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Modeling and control of Ag mill energy consumption based on ore hardness distribution in a large-scale iron ore plant | ||
| International Journal of Mining and Geo-Engineering | ||
| مقاله 3، دوره 60، شماره 2، شهریور 2026، صفحه 131-137 اصل مقاله (664.76 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/ijmge.2026.397207.595273 | ||
| نویسندگان | ||
| Milad Sfaram Jooneghani1؛ Seyed Mohammad Razavian* 1؛ Mojtaba Ghorbannejad2 | ||
| 1Department of Mining Engineering, Faculty of Engineering, University of Kashan, Kashan, Iran. | ||
| 2Gohare- farzanegan Pelletizing Project Management, Kerman. | ||
| چکیده | ||
| The performance of autogenous (AG) grinding circuits is highly sensitive to variations in ore hardness, particularly in dry processing operations with limited buffering capacity. This study investigated on the influence of ore hardness variability on the operational behavior of the AG mill in Line 3 of the Gole-Gohar Iron Ore Concentration Plant. A total of 82 feed samples were collected and analyzed using the SAG Power Index (SPI) test to quantify ore hardness. The SPI results ranged from 48 to 236 minutes, revealing substantial heterogeneity in the run-of-mine feed. Correlation analyses demonstrated that increasing ore hardness resulted in reduced mill feed rate and increased specific energy consumption, primarily due to extended residence time and lower breakage efficiency. A linear regression model was developed to predict the mill’s specific energy demand as a function of SPI, providing a practical tool for energy forecasting and operational optimization. Furthermore, hardness-based ore classification and blending strategies were designed to mitigate the adverse impact of hard feed on mill performance. These homogenization approaches, supported by block model data and SPI testing, offer a cost-effective means to enhance process stability and energy efficiency. Overall, the findings underscore the importance of incorporating quantitative hardness characterization into comminution circuit design, control systems, and mine-to-mill planning frameworks. | ||
| کلیدواژهها | ||
| AG Mill؛ Modeling؛ SPI Test؛ Gole-gohar | ||
| مراجع | ||
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[1]. Bis, K., (2018), Geometallurgical characterization of the Kittilä gold ore deposit, European Mining, Minerals and Environmental Program (EMMEP), pp 44-75. [2]. Gupta, A., & Yan, D. S. (2016), Mineral processing design and operations: An introduction. Elsevier. [3]. Napier-Munn, T. J., Morrell, S., Morrison, R. D., & Kojovic, T. (1996), Mineral comminution circuits: Their operation and optimisation. Julius Kruttschnitt Mineral Research Centre. [4]. Behnamfard A., Namaei Roudi, D., Veglio, F., (2020), The performance improvement of a full-scale autogenous mill by setting the feed ore properties, Journal of Cleaner Producton., 271, 122554. [5]. Morrell, S., & Valery, W. (2001), Influence of feed size on AG/SAG mill performance. In Proceedings of SAG 2001 Conference, Vancouver, Canada (pp. 203–214). [6]. Starkey, J., Dobby, G., Kosick., G., (1994), A New Tool for SAG Hardness Testing, Canadian Institute of Mining, Metallurgy and Petroleum. [7]. Kosick, G., & Bennett, C. (1999). The value of orebody power requirement profiles for SAG circuit design. In Proceedings of the 31st Annual Meeting of the Canadian Mineral Processors, Ottawa, Canada. [8]. Akbari Nasab, A., Sam, A., Banisi, S. (2005). The effect of feed ore hardness on the power consumption of autogenous mills in the grinding circuit of Gol Gohar iron ore processing plant, Iranian Mining Engineering Conference, Tarbiat Modares University, Tehran, Iran (In Persian). [9]. Azimi, E. (2006). Study of the efficiency of the grinding circuit of the new processing plant of Sarcheshmeh Copper Complex, M.Sc. thesis, Shahid Bahonar University of Kerman, Iran (In Persian). [10]. Amelunxen, P., Berrios, P., Rodriguez, E. (2014). The SAG grindability index test. Minerals Engineering, 55, 42–51. https://doi.org/10.1016/j.mineng.2013.10.009 [11]. Dehghani Firoozabadi, J. (2009), Performance evaluation of autogenous mill in Choghart Plant – Line 3, Chahoon, Master’s thesis, Yazd University (In Persian). [12]. Paymard, M. (2007), Optimization of ball charge in SAG mill of Sarcheshmeh Copper Complex, Master’s thesis, Yazd University (In Persian). [13]. Jahani, M., Noaparast, M., Farzanegan, A., Langarizadeh, G. (2011). Application of SPI for Modeling energy consumption in Sarcheshmeh SAG and ball mills, Journal of Mining and the Environment, 2(1), 27-40. [14]. Asadi, R. (2017), Monitoring and troubleshooting the SAG mill performance at Phase 1 of Sarcheshmeh Copper Complex based on feed hardness and particle size distribution, Master’s thesis, Vali-e-Asr University of Rafsanjan (In Persian). [15]. Ghorbanimoghadam, M. (2014), Investigation of feed characteristics' effect on autogenous mill performance in Gole-gohar Magnetite Plant, Master’s thesis, Lorestan University (In Persian). [16]. Namaei Roudi, D., Behnamfard, A., (2022), Model development for prediction of autogenous mill power consumption in the Sangan iron ore processing plant, International. Journal of Mining and Geo-Engineering, 56-4, 301-307. https:// DOI: 10.22059/IJMGE.2022.320882.594899 [17]. Saldaña, M.; Gálvez, E.; Navarra, A.; Toro, N.; Cisternas, L.A. (2023), Optimization of the SAG Grinding Process Using Statistical Analysis and Machine Learning: A Case Study of the Chilean Copper Mining Industry, Materials, 16, 3220. https://doi.org/10.3390/ma16083220 [18]. Sfaram Jooneghani, M., Razavian, S. M., Ghorbannejad, M., (2022), Investigation of the Effect of Various Parameters on the Ore Hardness of Gole-Gohar’s No. 1 Mine, Journal of Mineral Resources Engineering, 7(3): 139-153.
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