On the prediction of mucking rates in metal ore blasting

A model for the calculation of the productivity of cyclic excavators is developed. The production rate results as a product of an ideal, maximum, productivity rate (one of the coefficients of the model) times an operating efficiency. The latter is described as a function of three variables (rock strength, nominal bucket capacity and explosive energy concentration) and three more coefficients. The coefficients of the model have been obtained from field measurements in twenty production blasts at two open pit mines, for which mechanical properties of the rock, blasting characteristics and mucking rates were carefully measured. The model is statistically significant and explains up to 90 % of the variance of the production rate measurements.

[1]  Resat Ulusay,et al.  Evaluation of the block punch index test with particular reference to the size effect, failure mechanism and its effectiveness in predicting rock strength , 2001 .

[2]  Samuel Frimpong,et al.  Cable shovel digging optimization for energy efficiency , 2007 .

[3]  Essaieb Hamdi,et al.  Blast induced micro cracks assessment in muckpile blocks: P-wave velocity and porosity measurements , 2003 .

[4]  A. Kavetsky,et al.  A two-dimensional kinematic model for predicting muckpile shape in bench blasting , 1989 .

[5]  Andrew Hall,et al.  Characterizing the operation of a large hydraulic excavator , 2003 .

[6]  S. Kahraman.  Evaluation of simple methods for assessing the uniaxial compressive strength of rock , 2001 .

[7]  P. D. Katsabanis,et al.  Fragmentation prediction using improved engineering formulae , 2000 .

[8]  Werner Swanepoel.  The influence of bench height and equipment selection on effective mineral resource utilization , 2005 .

[9]  J. Sanchidrián,et al.  Calculation of the Energy of Explosives with a Partial Reaction Model. Comparison with Cylinder Test Data , 2006 .

[10]  H. Hartman.  SME mining engineering handbook , 1992 .

[11]  D. M. Thornton,et al.  Impact of blast fragmentation on hydraulic excavator dig time , 2003 .

[12]  Finn Ouchterlony,et al.  Fragmentation monitoring of production blasts at Mrica , 1990 .

[13]  A. R. Mattis,et al.  Efficiency of excavation of overburden rock at quarries with the use of blast-free technology , 1997 .

[14]  A. Hekmat,et al.  Prediction of Shovel Productivity in the Gol-e-Gohar Iron Mine , 2005 .

[15]  D. Groves,et al.  Geology and SHRIMP U-Pb Geochronology of the Igarapé Bahia Deposit, Carajás Copper-Gold Belt, Brazil: An Archean (2.57 Ga) Example of Iron-Oxide Cu-Au-(U-REE) Mineralization , 2005 .

[16]  J. A. Franklin,et al.  Suggested method for determining point load strength , 1985 .

[17]  J. Miller,et al.  Statistics and chemometrics for analytical chemistry , 2005 .

[18]  G. R. Adhikari,et al.  Estimating rock properties using sound levels produced during drilling , 2009 .

[19]  Per-Anders Persson,et al.  Rock Blasting and Explosives Engineering , 1993 .