Application of Response Surface Methodology for Modeling and Optimization of Preparation of High-Alumina Iron Ore-Coal Composite Hot Briquette

The effect of three major influence process parameters, carbon addition ratio, ore particle size, and coal particle size on the compressive strength of high-alumina iron ore-coal composite hot briquette (Al-CCB) with the application of response surface methodology is investigated in this paper. The results show that, with using multiple regression analysis, the experimental data can be fitted into a quadratic polynomial model. Based on the coefficient of determination (R-2 = 0.9883) and the analysis of variance (ANOVA), the model shows good agreement with the experimental data. The effect on the compressive strength of Al-CCB from big to small is carbon addition ratio, ore particle size, and coal particle size. In order to obtain the Al-CCB with 600N of compressive strength, the optimal experiment conditions are found to be the coal addition ratio of 16.44%, ore particle size of -100 mesh and coal particle size of -100 mesh, resulting in an actual compressive strength of 613N, as compared to the model prediction of 600 N. This paper can provide guidance for the optimization on preparation of Al-CCB. Also, it can offer reference for the process improvement of other ore-coal composite agglomerates.