Milling Result Prediction

Matos Camacho, S.; Leißner, T.; Atanasova, P.; Kamptner, A.; Rudolph, M.; Peuker, U. A.; Boogaart, K. G. van den

Milling Result Prediction

Matos Camacho, S.; Leißner, T.; Atanasova, P.; Kamptner, A.; Rudolph, M.; Peuker, U. A.; van den Boogaart, K. G.

Abstract

Fine grained ore can only be exploited with finer milling, which results in additional milling costs. The ability to infer the optimal milling parameters and corresponding grades of recovery from microstructural information allows optimal extraction and predicting processing costs and final recovery. The MLA (Mineral Liberation Analyzer) allows quantifying the 2D size of grains in the ore. We have developed a method to predict the effect of milling from milling experiments and MLA-images to the 3D liberation of the value mineral in the ore.

Keywords: grinding; geometallurgy; MLA; milling

Vortrag (Konferenzbeitrag)
15th Annual Conference of the International Association for Mathematical Geosciences - IAMG 2013, 02.-06.09.2013, Madrid, Espana
Beitrag zu Proceedings
15th Annual Conference of the International Association for Mathematical Geosciences - IAMG 2013, 02.-06.09.2013, Madrid, Espana
Mathematics of Planet Earth - Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences, Berlin, Heidelberg: Springer, 978-3-642-32407-9, 717-721
DOI: 10.1007/978-3-642-32408-6

Permalink: https://www.hzdr.de/publications/Publ-18639