细粒浮选尾矿品位分析与改善  

Analysis and Improvement of Fine Flotation Tailings Grade

作　　者：李青松 黄丽 李金龙 LI Qingsong;HUANG Li;LI Jinlong(Micro Ore Workshop of Mining Titanium Concentrator of Ansteel Panzhihua Iron and Steel Group,Panzhihua,Sichuan Province,617000 China;School of Intelligent Manufacturing,Panzhihua University,Panzhihua,Sichuan Province,617000 China)

机构地区：[1]鞍钢攀钢集团矿业选钛厂微矿车间,四川攀枝花617000 [2]攀枝花学院智能制造学院,四川攀枝花617000

出　　处：《科技创新导报》2021年第23期107-109,共3页Science and Technology Innovation Herald

摘　　要：为降低某矿业公司选钛厂细粒浮选尾矿品位,提高浮选回收率,确保钛精矿产量最大化和降低生产成本,对以往尾矿品位数据进行分析,设定优化目标将尾矿品位降低到5.50%,用因果矩阵和帕累托图分析影响浮选尾矿品位高的主要原因,筛选出关键因子,通过快速改善来优化关键因子,用全因子分析得到因子取值范围,根据取值范围确定最优的关键因子取值,最终超额完成预定目标,将尾矿品位从6.67%降低到4.91%。In order to reduce the grade of fine-grained flotation tailings in a titanium concentrator of a mining company,improve the flotation recovery rate,maximize the output of titanium concentrate and reduce the production cost,the previous tailings grade data are analyzed and the optimization target is set to reduce the tailings grade to 5.50%.Firstly,the main reasons affecting the high grade of flotation tailings are analyzed by Causal Matrix and Pareto Diagram.Then,the key factors are screened out and optimized through rapid improvement.Finally,the factor value range is obtained by full factor analysis,the optimal key factor value is determined according to the value range,the predetermined goal is exceeded,and the tailings grade is reduced from 6.67%to 4.91%.

关 键 词：尾矿品位 细粒浮选 质量管理 数据分析 

分 类 号：TD952[矿业工程—选矿]