Application of Taguchi-Based Response Surface Methodology to Optimize Process Parameters for a Small-Scale Wet Ball Mill for Use in Gold Mining

Abstract

A ball mill is a machine used in the mining industry to reduce the size of the ore to a desirable size in order to liberate the minerals. Effectively controlling the fineness of a ball mill's product necessitates an understanding of the impacts of various input parameters. In this study, Taguchi-based Response Surface Methodology (RSM) was employed to investigate the impact of feed size, slurry solid content and feed rate on the product’s Particle Size Distribution (PSD) of a small-scale wet ball mill. Taguchi’s L9 orthogonal array was utilized for experimental design to minimize the number of runs, while RSM was applied to optimize the input variables. Additionally, analysis of variance was employed to identify the most significant parameter influencing PSD within the range-150 + 75 µm. The findings revealed that, under the considered levels of the parameters, the average feed size exerted the most significant influence, followed by feed rate and solid content, respectively. The response optimizer indicated that a maximum PSD of 72.24% could be attained by maintaining an average feed size of 7.5 mm, a solid content of 60%, and a feed rate of 0.025 m³/h. The experimental PSD closely matches the predicted value with a 3.01% error, indicating a good fit.