Process evaluation using the floatability component model approach, T.C. Souza Pinto, L.S. Leal Filho, A.S. Geldenhuys, and D.A. Deglon

The Brucutu iron ore mine (Minas Gerais, Brazil), is Vale`s largest iron producing operation achieving around 21 million tons by flotation of iron ore pellet feed per annum. The run of mine is mainly composed of hematite (70%) and quartz (30%). After preparation (comminution and sizing), the slurry is submitted to reverse cationic flotation of quartz under basic conditions (pH=10.5). Corn starch (500g/t) is used to depress Fe-bearing minerals and alkyl (C10) ether amine is the collector for quartz. The flotation circuit is arranged in a “coarse” section utilizing dated 28m3 square Wemco cells, and a “fine” section utilizing modern 160m3 tank cells. The “coarse” flotation circuit treats material from the deslime cyclone underflow while the “fine” circuit treats material from the deslime cyclone overflow and the pulp product from the “coarse” circuit scavenger 2 bank. Evaluation of process performance is of high importance as even small gains can lead to large improvements for this high throughput plant. Cell-by-cell samples of the froth products, selected feed and pulp-products were analyzed for flow-rate, overall chemical composition, and particle size distribution. Bank-by-bank samples of the feed, froth and pulp products were analyzed on an assay-by-size basis. In addition, the flotation cells were hydrodynamically characterized and gas dispersion parameters assessed. The detailed experimental program resulted in a thorough characterization of the process and enough information to produce a calibrated floatability component model. Longer mainline residence time results in significant Fe2O3 losses while yielding little benefit in terms of SiO2 grade. Scavenger 2 has twice the residence time of scavenger 1 while having to treat only 10% of the SiO2; resulting in high Fe2O3 recoveries to the froth and poor separation. In addition, it is shown that the Fe2O3 exhibits true flotation behavior resulting in increased Fe2O3 losses. The detailed data collection campaign coupled with in depth data analysis and modelling gives unprecedented information and highlights avenues for optimization that was previously unknown. Keywords: Froth Flotation, Process modelling, Process evaluation, Metallurgical survey