Thickener Case Study

Client: Gold — Copper Mine, Chile

Project Objective

The project objective for was to model and optimize the thickener circuit in real time, identify the root cause of variability and continuously predict set-point recommendations for optimal predictive process control.


The existing thickener circuit Expert System didn’t enable continuous set point changes based on the type of materials entering the thickener — resulting in an inability of the operations team to take pre-emptive action to minimize variance at the circuit, with action being taken only after the event. This resulted in a low underflow % solids and water recovery, and high flocculant consumption.


The Thickener Circuit Optimisation application was implemented at the mine. The project integrated data from SCADA & other control systems (including upstream data) with advanced statistical data modelling, machine learning algorithms and first principle models to derive a digital model of the thickener circuit that can predict and simulate future performance of the circuit under various feed conditions and deliver continuous optimized control recommendations that result in;

  • Delivery of predicted material composition and mineralogy input to the thickener circuit.
  • Stable underflow % solid.
  • Online thickener circuit simulator.

Fig 1: Screenshot of the Thickener Operator Solution Panel.


  • Decreased variability in the thickener circuit operation.

  • Enhanced water recovery at the thickener circuit

  • Reduced equipment downtime due to stricter torque constraints.

  • Next-generation virtual sensors which replace crucial missing instrumentation.

  • Increased operational staff availability by reducing the time to collect previously siloed data.

  • Increased internal operator training through the brains.vos simulator.

  • Payback period shorter than 12 months with projected direct savings calculated at $400k in the first year alone.

 Fig 2: Screenshot of the Thickener application performance Solution Panel.

Mine to Market: Value Chain Optimization

Powered and connected together by the platform, the Thickener Optimization Application is one of a suite of real-time decision-making applications that uses Artificial Intelligence (AI) to optimize each process; from mine-to-market.

Our Material flow model connects these applications together to drive even greater efficiency gains.

The Application Portfolio

Mine to Market: Value Chain Optimization

The Stockpile & Inventory Optimization Application is one of a suite of real-time decision-making applications that uses AI to optimize each process; from mine to market.

Our Material Handling model connects these applications to drive even greater efficiency.

Our process optimization apps can be deployed on a specific process bottleneck or expanded across the entire value chain. They are powered by our Industrial AI Decision Intelligence Platform,

Stockpile and Inventory Optimization

Stockpile & Inventory Optimization

Grinding Optimization App

Grinding Optimization

Thickener Circuit Optimization

Thickener Optimization

Flotation Circuit

Flotation Optimization

Solvent Extraction Optimization App

Solvent Extraction (SX) Optimization

Leaching Optimization App

Leaching Optimization