Grinding Flotation Optimization Using Operational Intelligence

"In recent years, metal producing companies have increased their investment in automation and technological innovation, embracing new opportunities to enable transformational change. Internet of Things (IoT) is one of many transformational initiatives, which can fundamentally revolutionize how industrial complexes operate. Whatever the issue, the answer is in the abundant and growing quantity of real time data and events collected in the grinding and flotation circuits in a mineral processing plant. Based on earlier work, today a grade recovery model permits identifying the best operating conditions in real time. We will review the strategy for increasing the value of the abundance instrumentation in current plants. An optimal Gaudin size distribution model provides augmented information from traditional sensors to find the optimal grind cut to reduce metal losses in the flotation circuits. The large amount of sensors in a flotation circuits permits to estimate the recovery and to find the optimal froth depth and aeration using an air holdup flotation model. The paper will describe the strategy of classifying data for on line generation of insights to using operational intelligence tools. We will discuss the implementation Recovery/Grind strategy with industrial examples in non-ferrous mineral processing and iron beneficiation.INTRODUCTIONThe declining supplies of high grade ores and increasing consumption of mineral and metal products have demanded higher operational efficiencies with minimum capital investments. The objective of copper flotation objectives are based on maximizing the dollars return on the concentrate produced. The economic efficiency is maximized by manipulating the circuit along the grade/recovery curve relationship. To achieve such objective improved stabilization of the grinding and flotation circuits are required (Oosthuizen, Craig, and Jamsa-Jounela, 2017)."