Abstract

The depletion of high-grade ores has forced the utilization of low-grade ores. The small liberation sizes in the low-grade ores require fine grinding which is an energy intensive operation. In the present study, low-grade chromite ore bearing platinum group of elements (PGE) was used as an experimental material. The previous study concluded the liberation size of around 1–50 µm for chromite ore bearing PGE minerals. Therefore, the target product size for grinding was kept below 50 µm. The wet fine grinding experiments were performed in a vertical stirred mill. Four significant operating variables stirrer speed, grinding time, feed size, and solids concentration were investigated for their effect on the performance of stirred mills. The performance of the mill was assessed in terms of achieving small product size at lower energy consumption. The detailed investigations were carried out according to popularly adopted methods of statistical design of experiment. The results revealed that stirrer speed, grinding time, and feed size played crucial role on the performance of stirred mill. Mathematical correlations were developed for predicting product size and energy consumption. The models developed were then optimized using quadratic programing to minimize the combination of product size and energy consumption.

摘要

高品位矿石的枯竭迫使低品位矿石的利用。低品位矿石中的小游离尺寸需要精细研磨，这是一项能源密集型操作。在本研究中，使用含铂族元素 (PGE) 的低品位铬铁矿作为实验材料。先前的研究得出结论，含 PGE 矿物的铬铁矿矿石的释放尺寸约为 1–50 µm。因此，研磨的目标产品尺寸保持在 50 µm 以下。湿法细磨实验在立式搅拌磨中进行。研究了四个重要的操作变量搅拌器速度、研磨时间、进料尺寸和固体浓度对搅拌磨机性能的影响。工厂的性能是根据以较低能耗实现小尺寸产品来评估的。详细调查是根据普遍采用的实验统计设计方法进行的。结果表明，搅拌速度、研磨时间和进料粒度对搅拌磨机的性能起着至关重要的作用。数学相关性被开发用于预测产品尺寸和能源消耗。然后使用二次规划优化开发的模型，以最大限度地减少产品尺寸和能源消耗的组合。