In mineral processing, gravity separation circuits play a formidable role in the recovery of valuable metals/minerals due to their high efficiency and relatively low operational costs. However such processes are sensitive to changes in feed rate, flow rate, and pulp density( % Solids).
Response time to feed variability
Operators will often face challenges of adjusting the splitter settings in time, once they notice changes in the properties of the feed stream. Without the ability to know what will happen in the near future (having a prediction), heavy metal losses cannot be avoided. This model, therefore, allows the operators to be prepared and have full control over the circuit no matter what happens in the upstream processes.
The spiral prediction model focuses on the spiral circuit, which is a gravity separation process for recovering heavy minerals/metals such as Zirconium Oxide, Tungsten minerals, etc. It predicts certain process variables such as:
Spiral feed mass flow rate (tons/hour)
Spiral feed Volumetric flow rate (m3/hour)
Spiral feed percent solids (% - Percentage of solids in a mixture of water and solids)
Spiral product heavy metal concentrate volumetric flow (m3/hour)
Spiral product heavy metal concentrate percent solids (%)
Spiral product heavy metal concentrate mass flow rate (tons/hour)
Potential reduction of heavy metal (valuable component) losses to the tailings stream, thus giving higher returns on investment.
Reduces human decision-making, allowing consistent production regardless of shift.
Improved process efficiency and recovery.
Optimal resource utilization (Water, power, etc)
All these predicted metrics or variables can give significant insight into the performance or efficiency of the circuit and metal recovery.