Festus Kunkyin-Saadaari

The useful life of dump truck tyres is crucial for optimising economic efficiency and safety in mining operations. This study employs advanced hybrid models, including a generalised regression neural network (GRNN) combined with an artificial bee colony (ABC), ant colony optimisation (ACO), and firefly algorithm (FA), to predict tyre life at Perseus Mining Ghana Limited to enhance prediction accuracy. Sensitivity analysis using simple linear regression (SLR) identified tread depth as the most influential factor, with a correlation coefficient of 0.9638. Among the models, GRNN-FA demonstrated superior performance, achieving the highest correlation coefficient (r = 0.9586) and lowest mean squared error (MSE = 0.1019), root mean squared error (RMSE = 0.3191) and, mean absolute error (MAE = 0.2761). The study highlights that improving operational factors such as floor and road conditions, payload weight, and cycle time can significantly extend the tyre life. Implementing the GRNN-FA model can optimise tyre management, reduce downtimes, and enhance operational efficiency, thereby setting a new standard for tyre life prediction in the mining industry.

Mining results in both economic and uneconomic materials being generated. The uneconomic materials (wastes) are stacked in a convenient place for further use or stored permanently as a slope or embankment. In Ghana, a typical gold mine set up dumping sites to accommodate the waste generated from its operations. Samples were collected from three waste dumps and tested in the laboratory, and the parameters obtained were used as input for 2D model development. The Factor of Safety (FS) of the three waste dumps were determined using the Janbu Generalised slope stability analysis method. Path and slope surface (circular and non-circular) search methods were used for the three cases. The FS for the waste dumps were determined and ranged from 1.61-2.74, 1.49- 2.50 and 1.32-2.10 under dry, static and pseudo-static loading conditions, respectively. These values exceed the minimum requirements of 1.1-1.5 for stability conditions. The geometry of the waste dumps, Suraw Waste Dump (SWD), is within the standard and hence, does not require reshaping, while the slope angles for the remaining waste dumps, Tano Waste Dump (TWD) and Akoti Waste Dump (AWD) need to be reshaped to achieve the proposed slope angle of 3H:1V (18.40 degrees) as stipulated in the mine’s Environmental Impact Statement (EIS).