Heterarchical comminution model for SAG mills (study)

The study, published in Minerals Engineering, introduces the Heterarchical Model, a next-generation simulation model for understanding how ore breaks down inside SAG mills.

Key Facts

  • The Heterarchical Model enables mine operators to predict SAG mill performance with greater accuracy, enabling smarter, data-driven operational decisions.
  • Findings show the optimal SAG mill efficiency occurs at around 78% critical speed and 20–30% fill level, reducing energy waste and maximising throughput.
  • By accounting for grinding media behaviour and particle dynamics, the model supports improved mill design and performance optimisation.
This study, by Molycop Vice-President of Innovation Dr Paul Shelley et al, introduces the Heterarchical Model, which enables an understanding of how ore breaks down inside SAG mills. The model is both physics-based and scalable, designed to simulate millions of particles while capturing the complex dynamics of industrial grinding.

The model is not yet complete – it doesn't include water, grinding media wear or slow mechanisms like abrasion. However, future versions will address these limitations and potentially expand into 3D simulations.

Click to read the paper.

Key innovations

  • Incorporates particle mixing, crushing and segregation.
  • Accounts for steel grinding media, which are critical in SAG mills.
  • Tracks performance spatially and over time.
  • Efficient enough for real-world application.

Snapshot of a DEM simulation of a SAG mill during operation.

Main findings

  • Grinding media significantly improves breakage compared to ore-only grinding.
  • Smaller particles migrate to the edge; larger particles and balls remain central.
  • Optimal mill efficiency is reached at ~78% critical speed and 20–30% fill level.
  • Excessive fill levels reduce grinding effectiveness.

Heterarchical discretisation of a representative volume element (RVE) along a micro-structural coordinate (m) with periodic boundary (PB) conditions.

Industry impact

  • Enables more accurate performance forecasting.
  • Improves operational decision-making for mill operators.
  • Helps reduce energy waste in a key part of mineral processing.
This research marks a significant step toward more intelligent and energy-efficient comminution in mining. It combines scientific rigour with real-world practicality to support smarter mill design and operation.

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