A review of real-time optimization in underground mining production

Modern mining is the process of exploiting minerals from the earth to derive profits. Realtime optimization for plant-wide production has been implemented in the process industry; however, these systems have not yet been implemented for mine-wide production in the mining industry, particularly for underground mines. Real-time control systems have been applied to a few unit operations (e.g. conveying and hoisting), but these systems are only on a machine-level and not a minewide level. In the past, several unique features of underground mining limited the use of MPRTO on a mine-wide scale. For instance, the complicated structure of underground mines could make underground communication and positioning systems extremely expensive, while up-to-date 3D mine models would inevitably require demanding algorithms for operations and highperformance data processing. Additionally, lack of miners’ information technology (IT) skills and lack of interoperability among individual control systems would also make mine-wide use less viable. With the development of IT and other related technologies, the above technical barriers have gradually been eroded. Fortunately, IT training for miners has also become one of the top five concerns for mining employers (Ruiter, 2011). In general, the prerequisites for applying the MPRTO system are close to completion. A survey from Mincom (2010) showed that improving operational effectiveness is the second top challenge faced by senior executives of global mining companies, ensuring workforce safety being the first. Another survey from Mincom (2011) showed that optimizing production effectiveness has become the top challenge, pushing the primary concern of 2010 – ensuring workplace safety – into second position, as long as safety is acceptable. There is an example of a real-time production optimization system used in a related industry – construction. The benefit of the system has been shown by an improvement of 30–50 per cent in production, with an associated reduction in fuel consumption and carbon dioxide emissions of 43 per cent (Caterpillar, 2006). Therefore, there is a great potential in the form of commercial value and public benefit for developing an effective MPRTO system. The development of this system will basically require optimization techniques, a mine-wide A review of real-time optimization in underground mining production