In this work, we present a case study demonstrating the application of Optimaviz, an advanced data analytics platform, in addressing the challenges of flotation optimization in the mining industry. The study utilizes historical data from the Jabal Sayid underground copper mine, operated by Ma’aden Barrick Copper Company (MBCC), a joint venture between Ma’aden and Barrick Corporations. Our findings reveal that maintaining cyclone feed slurry percentage solids within the range of 65–71 wt% is crucial for achieving high plant performance (rougher tails copper grade < 0.15 wt% and combined concentrate grade > 24 wt%), with deviations from this prescribed range resulting in a significant decrease in performance. Additionally, we observe the impact of the first concentrate grade (rougher concentrate grade) on overall plant performance, requiring first concentrate grade to be above 26 wt% to achieve high performance, highlighting the importance of the efficiency of the first three rougher cells on the overall plant performance. Furthermore, the study underscores the significance of the balance of power between the SAG mill and Ball mill in achieving a finer rougher feed size distribution that is required to promote flotation performance. This study demonstrates how Optimaviz can be used to effectively optimize mineral processing circuits, providing process engineers and metallurgists with a robust tool to derive actionable insights and enhance plant performance without the need for coding knowledge.

中文翻译：

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优化马丁巴里克铜业公司 （MBCC） 浮选回路的数据驱动策略 - 可视化和机器学习在数据挖掘中的力量 -


在这项工作中，我们提供了一个案例研究，展示了高级数据分析平台 Optimaviz 在解决采矿业浮选优化挑战中的应用。该研究利用了 Jabal Sayid 地下铜矿的历史数据，该铜矿由 马亚丁和巴里克公司的合资企业 马 aden 巴里克铜矿公司 （MBCC） 运营。我们的研究结果表明，将旋流进料浆料固体百分比保持在 65-71 wt% 范围内对于实现高工厂性能至关重要（粗尾铜品位 < 0.15 wt% 和混合精矿品位 > 24 wt%），偏离此规定范围会导致性能显着下降。此外，我们观察到第一精矿品位（粗精矿品位）对工厂整体性能的影响，要求第一精矿品位高于 26 wt% 才能实现高性能，这突出了前三个粗浆单元的效率对工厂整体性能的重要性。此外，该研究强调了半自磨机和球磨机之间的功率平衡在实现更精细、更粗的给料粒度分布方面的重要性，这是提高浮选性能所必需的。本研究展示了如何使用 Optimaviz 有效优化矿物加工回路，为工艺工程师和冶金学家提供强大的工具，无需编码知识即可获得可操作的见解并提高工厂性能。