Parametric optimisation and modelling of tungsten mine tailings beneficiation and carbothermic reduction using Box-Behnken design with subsequent smelting

The progressive depletion of high-grade hematite necessitates the utilisation of lean-grade resources through innovative beneficiation and ironmaking routes. In this research, tailings from a tungsten mine, e.g. lean-grade hematite ore, were upgraded via jigging and statistically optimised using a Box–Behnken design to evaluate the effects of particle size, pulsation frequency, and time on total grade recovery. Due to extensive and progressive mining, most tungsten deposits have been depleted, leaving behind vast quantities of tailings that now represent a potential lean-grade hematite resource. Quadratic regression models with high coefficient of determination (R2 > 0.95) accurately predicted process outcomes, while ANOVA confirmed that particle size and pulsation frequency were the dominant factors. Response surface analysis revealed optimum conditions that maximised iron recovery with minimal silica and alumina contamination. The optimised concentrate underwent carbothermic reduction and smelting, producing metallic iron with uniform microstructure confirmed by XRD, FESEM-EDAX, and FTIR. Finer particle size (75 µm), higher temperature (1050°C), and longer duration (60 min) enhanced the extent of reduction (EOR) and degree of metallisation (DOM). This integrated beneficiation-smelting route offers a sustainable pathway for efficient utilisation of lean hematite resources.