Optimizing Mineral Extraction in Peru: Integrating Geometallurgical Planning with Mining 4.0 Technologies

Geometallurgy is a comprehensive approach linking geology with mineral processing, addressing orebody variability and its impact on material quality.In Peru, the absence of predictive geometallurgical planning and real-time data poses challenges.This study aims to develop effective geometallurgical planning for Peruvian mining, optimizing mineral extraction and processing through advanced techniques like geostatistics and machine learning.Using a descriptive, non-experimental approach, the study focused on open-pit and underground mines.Methodology included detailed geological and metallurgical characterization, involving chemical analysis, mineralogical studies, and metallurgical tests.Geometallurgical models were implemented, integrating machine learning and geostatistics for data management and analysis.Results showed that geometallurgical planning allowed mining companies to better understand their deposits, optimizing extraction and processing.Specifically, detailed mineralogical characterization and geometallurgical domains reduced production variability by 15%.Advanced techniques improved accuracy in resource prediction by 20% and enhanced data management, enabling informed decisions-making.In conclusion, geometallurgy is crucial for optimizing mining production and reducing environmental impact.The study emphases the importance of technological innovations for sustainable practices in the Peruvian mining industry, highlighting that effective geometallurgical planning, can significantly improve operational efficiency and resource utilization.