School of Mining Engineering

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Online database of mine planning and peripheral software used in the South African mining industry.
(The Southern African Institute of Mining and Metallurgy., 2013-06) Katakwa, T.P.; Musingwini, C.; Genc, B.
The utilization of software is now inherent to virtually every activity along the mining value chain. However, apart from the software survey done by Gibbs in the 1990s and work on the extent of diffusion of information and communication technology (ICT) in the South African platinum sector by Mugodi and Fleming in 2003, the nature and extent of software utilization in the South African mining industry has never been evaluated. The Mine Planning, Optimisation and Valuation (MPOV) Research Group in the School of Mining Engineering, University of Witwatersrand, therefore initiated a project to collate and analyse the current utilization of software in the South African mining industry. This was done through the development of a web-based database of the relevant software. Snowball sampling was used to collect the data because the South African mining industry is diverse and software utilization is fragmented across and within the sectors of the industry. The data was then organized into distinct categories so that the information from a variety of sources could be evaluated on the same basis. A beta version of the database can be accessed online through a user-friendly front-end platform at http://db.mining.wits.ac.za. The database is expected to help at least 13 educational institutions with decisions on facilities and training that are vital to the education of mining and mining-related professionals. Exploration, mining, and consulting companies will also benefit from information in the database relating to availability and useful combinations of software solutions. The database is also strategic to software providers by providing a better understanding of their respective relative market share along the mining value chain. An analysis of the data collated in this research shows that about 77% of the software users are mining companies, 17% are consulting companies, 3% are mineral exploration companies, and the rest are software providers and educational institutions. The software used in the South African mining industry is largely provided by Gemcom Software International, MineRP Solutions, and MRM Mining Services. CAE Mining, who in 2010 acquired the Datamine Group providing Datamine software, is also widely acknowledged as a major software supplier in South Africa, but data from them had not been obtained at the time of producing the beta version of the database due to proprietary constraints. The work reported in this paper is part of an MSc research study in the School of Mining Engineering at the University of the Witwatersrand.
Sampling in the South African minerals industry.
(The Southern African Institute of Mining and Metallurgy., 2014) Minnitt, R.C.A.
Although not fully accepted in South Africa, the Theory of Sampling originally proposed by Pierre Gy is fast becoming the cornerstone of sampling practice throughout the world. The growing acceptance of Gy's Theory of Sampling in South Africa can be attributed to a number of factors, chief amongst them being the development of a tradable mineral asset market, the promulgation of the Mineral and Petroleum Resources Development Act (MPRDA), the growing number of commercial and academic courses that are offered on sampling, and the regulation of the industry through internationally acceptable guidelines and rules for reporting and trading in mineral assets. The size of the South African minerals industry and the dependence of our economy on mineral production have also meant that correct sampling is of key importance to mineral trade. ISO standards have been the principal guides for producers of mineral bulk commodities who produce to customers' specifications, whereas Gy's insights have been most readily accepted by precious and base metals producers whose product is sold into metal markets. Understanding of small-scale variability is essential in the precious and base-metal industries, but detailed studies of the effects of heterogeneity have not been as productive in the bulk commodities. Sampling practices at different stages of mineral development from exploration, face sampling and grade control, ore processing and handling, metallurgical sub-sampling, point of sale sampling, and sampling in the laboratory are considered in the gold, platinum, ferrous metal, and coal industries. A summary of the impact of poor sampling in these industries is presented. Generally it appears that poor sampling practice is most likely to erode mineral asset value at the early stages of mineral development. The benefits of good sampling are considered, especially with regard to the financial implications of bias and error on large and consistent consignments of bulk commodities.

School of Mining Engineering

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