Component optimization of sintering raw material based on fuzzy comprehensive evaluation and response surface method

The matching rationality of the sintering raw material components directly affects the high-quality production of the sinter. For the sake of forecasting and improving the sinter quality, an optimization model of the sintering raw material components based on fuzzy comprehensive evaluation (FCE) and response surface method (RSM) was constructed. The low-temperature reduction pulverization index (RDI + 3.15mm ) and the calcium ferrite content (VOL SFCA ) were taken as the fuzzy comprehensive evaluation result ( Y ) to assess the sinter quality. The interaction and the optimization of the component factors ω(MgO), ω(Al 2 O 3 ), and R (CaO/SiO 2 ) were thus determined. The results showed that the P -value of the FCE-RSM component optimization model was <0.0001, the adjustment coefficient R 2 adj was 97.45%, and the predicted determination coefficient R 2 pred was 86.03%. The influence degree of the component factors on the FCE result was R (CaO/SiO 2 ) >ω(MgO) >ω(Al 2 O 3 ), and the interactions of every two factors were all significant. The component optimization of sintering raw material determined by the model application was ω(MgO) = 2.33%, ω(Al 2 O 3 ) = 2.04%, and R (CaO/SiO 2 ) = 2.17, while the actual value of the FCE result ( Y = 0.98) was the same as that of the predicted value ( Y = 0.99). This method is effective and beneficial for the high-quality production of sinter.