Research Outputs (Mining Engineering)

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For information on accessing School of Mining Engineering Research Articles content please contact : Salome Potgieter by email : salome.potgieter@wits.ac.za or Tel : 011 717 1961

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Cokriging for optimal mineral resource estimates in mining operations.
(The Southern African Institute of Mining and Metallurgy., 2014) Minnitt, R.C.A.; Deutsch, C.V.
Cokriging uses a sparsely sampled, but accurate and precise primary dataset, together with a more abundant secondary data-set, for example grades in a polymetallic orebody, containing both error and bias, to provide improved results compared to estimation with the primary data alone, as well as filtering the error and mitigating the effects of conditional bias. The method described here may also be applied in polymetallic orebodies and in other cases where the primary and secondary data could be collocated, and one of the data-sets need not be biased, unreliable, etc. An artificially created reference data-set of 512 lognormally distributed precious metal grades sampled at 25×25 m intervals constitutes the primary data-set. A secondary data-set on a 10×10 m grid comprising 3200 samples drawn from the reference data-set includes 30 per cent error and 1.5 multiplicative bias on each measurement. The primary and secondary non-collocated data-sets are statistically described and compared to the reference data-set. Variograms based on the primary data-set are modelled and used in the kriging of 10×10 m blocks using the 25×25 m and 50×50 m data grids for comparison against the results of the cokriged estimation. A linear model of coregionalization (LMC) is established using the primary and secondary data-sets and cokriging using both data-sets is shown to be a significant improvement over kriging with the primary data-set alone. The effects of the error and bias are filtered and removed during the cokriging estimation procedure. Thus cokriging using the more abundant secondary data, even though it contains error and bias, significantly improves the estimation of recoverable reserves.
Just-in-time development model for a sub-level caving underground mine in Zimbabwe.
(The Southern African Institute of Mining and Metallurgy., 2003-04) Musingwini, C.; Minnitt, R.C.A.; Phuti, D.; Makwara, F.
Traditionally, mineral reserves management at most underground mines in Zimbabwe focus on maintaining large mineral reserves so that the time between development and production is as long as possible. Historical data at Shabanie mine, a Zimbabwean sub-level caving underground mining operation, confirms this practice. However, the high cost of underground development means that the luxury of large buffer mineral reserves cannot be justified. Furthermore significant increases in the costs of production, exacerbated by the current unfavourable economic climate, make the wisdom of extending development workings well ahead of use questionable. Poor ground conditions at Shabanie mine, mean that some development ends have to be re-mined two or three times due to partial or complete closure between the time they are mined and the time they are utilized. In order to reduce the inordinately high support costs associated with closure of development ends a new 'Just-in-time' (JIT) approach that provides development ends as and when they are needed, has been adopted. Accordingly a model to determine an appropriate 'just-in-time' rate of development has been created. The JIT development model indicated that the mine could reduce development rates from 330 m/month in 2001, to 160 m/month in 2002 and achieve savings of about 50% on annual support costs, but still assure customers of a long-term product supply. The mine accepted the model in November 2001 and began implementing it in 2002. Results of the implementation will be reviewed in 2003.
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.
Technical operating flexibility in the analysis of mine layouts and schedules.
(The Southern African Institute of Mining and Metallurgy., 2007-02) Musingwini, C.; Minnitt, R.C.A.; Woodhall, M.
Often overlooked factor in the analysis of mine layouts and schedules is technical operating flexibility (or tactical flexibility), mainly due to its nebulous nature. By glossing over technical operating flexibility the resultant mine layouts and schedules may be suboptimal. The need to incorporate technical operating flexibility into the analysis and comparison of mine layouts and schedules is increasing in importance. The nature of technical operating flexibility is illustrated, previous work on valuing of operating flexibility reviewed, and a proposal made on how technical operating flexibility can be quantified for tabular reef mines by using a platinum reef deposit as a case study. Once technical operating flexibility has been quantified it becomes possible to explore its incorporation into the analysis of mine layouts and schedules and subsequent optimization processes. This paper is a revised version of a paper presented in the Proceedings of the Second International Platinum Conference, 'Platinum Surges Ahead' in 2006. The work described in this paper is part of a current PhD study at the University of the Witwatersrand.

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