Browsing by Author "Massawe, Antipas T. S."

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    Modeling the Impact of Mine and Country Variations on the Cost and Country-Benefit of Gold Mining
    (Scientific Research, 2011) Baruti, Karim R.; Massawe, Antipas T. S.; Kundi, Beatus A. T.
    This paper dwells on regression models of cash-cost and country-benefit developed to enable accounting for the cumulative impact of the determinant parameters in the prediction of cash-costs and country-benefits of gold mining opportunities in the justification of taxation regimes and selection of investment targets worldwide. The data used in the generation of regression models include the total cash-cost and country-benefit per ounce vs the parameters of rock-mass (type of ore body, its dip angle, strike length and thickness), mine-design (rate of gold production, type of mine, depth of mine, gold price and age of mine) and country parameters (the Fraser Institute parameters: taxation regime, infrastructure, environmental regime, political stability, labor regulations and security) were generated from 160 gold mines in the top 20 gold rich countries for a period of 7 years from 2002 to 2008. The regression models show that the determinants account for 71% and 55% of the determinants of cash-cost and country-benefit respectively. Depending on the availability of data, the regression models generated in this study could be enhanced by adding into the parameters used in the regression analysis, the unaccounted for mine and country parameters. Also, Depending on the availability of data, the Regression models generated in this study could be enhanced further by replacing the parameters of Fraser Institute ranking used in the regression analysis with the actual parameters of country effect on cash-cost and country-benefit of the gold produced. Nevertheless, the regression models generated in this study could be used to predict the cash-costs and country-benefits of gold mining opportunities in the justification of taxation regimes and selection of investment targets worldwide.
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    Regression Models of the Impact of Rockmass and Blast Design Variations on the Effectiveness of Iron Ore Surface Blasting
    (Scientific Research, 2011) Massawe, Antipas T. S.; Baruti, Karim R.
    The desired economics of hard rock surface mining is mainly determined by the para-meters of process design which minimize the overall cost per tonne of the rock mined in drilling, blasting, handling and primary crushing in given rockmass conditions. The most effective parameters of process design could be established based on the regression models of the cumulative influence of rockmass and mine design parameters on the overall cost per tonne of the rock drilled, blasted, handled and crushed. These models could be developed from the huge data accumulated worldwide on the costs per tonne of hard rock surface mining in drilling, blasting, handling and primary crushing vs the parameters of rockmass and mine design. This paper only dwelt on the development of regression models for oversize generation, blasthole productivity and blasting cost for iron ore surface mines, whose data is available. The SPSS standard statistical correlation – regression analysis software was used in the analysis. Interpretation of the models generated shows that the individual effects of the determinant rockmass and blast design parameters on oversize generation, blasthole productivity and blasting cost are all in compliance with the findings of other researchers and the theory of explosive rock fragmentation and could be used for the estimation of oversize generation, blasthole productivity and blasting cost in rockmass and blast design conditions similar to those of the iron ore surface mines examined in this study. However, the regression models obtained here could not be used alone for the optimization of blast design because most of the determinant parameters also have conflicting effect on the other processes of drilling, handling and primary crushing the blasted rock. Also, the quality and content of the regression models could be enhanced further by increasing the content of rockmass and blast design parameters and the volume of data considered in the regression analysis.
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    Theoretical Basis in Regression Model Based Selection of the Most Cost Effective Parameters of Hard Rock Surface Mining
    (Scientific Research, 2011) Massawe, Antipas T. S.; Baruti, Karim R.; Gongo, Paul S. M.
    What determines selection of the most cost effective parameters of hard rock surface mining is consideration of all alternative variants of mine design and the conflicting effect of their parameters on cost. Consideration could be realized based on the mathematical model of the cumulative influence of rockmass and mine design variables on the overall cost per ton of the hard rock drilled, blasted, hauled and primary crushed. Available works on the topic mostly dwelt on four processes of hard rock surface mining separately. This paper dwells on the theoretical part of a research proposed to enhance effectiveness in the selection of the parameters of hard rock surface mining design based on the regression model of overall cost per tonne of the rock mined fit on the determinant variations of rockmass and mine design. The regression model could be developed based on the statistical data generated by many of the hard rock surface mines operating in variable conditions of rockmass and mine design worldwide. Also, a regression model based general algorithm has been formulated for the development of software and computer aided selection of the most cost effective parameters of hard rock surface mining.