Digital Stockpile Spotlight

Learn how you can track your Material Provenance through Stockpiles with our Hematite ’21 release. 

Hematite is the very latest release of our suite of decision intelligence applications built specifically for the mining industry.  The applications all use artificial intelligence (AI) and data science models to target individual mining processes and increase their efficiency, sustainability and safety.

This third spotlight in our series focuses on our Digital Stockpile app and specifically on granular material tracking.

Hematite - a decision intelligence applications built specifically for the mining industry

It’s all about Granular Material Tracking

The IntelliSense.io Digital Stockpile application provides an advanced understanding of the qualities of the material stored in stockpiles and waste piles, enabling targeted dumping and reclaiming as well as better mine planning activities.

Mine planners benefit from the granular material knowledge to provide the plant with a more homogeneous and predictable feed, with significant decreases of deviations between planned material specifications and actuals in periods when the material is sent from the stockpiles.

Differences in terms of expected versus recovered mineral content will still happen, explained by factors such as the uncertainty of the block model’s predicted properties as well as other confounding parameters such as muck pile movements and dilution resulting from blasting processes.

How then can reconciliation be used to better identify where the deviations originate from in the mining value chain to improve the effectiveness of mining operations?

 

Material Provenance Tracking through Stockpiles

When using a standard Weighted Average Model (WAM), stockpiles do not have any granularity. Not only do the material properties get averaged over large volumes and masses of material, but there is also no ability to track where any of this material comes from when it gets reclaimed to feed the plant.

Simplistic models such as First In/First Out (FIFO) or Last In/First Out (LIFO) are sometimes used, but hardly match the complex reality of stockpiling activities.

Traditional Stockpile Weighted Average Model (WAM)

Standard Weighted Average Model (WAM) Stockpile

3D Digital Stockpile

IntelliSense.io 3D GRIDS Model

To enable a proper understanding of deviations between theoretical and actual recoverable minerals using reconciled values, our Digital Stockpile application keeps track of the origin of the material found in each of the stockpile blocks.

Each stockpile material block can be traced back to its original dig zone (e.g. material dug from a blasted mining block or excavated from a stope), provides a means to reconcile material properties back to the dig zones and to better understand where deviations occur.

 

How Does it Work?

For each stockpile:

  • Each material block in the modelled stockpile retains a link to its genealogy (dig zone it originates from).
  • Blended blocks track the proportion of material coming from multiple dig zones.
  • The 3D digital block model of the stockpile available for export includes a new dig zone column representing the majority dig zone for each block (this column is left empty for historical material stockpiled prior to the modelling done with the Digital Stockpile application).
  • Material reclaimed from the stockpiles is tracked including its provenance information.

 

Benefits

The benefits of this new functionality include:

  • Being able to trace any material back to its original dig zone, allowing others to understand the origin of low/high-grade material found in different stockpile areas.
  • The ability to track the origin of material blended at the crusher from the pit and reclaimed stockpile zones to better understand the influence of upstream processes performed at the original dig zones (such as blasting) on downstream plant performance.
  • The ability to reconcile mineral recovery from the plant back to the actual dig zones, enabling a better understanding of the impact of dilution and other factors as part of the reconciliation process, and to focus process improvements accordingly.

We are very excited about the opportunities enabled by this material provenance tracking, to continue to decrease uncertainty and variations between the desired feed to the plant and the reality. Fewer deviations between theoretical and actual recoverable minerals enable our customers to have more certainty about the mine’s NPV and strengthen collaboration and alignment between planning, mine personnel and plant personnel.

Want to know more? We would be delighted to provide a live demo tailored to your requirements.

The IntelliSense.io Application Portfolio