The paper shows the preparation of the numerical models necessary for the simulation mapping of industrial-scale crushers of problematic material, such as copper ore with complex lithology. The crushers investigated in this work are located in the KGHM Polska Miedz S.A. copper ore processing plant. The complex ore consisting of sandstone, dolomite and shale is modeled using the Discrete Element Method (DEM) with Particle Replacement Model (PRM) that was chosen to simulate the crushing process. The article discusses the tests and calibration of material parameters and proceeds to test a breakage model in a laboratory-scale jaw crusher. The results are finally validated with the data from actual industrial-scale crushers and compared with the simulations. As an optimization option, the new shape of hammers is proposed and tested in a numerical environment. The performance of the newly designed hammers was examined using numerical methods. The numerical tests showed that the new design performed worse than the current solution. As a result, time and money were saved by avoiding industrial tests. In conclusion, the work shows how complex processes can be characterized in the numerical environment and used for further analysis.

This paper addresses the problem of conveyor transfer station design in harsh operating conditions, aiming to identify and eliminate a failure phenomenon which interrupts aggregate supply. The analyzed transfer station is located in a Polish granite quarry. The study employs laser scanning and reverse engineering methods to map the existing transfer station and its geometry. Next, a discrete element method (DEM) model of granite aggregate has been created and used for simulating current operating conditions. The arch formation has been identified as the main reason for breakdowns. Alternative design solutions for transfer stations were tested in DEM simulations. The most uncomplicated design for manufacturing incorporated an impact plate, and a straight chute has been selected as the best solution. The study also involved identifying areas of the new station most exposed to wear phenomena. A new transfer point was implemented in the quarry and resolved the problem of blockages.

Ball mills are widely used for size reduction in mineral processing, but effective scaling from laboratory to industrial scale remains challenging. This study introduces a novel scaling constant approach to replicate energy transfer to ore during milling across different scales by adjusting rotational speed and grinding medium size distribution. The scaling constant encapsulates parameters like the number of balls per working area, rotational speed, and an average ball’s maximum potential and kinetic energies. Experiments were conducted using a laboratory ball mill with interchangeable drum sizes (300, 400, and 500 mm) and a Design of Experiments methodology. Statistical analysis revealed that the scaling constant was more effective at maintaining consistent specific energy and energy per rotation across scales than size reduction, especially in dry milling. Wet milling results showed no significant differences in all metrics across scales. The dominant charge motion shifted from centrifuging to cascading as the mill diameter increased, highlighting the complex scaling dynamics. While the scaling constant shows promise for maintaining energy utilization, additional factors like charge motion and particle breakage mechanisms should be considered. The findings provide insights for improving ball mill design and optimization in mineral processing.

This article presents a novel approach to calibrating the digital twin of a laboratory mill used for copper ore milling. By integrating computer vision techniques for real-time data extraction and employing DualSPHysics simulations for various milling scenarios, including balls only, balls with ore, and balls with slurry, we achieve a high degree of accuracy in matching the digital twin’s behavior with actual mill operations. The calibration process is detailed for mills with three different diameters, highlighting the adjustments in simulation parameters necessary to account for the absence of ore. Understanding the dynamics between the suspension within the mill and the operation of the grinders is crucial for the future improvement of the grinding process. This knowledge paves the way for optimizing the process, not only in terms of the quality of the end product but primarily in terms of energy efficiency. A profound understanding of these interactions will enable engineers and technologists to design mills and grinding processes in a way that maximizes efficiency while minimizing energy consumption.