Abstract
The Pau Branco mine supplies two blast furnaces with iron ore lumps, and currently, charcoal consumption for pig iron production accounts for 47% of the blast furnaces' operational cost. A geometallurgical model is presented to support an economic study considering reserve volumes, product quality, and operational costs based on the metallurgical performance of different iron ore typologies. Sample analysis provides values required in the model. From the model, an alternative production plan is presented with a positive impact of USD 25.6M over the current net present value of the mining/mill system.
Highlights
Higher environmental and socioeconomic demands in the exploitation of future mineral resources require comprehensive knowledge of ore bodies even in the early stages of the mining process
This paper describes the development of a geometallurgical model for Pau Branco Mine’s iron ore lumps
The concentration factors (CFs) obtained through industrial plant processes were coherent, compared to that obtained in the laboratory, indicating the representativeness of the typology’s definition and sampling
Summary
Higher environmental and socioeconomic demands in the exploitation of future mineral resources require comprehensive knowledge of ore bodies even in the early stages of the mining process. Geometallurgy combines geological and mineral processing information to create a spatial model for production planning and management. A geometallurgical model can be established with three sub-models: a geological model, a process model, and a production model. The process model must be capable of receiving the information from the geological model and forecasting the metallurgical response for any given geological unit (sample, ore block, or geometallurgical domain). These two models are combined into a production model capable of handling the time frame and different scenarios for ore mining and processing. The production model returns figures such as the amount of final product in a given time, production value, and production costs (Lund et al, 2013, Lamberg, 2011)
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