Efficient comminution requires crushing circuits to break down run-of-mine ore for grinding. The operator needs to reach the particular P80 that stands for the screen size through which 80% of the product mass goes. Getting the particular target P80 calls for balancing closed-side settings (CSS) of the circuit, which are the smallest possible distance between crushing surfaces during the gyration cycle. The coordination of CSS across the three-stage circuit with the primary, secondary, and tertiary crushers is critical for maximizing throughput and saving energy.
It is necessary to control the distribution of the loads throughout the circuit in order to achieve the desired CSS balance. At the primary crushing stage, the main volume reduction takes place, while the secondary and tertiary stages are responsible for further crushing the material. If the gap in the primary crusher is too wide, this results in an excessive amount of oversized material which puts a strain on the secondary crushers. Conversely, if the gap is too small, the overall circuit throughput is reduced. The selection of the gap must be treated as a comprehensive issue because the performance of one stage has a significant effect on that of the subsequent stage (Bhadani et al., 2021).
For achieving efficient target P80, the secondary crusher has to be an optimal bridge. It needs to be strictly tuned to create the particular particle size distribution that will safely choke-feed the third stage. Choke feeding keeps the crusher chamber always full and promotes inter-particle breakage which leads to the uniform shape of particles and stable power draws (Duarte et al., 2021). If the gap is not properly balanced, the choke feeding for the tertiary crusher is broken and it becomes impossible to reach a steady P80.
Finally, the tertiary crusher is responsible for the P80 since it operates in the closed loop with the screens. The CSS adjustment affects the recirculating load mass. Even though the tighter gap results in finer material, it also increases the amount of the recirculating load and the risk of screen overload. The trade-off curves created by the dynamic process simulation show the optimal gap that effectively balances the recirculating load and meets the target P80 without the equipment bottleneck (Bhadani et al., 2023).
Modern optimization includes the usage of dynamic control systems to automatically tune the CSS according to the hardness and feed sizes. Centralized controls and dynamic digital twin simulation adjust the CSS of the crushers and the speeds of the upstream feeders (da Silva et al., 2024). With the help of power draw and silo levels monitoring, such a system adjusts the cone crushers in real time. In case of the hard ore being fed into the circuit, the CSS might be loosened slightly to avoid overload and adjust feeders at the same time.
To conclude, the balancing of the gap settings of the three-stage circuit is the comprehensive task of controlling material flows. Operators need to consider the primary, secondary, and tertiary crushers as the united system and not as individual mechanical parts. With choke feeding, recirculating load control, and dynamic gap adjustment, the comminution plant will be able to consistently reach its target P80.
References
Bhadani, K., Asbjörnsson, G., Bepswa, P., et al. (2021). SIMULATION-DRIVEN DEVELOPMENT FOR COARSE COMMINUTION PROCESS – A CASE STUDY OF GEITA GOLD MINE, TANZANIA USING PLANTSMITH PROCESS SIMULATOR. Proceedings of the Design Society, 1, 2681–2690. https://doi.org/10.1017/pds.2021.529
Bhadani, K., Asbjörnsson, G., Soldinger Almefelt, M., Hulthén, E., & Evertsson, M. (2023). Trade-Off Curves for Performance Optimization in a Crushing Plant. Minerals, 13(10), 1242. https://doi.org/10.3390/min13101242
da Silva, M. T., Bitarães, S. M., Yamashita, A. S., et al. (2024). Centralized Finite State Machine Control to Increase the Production Rate in a Crusher Circuit. Energies, 17(14), 3374. https://doi.org/10.3390/en17143374
Duarte, R. A., Yamashita, A. S., da Silva, M. T., Cota, L. P., & Euzébio, T. A. M. (2021). Calibration and Validation of a Cone Crusher Model with Industrial Data. Minerals, 11(11), 1256. https://doi.org/10.3390/min11111256
