An investigation into the effects of UG2 Ore variability on froth flotation.
South Africa is the world’s largest producer of platinum group elements (PGEs). Mining takes place in the Bushveld Complex, and recent statistics, (Mudd, 2010), showed that the UG2 reef is the main source of production, accounting for approximately 60% of world mining production. However, recovery by flotation is complicated by variations in the mineral composition, the need to grind fine and entrainment of chromite, which has an adverse effect on the subsequent smelting of the concentrate. The recovery of PGEs is variable, and it is influenced by PGE feed properties such as degree of liberation, mineral type and grain size. Conventional rougher batch flotation tests on drill core samples do not provide sufficient information for predicting plant performance. The aim of this research was to develop a rigorous method for the testing of UG2 drill core samples. A rougher-cleaner flotation test procedure was developed, and statistical tests were applied to select an appropriate model, which included entrainment of hydrophilic minerals. Fifty UG2 samples from across the Bushveld were milled at a fixed energy input, and the new test procedure was applied to derive model parameters for all samples. There was a significant variability in the PGE recovery, and typical feed characteristics such as PGE feed grade and grind did not show a clear link to the PGE recovery. This was due to the complex mineralogy of the PGE minerals and variations in ore hardness. Hence, a statistical modelling algorithm was used to determine the factors affecting PGE recovery, and an empirical model was developed, which relates the PGE recovery to feed properties. The model can be used to estimate PGE recovery based on feed properties. Samples which had a high base metal content (e.g. high nickel to iron ratio) had a high PGE recovery, and samples which were altered (e.g. high Rb/Sr ratio and loss on ignition) had a low PGE recovery. Depressant addition is used in PGE flotation to control the recovery of gangue, but it also affects the flotation of composite PGE/gangue particles. Seven of the fifty UG2 samples were selected for a more detailed investigation, using a more advanced batch flotation test and a mineralogical liberation analysis. The advanced batch flotation test was a new development, in which flotation model parameters were derived simultaneously for flotation after two stages of grinding and a combined cleaning stage. The effect of a range of depressant additions was also modelled. The floatable PGE fraction, determined from batch modelling, was linked to the mineralogical liberation analysis of the feed. The model is the first of its kind, and it makes it possible to predict the mineralogical characteristics of the feed from flotation data. A spread-sheet simulator was developed, to demonstrate how batch data (from the advanced flotation test) could be used to predict plant performance. Scale-up parameters were derived by using pilot-plant data for one of the ores. The spread-sheet was then used to optimise the plant design and depressant addition for an ore, while constraining, the mass of concentrate and the chromite content. The example showed that there was an optimum depressant addition and rougher-cleaner volume capacity for an ore. The gambit of this study was the linking of feed chemical assay and mineralogical properties to PGE recovery. The application of mineralogical tests and modelling of data from the advanced flotation test has demonstrated that the link is relatively complex.