4. Electronic Theses and Dissertations (ETDs) - Faculties submissions
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Item Use of Artificial Intelligence, Machine Learning and Autonomous Technologies in Mining Industry, South Africa(University of the Witwatersrand, Johannesburg, 2023) Nong, Setshaba; Sethibe, TebogoThe 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 ATItem Transforming the mining industry: in search of legal certainty and meaningful empowerment(University of the Witwatersrand, Johannesburg, 2023-02-28) Lawrence, Zinzi Nicollet; Murombo, TumaiThe South African government adopted the Broad-Based Socio-Economic Empowerment Charter for the Mining Industry in 2004 pursuant to section 100(2)(a) of the Mineral and Petroleum Resources Development Act, 2002 to regulate empowerment in the mining industry. Since then, various iterations of the Mining Charter have been published. The legal challenges resulting from the different interpretations of the attainment of the goals set out in the Mining Charter have resulted in uncertainty regarding empowerment and have been the subject of much judicial attention. One of the fundamental issues with the Mining Charter is its status and the lack of authority of the Minister of Mineral Resources and Energy to publish subsequent updated iterations. The growing regulatory burden and uncertainty has increasingly hampered efforts to transform the mining industry. Considering the importance of transformation of the mining industry, this paper analyses the legal and policy impediments to achieving empowerment and proposes solutions to bring about certainty