DescriptionSensor-based ore sorting is being increasingly used to reduce the amount of low-grade and waste material processed in mineral concentrators. This type of preconcentration provides bottom-line benefits to users by reducing the amount of energy, water and consumables, as well as reducing capital cost. Existing operations can increase metal production, while previously uneconomic deposits and low-grade stockpiles can also be exploited. The technology can also be used to separate ore types for selective processing.
The path to implementing sensor-based sorting may include:
• geometallurgical evaluation
• first inspection testing to investigate sensor response
• bench-scale testing where sensor selection is not obvious or for difficult applications
• performance testing in full scale sensor-based sorting machines
• larger scale site-based piloting with a temporary semi-mobile plant installation.
Sorting requires material to be suitably prepared and presented to the machines and typically this consists of crushing and screening to limit top size and optimise liberation. However, where material streams are suitably sized and prepared, additional equipment may not be required (e.g. the sorting of semi-autogenous grinding (SAG) Mill pebble streams).
This paper presents a case study of economic upgrading of gold ore, by preconcentrating with sensor-based ore sorting. The case study examines sorting amenability, test work, the feasibility study through to implementation, with associated flow sheet development. The development process is analysed and evaluated with a view to rationalising the process for development of future projects. In addition, limited financial modelling based on expected results is shown to illustrate the benefit to the operation.
Nielsen, B, Rohleder, J, Lehto, H and Robben, C, 2017. Sensor-based ore sorting to maximise profit in a gold operation, in Proceedings MetPlant 2017, pp 131–146 (The Australasian Institute of Mining and Metallurgy: Melbourne).