Improving energy efficiency of the ore preparation process based on analyzing energy consumption of semi-autogenous grinding mills

In conditions when easily accessible ore reserves are depleting and the energy tariffs are rising, improving the energy efficiency of mining and processing plants is becoming a critical task. Ore preparation processes, particularly operation of semiautogenous grinding mills, which are major electricity consumers, hold the greatest optimization potential. The aim of this work is to analyze the actual energy consumption of a semi-autogenous grinding mill at the Kochkar gold ore deposit to develop practical recommendations for reducing specific energy costs. The study employs a comprehensive approach combining the Bond method for calculating the ore work index, direct measurements of electrical parameters (current, voltage, power) using AR5 and PKK-57 analyzers, and processing of statistical data using Python and MathCAD. The key results show that the average work index is 1.01 kWh/t; however, a weak correlation between the throughput and active power was identified. It was found that short-term interruptions in the ore feed fail to produce proportional energy savings. The practical significance of this work lies in justifying the need of transition to adaptive control systems and digital twins, which could reduce specific energy consumption by 10–15% and enhance the stability of the technological process.