

Dilution – waste material mixed with ore – directly reduces processing efficiency. Every tonne of waste that enters the processing plant consumes capacity while contributing nothing to recovery. At current treatment costs, dilution has significant economic impact.

Traditional approaches to ore/waste discrimination relied on geological models, visual identification, and periodic sampling. These methods provided imprecise boundaries and delayed feedback. Material was often misclassified, sending ore to waste dumps and waste to the mill.

Modern ore tracking systems address dilution through better data, faster feedback, and tighter control.

Blast Hole Sampling and Analysis

Grade control begins before blasting. Blast hole samples provide the first direct measurement of material that geological models have predicted.

Continuous sampling systems capture cuttings from every blast hole automatically. This comprehensive coverage replaces selective sampling approaches that could miss grade variations.

On-site analysis using portable analysers provides rapid results. Waiting days for laboratory assays delays blast design and dig planning. On-site analysis enables same-day decision making.

Blast hole database systems integrate sampling results with spatial coordinates. Visualisation tools display grade distributions across blast patterns, enabling dig boundary refinement before material is disturbed.

Reconciliation workflows compare blast hole data with geological models, identifying where models need updating. This feedback loop improves future predictions.

Dig Face Sensing Technology

At the dig face, sensing technology provides additional information to guide excavation.

On-excavator sensors can measure material properties in real time. Technologies include prompt gamma neutron activation analysis (PGNAA), near-infrared spectroscopy, and other sensing approaches suited to different commodities.

GPS-guided excavation ensures operators dig planned boundaries accurately. Displays in the excavator cabin show planned dig limits overlaid on current position, enabling precise boundary control.

Material classification at loading assigns destination routing – ore to the mill, waste to the dump, marginal material to stockpiles. This decision point determines whether value is captured or lost.

Haul Tracking Systems

Once material is loaded, tracking continues through haulage.

RFID and GPS tracking records which truck loaded which material from which location. This creates an audit trail linking processed material back to its source.

Weigh-in-motion systems measure payload as trucks pass. Combined with grade estimates, this enables real-time metal accounting through the mining chain.

Truck assignment optimisation routes trucks to appropriate destinations based on loaded material type. Dynamic routing responds to changing conditions – a truck initially assigned to the ROM pad might be redirected if better information becomes available.

Material stockpile management tracks additions and withdrawals from stockpiles. Stockpiles often accumulate material of varying grade, and managing these inventories requires knowing what’s where.

Processing Plant Integration

Ore tracking connects mining operations with processing plants.

ROM pad characterisation provides advance notice of material characteristics. If the plant knows harder or lower-grade material is coming, it can adjust operating parameters proactively.

Blend management optimises feed characteristics. Stockpile systems with multiple grade categories enable blending that achieves target feed grades more consistently than single-source feed.

Metallurgical performance correlation links processing outcomes back to material sources. Understanding which ore sources deliver good recovery and which cause problems enables better mining prioritisation.

Real-time grade measurement at the plant entrance verifies incoming material grade. Discrepancies between predicted and measured grades trigger investigation and model updates.

Data Integration Platforms

Ore tracking generates substantial data that must be integrated and analysed.

Unified data platforms bring together geological models, sampling results, equipment tracking, and processing data. This integration enables analysis that would be impossible with siloed information systems.

Visualisation tools display material flows and grade distributions in intuitive formats. Three-dimensional views of ore blocks colour-coded by grade help geologists and mining engineers understand grade distributions.

Performance dashboards track key metrics – dilution percentage, ore loss, grade variability, reconciliation accuracy. These metrics enable management attention to areas needing improvement.

Predictive analytics can identify patterns that affect ore tracking performance. Machine learning approaches may detect subtle factors that influence dilution or recovery that wouldn’t be apparent from simple analysis.

Underground Applications

Underground mining presents different ore tracking challenges and opportunities.

Development face sampling characterises material as mining advances. Unlike surface mining where blast holes precede mining, underground development often samples after excavation.

Stope boundary optimisation uses grade control information to adjust mining limits. Taking a little more waste to capture additional ore, or leaving marginal material in place, can optimise value extraction.

Ore pass tracking monitors material flow through ore passes and handling systems. Mixing in ore passes can complicate grade tracking, requiring statistical approaches to estimate delivered grades.

Batch tracking associates processing batches with source locations. This enables metallurgical performance analysis at the stope level.

Economic Impact

The economics of improved ore tracking are compelling across multiple dimensions.

Reduced dilution decreases processing costs per tonne of metal produced. Plants process less waste, reducing reagent consumption, energy use, and wear.

Reduced ore loss captures value that would otherwise be left behind or sent to waste. Every percent of ore recovered from the waste stream contributes directly to revenue.

Improved feed consistency enables more stable plant operation. Consistent feed grades allow optimised operating parameters rather than continuous adjustment.

Better planning from accurate grade information improves scheduling and production forecasting. Knowing what’s coming enables better resource allocation.

Implementation Considerations

Ore tracking systems require investment in technology, training, and process change.

Equipment integration can be challenging. Sensors must function reliably in harsh mining environments. Data transmission from mobile equipment requires robust communication systems.

Workflow changes affect operators, geologists, and engineers. New procedures must be practical to implement consistently. Training ensures personnel understand and follow ore tracking protocols.

Change management addresses cultural factors. If frontline personnel don’t see value in ore tracking, compliance will suffer. Demonstrating benefits and involving workers in system design improves adoption.

Continuous improvement mindset recognises that ore tracking systems improve over time. Initial implementations rarely achieve full potential immediately. Systematic refinement based on operating experience delivers improving results.

The Future of Ore Tracking

Ore tracking technology continues advancing. Sensor capabilities improve, data systems become more sophisticated, and integration deepens.

The ultimate vision is complete material visibility from in-situ ore body through to final product. Every tonne traced, every movement recorded, every decision supported by data. This vision is increasingly achievable with current technology.

Mining operations that master ore tracking will outperform those that don’t. The value proposition is clear: better information enables better decisions, and better decisions improve economic outcomes. In an industry where margins matter, ore tracking technology delivers measurable advantage.