Optimization of comminution in grinding to reduce operating costs at the Antamina mining project. (#2052)

Authors

Aguilar Julca, Paul Michael

Monsalve Vásques, Royner

De La Cruz Capitán, Adriana Del Pilar

Abstract

High energy consumption during the comminution stage is one of the main challenges to the operational efficiency of Peruvian mining. In this context, this research focused on optimizing the comminution circuit at Compañía Minera Antamina S.A., located in the district of San Marcos, province of Huari, region of Áncash, Peru. The purpose of the study was to theoretically analyze the reduction in energy consumption and the operational benefits derived from the implementation of emerging technologies, such as machine learning, advanced process control, and high-pressure grinding (HPGR). The research was applied, descriptive-comparative in nature, and employed a non-experimental, cross-sectional design. It was based on a documentary analysis of technical reports and recent specialized literature (2019–2024). The results showed that modernizing the grinding circuit reduced specific energy consumption from 14 to 10.5 kWh/t, equivalent to an approximate 25% savings, and increased throughput from 2,750 to 4,400 tons per hour. These improvements demonstrated more efficient use of installed power and a reduction in the process's environmental footprint. In conclusion, optimizing the comminution circuit at Antamina represents an effective strategy for reducing energy costs, improving productivity, and strengthening the sustainability of the mining operation. Keywords- Comminution, energy efficiency, machine learning, Antamina, sustainability.