Qualitative and Quantitative Synthetic Methodology for Blending Optimization in Lead-zinc Sintering

To deal with the problem of high cost and low accuracy existed in conventional methods for the lead-zinc sintering blending, a qualitative and quantitative synthetic methodology for sintering blending optimization is presented in this paper. First, two prediction models are built based on a process neural network and the improved grey system theory. Next, these two models are integrated into one prediction model by using the concept of entropy. It guarantees the prediction precision of the Pb and Zn components in the agglomerate. Then, a blending optimization model is established to minimize the costs. Finally, the component ratios are optimized by using the expert reasoning strategy and an integrated synthesis methodology.