Multiobjective optimization of dry batch micronized grinding of slaked lime in a vibrating mill via TOPSIS and ANOVA

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ABSTRACT The multiobjective optimization of dry batch micronized grinding of slaked lime in a vibrating mill was carried out via the technique for order of preference by similarity to the ideal solution (TOPSIS) method. The main objective is to reduce the average particle size (d50) and specific energy consumption (SEC) and maximize the specific surface area (SA). Experimental trials varied the charged material volume, ball-filling ratio, and grinding time. The results were analyzed via analysis of variance (ANOVA) to determine each parameter’s contributions, and regression models were used to predict the relative closeness (RC) to the ideal solution. The optimal grinding parameters were 30% for the charged material volume, 80% for the ball filling ratio, and 10 minutes for the grinding time, resulting in a d50 of 6.26 µm, an SA of 2.71 m2/g, and an SEC of 2.42 kWh/ton. The empirical model, validated through ANOVA, revealed a high coefficient of determination (R2 = 0.975), confirming the model’s accuracy. The findings show that while higher impact forces, frequencies, and acceleration in vibrating mills allow the use of smaller grinding media, the increased surface area of micronized slaked lime is not directly proportional to the energy input. This study provides a comprehensive approach for optimizing the micronization of slaked lime, contributing valuable insights into energy-efficient grinding processes.