Browsing by Author "Nong, Setshaba"

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Review of successes and failures of mechanisation trials on platinum mines of the Bushveld Complex.
(2011-11-02) Nong, Setshaba
Mine mechanisation seems to be failing in the Bushveld Complex (BC) although it has been promoted on the basis of superior qualities to the conventional mining methods. This is particularly true for the extra low profile (XLP) mining method. The reasons for the successes and failures were observed from case studies and previous work captured through a comprehensive literature review. Interaction with industry experts and mine operators provided further insight into the suitability of mechanised mining systems on the BC. Technology trials on the BC included non blasting mining methods in the form of cutting discs which were not successful but provided encouraging data for future development. The low profile (LP) and extra low profile (XLP) mining technology is the only tried technology that has formed part of the mining mix in the BC albeit with challenges. In some operations where mine mechanisation technology was tried the performance was poor resulting in discontinuation, conversion to hybrid mining method and/ or reverting to the conventional mining method. Dilution makes the XLP and LP mining unsuitable for mining narrow tabular ore bodies due to the amount of waste that dilutes the ultimate grade of the mine. The technology that is suitable for mining mechanised equipment must be able to ensure that it does so safely and without compromising the value in terms of grade. The current mining methods utilising mechanised equipment found in the BC has resulted in lower grades because of dilution caused by large excavations which are required to accommodate the equipment. It is imperative to understand the impacts on value the mining method creates and/or destroys for the Life of mine. There are other mining methods which must be further investigated. These include non-blasting and long hole stoping mining methods, both have the same attributes of safety and high grade. Both systems remove persons from dangerous working areas and mining is concentrated on the mining channel width resulting in higher grades. Higher grade contributes to ultimate value of the mine.
Use of Artificial Intelligence, Machine Learning and Autonomous Technologies in Mining Industry, South Africa
(University of the Witwatersrand, Johannesburg, 2023) Nong, Setshaba; Sethibe, Tebogo
The mining industry plays a convincing role globally in driving various industries and contributing to economic prosperity. Locally, South Africa is known for having some of the largest minerals reserves in the world, although it is burdened with challenges inhibiting its progress and competitiveness. It is, however, expected that with application of AI, ML and AT will be able to revolutionise the industry, changing its fortunes, which will increase its competitiveness globally in the process attract investment and contribute to its longevity. As a result of these benefits, this research sought to investigate implication of AI, ML, AT technologies implementation in the mining industry of South Africa. The technologies are considered novel, especially in the mining industry, making employing qualitative study appropriate to assess how the implementation is received by the industry including perceptions and its potential impacts. Key findings of the study indicate that these technologies have the capacity to change the trajectory of the South African mining industry by dealing with issues of safety, costs, labour and efficiency. There is also an opportunity to pursue additional resources locked in pillars, by depth and dangerous working conditions due to geological complexities. However, capital costs, the nature of narrow tabular ore bodies and variability of various conditions are found to be some of the inhibiting factors for implementations of these technologies. As a result, there is no mine that has implemented any of these technologies as a primary means of production. This research will measure current perceptions of industry stakeholders and insights, role of government, mining companies, and equipment manufacturing response. The research highlight areas of impact and challenges that will contribute to strategy development in the process contributing to its sustainability. It is important to consider application of theory of constraint which is a detailed analysis which can assist mining companies in identification of inherent challenges so as to be able to respond appropriately with solutions offered by AI, ML and AT