Predictive Geometallurgy: The Role of SEM Based Automated Mineralogy and Statistical Assesment for Mineral Processing

SEM-based image analyses is widely used as major analytical tool to improve the recovery of those constituents (ore minerals) that contain the major products (metals) of existing or planned mining operations and processing plants. Here three very different case studies are presented where SEM based automated mineralogical and microstructural data is combined with complementary analytical data and statistically assessed in order to predict the material behaviour during mineral processing. This approach is applied (1) on the recovery of Sn from a historic flotation tailings storage facility; (2) on by-product recovery from a chromite ore deposit; and (3) on simulated sensor based sorting. The studies were performed by interdisciplinary teams in resource characterization, minerals processing and statistical modelling.