"Predictive Model of Mineral Liberation for Geometallurgical Applications"

"In the design and operation of mineral processing plants, knowledge of the variability of ore properties and that of the expected metallurgical performance within the orebody is of great importance in order to avoid both production constraints due to inadequate design and less than expected metallurgical performance during operation. Of the many properties that determine the performance of downstream separation processes, such as flotation, gravity separation and leaching etc the liberation characteristics are of primary importance.Current methods of evaluating liberation characteristics of ores such as the use of Mineral Liberation Analyzer (MLA) and QEMSCAN techniques are expensive and suffer from the drawback that these tests are performed on comminuted particles at a given grind size and/or samples of product streams. This problem could be overcome by developing predictive models of liberation that can predict the grade distribution of comminuted products at any grind size based on texture of the parent rock. This paper discusses a procedure that has been developed to predict liberation using information obtained from a sample of the parent rock such as drill core, based on Barbery’s liberation models. The required characteristic statistical functions have been evaluated from image analysis techniques using scanning electron microscope (SEM) images of the parent rock and narrowly sized comminuted particles. Such information can then be used in a predictive model to predict or explain the variability of metallurgical performance at various grind sizes used in future operating plants. The model will predict not only the valuable mineral liberation but also gangue liberation, which will be useful to those who are looking to remove liberated gangue from comminution circuits.CITATION:Subasinghe, G K N, and Dunne, R, 2016. Predictive Model of Mineral Liberation for Geometallurgical Applications, in Proceedings The Third AusIMM International Geometallurgy Conference (GeoMet) 2016, pp 347–350 (The Australasian Institute of Mining and Metallurgy: Melbourne)."