Optimización del proceso de Trituración primario en una cantera de caliza

Abstract

The project optimizes the primary crushing process in a limestone quarry, aiming to improve energy and economic efficiency as well as crushing performance through the development of descriptive and predictive models for primary crushing and the generation of cost curves for later evaluation. The hypothesis states that controlling the particle size feed directly affects the overall process costs and performance. The justification is based on the need to reduce energy and operational costs within the quarry. The project was developed through field data collection, blast photogrammetry using a DJI Mavic 3 Enterprise drone, and artificial intelligence processing with the Strayos software. The crushing equipment was characterized, and the process was simulated using the Modsim software, applying Bond’s Law for energy and cost analysis. The main results showed that a blasting particle size distribution with a D80 close to 65 cm optimizes the balance between explosive consumption and crushing energy, improving efficiency, and reducing costs. In conclusion, optimizing the primary crushing process increases productivity and energy efficiency, ensuring a more profitable and sustainable operation in the limestone quarry. Keywords: Particle size distribution, Bond’s law, Energy consumption, Operational efficiency.