MINERÍA la mejor puerta de acceso al sector minero EDICIÓN 581 / FEBRERO 2026 54 Minería 4.0 Abstract This study describes the development, implementation, and evaluation of LingoSmelter, a statistical model based on Machine Learning (ML) techniques aimed at optimizing crude tin metal recovery in the Ausmelt furnace at the Minsur smelting plant. Traditionally, the prediction of crude metal recovery has been based on a theoretical model supported by mass and energy balances, which, although functional, presents limitations when facing operational variability and the complexity of process data. LingoSmelter was developed using an advanced analytics workflow that integrates supervised learning algorithms (XGBoost) LINGOSMELTER, APLICACIÓN Y EVALUACIÓN DE MODELO ESTADÍSTICO BASADO EN MACHINE LEARNING PARA LA OPTIMIZACIÓN DE RECUPERACIÓN DE METAL CRUDO
RkJQdWJsaXNoZXIy MTM0Mzk2