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Conference Proceedings

Mining Geology 2014

Conference Proceedings

Mining Geology 2014

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Optimum Dig Lines for Open Pit Grade Control

Critical reviews of grade control generally focus on blasthole sampling and the estimation of ore control block model (OCM) grades, with little or no attention given to dig-line design. For example, the estimation of block grades is deemed important as estimation errors lead to the misclassification of ore types and subsequent dollar loss. Recognition of the problem that the underestimation of block grades may be more or less costly than overestimation led to the application of loss functions to the classification of individual OCM blocks by ore type. The method is known as maximum profit selection (MPS). However, each OCM block may be misclassified a second time by dig-line design. Although each block may initially be assigned an optimum ore type by MPS, OCM blocks are seldom individually mineable by ore type. As a result, a common solution to this problem is the design of mineable polygons or dig lines loosely constrained by a minimum mining width. All material within a properly designed dig-line polygon can be mined and sent to a single destination such as the mill, stockpile or waste dump. These dig lines are often designed manually or by simple variations of computer-generated contour lines. They are generally suboptimal and result in additional misclassifications of ore types. This paper provides an algorithm for constrained optimum dig-line design where dig-line misclassifications are also evaluated through loss functions or MPS. Constrained optimum dig-line designs minimise the dollars lost by dig line misclassifications for a given minimum mining width constraint. A case study is provided illustrating constrained optimum dig-line design and subsequent benefits.CITATION:Isaaks, E, Treloar, I and Elenbaas, T, 2014. Optimum dig lines for open pit grade control, in Proceedings Ninth International Mining Geology Conference 2014 , pp 425-432 (The Australasian Institute of Mining and Metallurgy: Melbourne).
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  • Published: 2013
  • PDF Size: 3.513 Mb.
  • Unique ID: P201407048

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