Optimization of comminution in grinding to reduce operating costs at the Antamina mining project.

Autores/as

  • Paul Michael Aguilar Julca Universidad Privada del Norte - (PE), Perú
  • Royner Monsalve Vásques Universidad Privada del Norte - (PE), Perú
  • Adriana Del Pilar De La Cruz Capitán Universidad Privada del Norte - (PE), Perú

DOI:

https://doi.org/10.18687/LACCEI2026.1.1.2052

Palabras clave:

Comminution, energy efficiency, machine learning, Antamina, sustainability.

Resumen

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.

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Publicado

2026-07-27

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Articles

Licencia

Licencia Creative Commons

Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.

LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).

Cómo citar

Aguilar Julca, P. M., Monsalve Vásques, R., & De La Cruz Capitán, A. D. P. (2026). Optimization of comminution in grinding to reduce operating costs at the Antamina mining project. LACCEI, 1(14). https://doi.org/10.18687/LACCEI2026.1.1.2052

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