Using Run-of-mine Tonnage and Grade to Predict Cost and Categorize Gold Mines

Abstract

This paper focuses on establishing logistic model of cost effect of run-of-mine tonnage and grade in the justification of categorization of gold mines. Gold mines could be categorized based on the abilities of rom-grade and rom-tonnage to predict cost. The data used in the generation of the logistic model were cash-cost as dependent variable vs. rom-grade, rom-tonnage as independent variables together with the type of mine obtained from 160 gold mines selected from the top 20 gold rich countries in the period of 7 years from 2002 to 2008. Logistic Regression Analysis using SPSS software was carried out to determine the probability of occurrence of low cost given rom-grade and rom-tonnage for either an open pit, underground or both mines together. The results indicated that only rom-grade with a cut-off value 5.385 g/t can be used to categorize gold mines as low and high grade while there was not enough evidence to categorize gold mines based on their rom-tonnage. The full model established in this study has a percentage correct of 62.9 compared to 57.9 percent by guess. The relationship between cost vs. rom-grade and rom-tonnage indicated that only 6.9 percent of the cost is accounted by rom-grade and rom-tonnage. This is a weak relation indicating that rom-grade and rom-tonnage are not the only determinants and therefore on their own must be used with precaution. Validation of the model agrees well with the actual results.

Authors and Affiliations

Karim Rajabu Baruti

Keywords

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  • EP ID EP497902
  • DOI -
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How To Cite

Karim Rajabu Baruti (2018). Using Run-of-mine Tonnage and Grade to Predict Cost and Categorize Gold Mines. International Journal of Engineering Innovations and Research, 7(3), 152-158. https://europub.co.uk/articles/-A-497902