Optimising mine cooling system performance through monitoring and analysis

Abstract

The South African mining industry is under ever-increasing economic pressure. The lack of shallow resources forces mining companies to increase workplace depths to exploit mineral resources. The increased depth of workplaces poses significant environmental challenges due to increasing temperature resulting from auto-compression and higher virgin rock temperatures. Mines mitigate this heat load with large cooling systems to provide safe working conditions. These cooling systems are therefore critical in effective mine operations and are an area in need of optimisation through monitoring and analysis. This study implemented a novel application of the Data, Information, Knowledge, Wisdom (DIKW) method on a deep-mine cooling system to monitor the cooling system performance. The method aggregated data available on the mine into an automatic daily report, which extracted valuable information and knowledge. This data maturity led to a wisdom-level understanding of cooling performance, enabling informed management decisions. The DIKW method facilitated an improvement of 55% in delivered cooling on a South African deep gold mine. This increase in cooling resulted in safer workplace environmental temperatures. However, a shortcoming of the methodology was the inability to account for the expected performance of the cooling systems at off-design conditions. The changing nature of the underground environmental conditions resulted in a need to analyse the expected performance of mine cooling systems operating under off-design conditions. The study developed simulation models to predict the expected (normalised) performance of underground cooling systems operating under off-design conditions. The novel application of this method on tertiary cooling systems (cooling coils) showed that the conventional method of calculating cooling coil efficiency was 38% off. The use of simulation models in cooling coil analysis enabled a more accurate representation of their efficiencies. The results then enabled effective maintenance strategies aimed at the cooling coils, as well as the environmental conditions. This research showed the importance of actual performance monitoring and reporting, as well as using normalised performance for accurate cooling system analysis. The developed monitoring and analysis methods form the building blocks for the current Industry 4.0 drive on deep-mine cooling systems. The research outcomes added substantial value for the future of optimising mine cooling system performance. This Master's degree is in an article-based format, with the first article covering the DIKW approach, published in the International Journal of Mining Science and Technology. The second article, investigating the normalised performance of cooling coils, was submitted to Applied Energy.