Total Ore Processing Integration and Management
This report outlines the technical progress achieved for project DE-FC26-03NT41785 (Total Ore Processing Integration and Management) during the period 01 January through 31 March of 2006. (1) Work in Progress: Minntac Mine--Graphical analysis of drill monitor data moved from two-dimensional horizontal patterns to vertical variations in measured and calculated parameters. The rock quality index and the two dimensionless ({pi}) indices developed by Kewen Yin of the University of Minnesota are used by Minntac Mine to design their blasts, but the drill monitor data from any given pattern is obviously not available for the design of that shot. Therefore, the blast results--which are difficult to quantify in a short time--must be back-analyzed for comparison with the drill monitor data to be useful for subsequent blast designs. {pi}{sub 1} indicates the performance of the drill, while {pi}{sub 2} is a measure of the rock resistance to drilling. As would be expected, since a drill tends to perform better in rock that offers little resistance, {pi}{sub 1} and {pi}{sub 2} are strongly inversely correlated; the relationship is a power function rather than simply linear. Low values of each Pi index tend to be quantized, indicating that these two parameters may be most useful above certain minimum magnitudes. (2) Work in Progress: Hibtac Mine--Statistical examination of a data set from Hibtac Mine (Table 1) shows that incorporating information on the size distribution of material feeding from the crusher to the autogenous mills improves the predictive capability of the model somewhat (43% vs. 44% correlation coefficient), but a more important component is production data from preceding days (26% vs. 44% correlation coefficient), determined using exponentially weighted moving average predictive variables. This lag effect likely reflects the long and varied residence times of the different size fragments in the grinding mills. The rock sizes are also correlated with the geologic layers from which they originate. Additional predictive parameters include electric power drawn by the crusher and the inverse of the average grind index of the ore being milled.
- Research Organization:
- University of Missouri-Rolla
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- FC26-03NT41785
- OSTI ID:
- 883046
- Country of Publication:
- United States
- Language:
- English
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Total Ore Processing Integration and Management
TOTAL ORE PROCESSING INTEGRATION AND MANAGEMENT