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Optimization of Pb flotation using statistical technique and quadratic programming

机译:利用统计技术和二次规划优化铅浮选

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摘要

A three-level Box-Behnken factorial design combining with a response surface methodology (RSM) was employed for modeling and optimizing three operations parameters of the flotation on lead flotation. The flotation studies of lead ores containing 7.1% Pb were carried out in this study. The variables studied were potassium amyl xanthate (KAX) as a collector, sodium sulfide (Na2S) and pH. Experiments were carried out using Box-Behnken factorial design. The main and interaction effects were evaluated using response surface methodology. Second order response functions were produced for both the Pb grade and recovery. These response functions were then optimized using the quadratic programming method to maximize Pb grade and recovery within the experimental range studied. The optimum composition was found to be 212 g/t KAX, 1250 g/t sodium sulfide and 9 pH to achieve the maximum Pb grade. The model prediction of 47.44% Pb at optimum conditions was higher than any value obtained in the initial experiments conducted. In the same way, the optimum composition was found to be 100 g/t KAX, 1250 g/t Na2S and 7 pH to achieve the maximum recovery. The model prediction of 84.58% recovery at optimum conditions was also higher than any value obtained in the initial experiments conducted.
机译:采用三级Box-Behnken析因设计与响应面方法(RSM)相结合,对铅浮选过程中浮选的三个操作参数进行建模和优化。这项研究进行了含铅量为7.1%的铅矿石的浮选研究。研究的变量是戊基黄原酸钾(KAX)作为收集剂,硫化钠(Na2S)和pH。实验是使用Box-Behnken因子设计进行的。使用响应面方法评估了主要和相互作用的影响。对铅的品位和回收率都产生了二阶响应函数。然后使用二次编程方法对这些响应函数进行优化,以在研究的实验范围内使Pb品位和回收率最大化。发现最佳组成为212 g / t KAX,1250 g / t硫化钠和9 pH以达到最大Pb级。在最佳条件下,模型预测的47.44%Pb高于进行的初始实验中获得的任何值。同样,发现最佳组成为100 g / t KAX,1250 g / t Na2S和7 pH以实现最大回收率。在最佳条件下,模型预测的84.58%回收率也高于进行的初始实验中获得的任何值。

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