Application of Multiple Linear Regression (MLR) Analysis on the Concentration of Chromite Plant Tailings by a Shaking Table

In this paper, the beneficiation of the Upper Group 2 (UG-2) plant tailings was investigated to recover chromite. Multiple linear regression analysis was applied to estimate the recovery and grade of chromite. A detailed chemical and mineralogical characterization of the UG2 plant tailings was conducted using X-ray fluorescence (XRF) and Scanning electron microscopy (SEM) with energy dispersive X-ray spectroscopy (EDS) for elemental composition and surface morphology respectively. The results showed that the major elements in the chromite plant tailings are Fe (12.96 wt%), Cr (10.97 wt%) and Si (15.64 wt%). The major mineral phases are quartz, spinel, magnesiochromite and aluminosilicates. The results attained from the Microtrac particle analyser indicated that 80% of the particles are < 95 μm and only 6% was less than 10μm. The highest recovery of Cr₂O₃ was found to be 67.27% at a grade of 21.87% chromite. Multiple linear regression equations were created based on the experimental results to forecast the recovery and grade of the chromite concentrate, and the regression coefficients between experimental and anticipated values were poor for grade and good for recovery (R2 values of 0.18 and 0.66, respectively). It was concluded that the generated MLR equations can be used to forecast the recovery of chromite from UG-2 plant tailings.