Additonal authors: Fuentes, R.. Book title: Proceedings of the 58th Conference of Metallurgists Hosting Copper 2019. Chapter: . Chapter title:
Rapid analytical assessment in copper mining industry is a limiting factor for operational purposes and for the improvement of processes. The present work aims to review the analytical assessment in the copper industry utilizing emerging spectrochemical techniques such as laser induced breakdown spectroscopy (LIBS) and UV-Vis-IR Hyperspectral Sensing. LIBS is a plasma based spectroscopic method where the sample surface is irradiated by high power laser. The light emitted from the plasma contains atomic
-molecular spectral information and can be detected using a simple CCD based spectrometer. UV-Vis-IR Hyperspectral Sensing is produced by the reflection of light from the sample’s rough surface in all directions and it can be collected by using an ellipsoid or paraboloid mirror arrangement. The electromagnetic radiation emitted by the samples in the UV-Vis, NIR and MIR region can be used for molecular characterization. The spectrometer splits different wavelengths through a CCD arrangement in 2D spatial and spectral dimensions, thus a hyperspectral cube of data is generated. Chemometric techniques such as principal component analysis (PCA), K- nearest neighbors (KNN), support vector machine (SVM) among others, can be applied to LIBS and Hyperspectral data for better classification and quantification purposes in copper ores. Real- time determination of elemental and mineral species used for online processing control will help to achieve the copper industry 4.0.
The demand for copper mineral resources is intensely growing with the increase in population, per capita GDP, the development of new technologies and the increase in global living standard. With the rise in consumption of copper, it is important to optimize mining and metallurgical processes tending to the copper industry 4.0 (Ge, Song, Ding, & Huang, 2017). The real-time analytical assessment in the mining and metallurgical processes is a crucial part for allowing the global improvement in mining industry. The features considered for better analytical assessment are the instrumental automation and interconnection, real time results, low cost, quality in terms of accuracy and precision. Furthermore, improving recovery (extraction), timing and quality of final products avoiding environmental impacts. Some elements such as Cu, Fe, Ag, Au, Mo, S, As, Pb, Zn are important to be determined in the process control. Additionally, rapid mineral identification of few species such as CuFeS2, Cu4FeS5, FeS2, CuS, Cu2S, MoS2, Cu3AsS4, FeAsS, among other can be challenging.