Metallurgical Yield Risk Assessment
VBKOM’s metallurgical division assisted a major mining client to model the expected variability of their product yield in comparison to the results modelled using their beneficiation algorithms. The mine in question intends to invest capital to modify their processing plants in order to process previously classified waste material. The business case for this modification was previously built only on outcomes predicted by their empirical algorithms. As such the likely yields resulting from run-of-mine (‘RoM’) qualities for specific different ore types were modelled and applied across the entire ore body (i.e. a quantitative yield risk assessment).
The yield study entailed running two scenarios across each of the two processing plants (base case and the investment case). Each scenario and each processing plant had unique characteristics in terms of feed distribution, separation density, throughput, and yield. In preparing for the simulation, actual beneficiation sample data were utilised to determine the upper and lower boundaries for the different ore type’s yield distributions. In the end 5000 iterations were simulated on each scenario and a total of 48 simulations were run and analysed as part of the yield study.
Yield comparison graphs between the algorithms and the Monte Carlo simulation as well as weighted yield distribution curves from the Monte Carlo simulation were produced for each combination with 18 outputs per combination (i.e. a total of 72 Monte Carlo weighted yield output values). The same process was followed with the beneficiation algorithm data.
The value to the client was that the outcomes of the simulation enabled the client to validate their yield assumptions in their Life-of-Mine ('LoM') plan and, in turn, mitigate the risk in their investment decision.