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Vol. 28 No. 53 (2019)

Papers

Statistical Modeling and Optimization of the Cyanidation Process of Gold Mineral

https://doi.org/10.19053/01211129.v28.n53.2019.9745

Published 2019-08-14

Jairo Antonio Ruiz-Córdoba, M.Sc.
Universidad de Antioquia

Carlos Alberto Lopez-Cañas, M.Sc.
Universidad de Antioquia

María Eugenia Carmona-Arango
Universidad de Antioquia

William Hernán Bolívar-García
Universidad de Antioquia

Abstract

In this paper, we have sought to identify the conditions and optimal operating variables for the processing of a gold ore, in such a way to achieve high efficiency in the recovery of the precious metal. Initially a characterization of the mineral under study was carried out with the performance of different laboratory tests. Likewise, a grinding test was made. In the same way, a sample of ore was classified using a series of Tyler sieves. Next, the material was subjected to gravimetric concentration on a Wilfley concentrator table. The fines, product of the concentration, with a 100 % granulometry through 170 Tyler meshes, were subjected to conventional flotation tests. In this way, to optimize the recovery of gold from the gold ore under study, an experimental design of 2k factorial analysis with central point, three variables and the response surface method was applied to determine the optimal parameters to achieve an efficient recovery during cyanidation. The results obtained show that the mineral has a high degree of cyanide leachability, obtaining a gold recovery of 89.35 %. The research demonstrated that the statistical experimental design is a valuable tool for the efficient processing of the minerals, since it allows finding the optimal parameters of the cyanidation process such as the leaching time, the granulometry of the mineral and the concentration of NaCN. The results obtained with the application of the statistical design in the cyanidation tests allowed determining the optimal operating conditions for a maximum gold recovery.

Keywords

cyanides, floatation, gold, minerals, precious metals, statistical analysis

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