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 October through 31 December of 2005. Graphical analysis of blast patterns according to drill monitor data is continuing. Multiple linear regression analysis of 16 mine and mill variables (powder factor, two modeled size fractions, liberation index, predicted grind, total crude Fe, Satmagan Fe, sat ratio, DSC, geologic blend, ambient temperature, cobbing hours, feeder plugs, and percent feeder run time-of-mill time) indicates that December variations in plant performance are generally predictable (Figure 1). The outlier on December 28th coincides with low cobbing availability and equipment downtime. Mill productivity appeared to be most influenced, as usual, by ore quality as indicated by the liberation index--the higher the liberation index, the lower the throughput. The upcoming quarter will be concerned with wrapping up the work in progress, such as the detailed statistical analyses, and writing a final report. Hibtac Mine engineers are evaluating neural network software to determine its utility for modeling, and eventually predicting, mill throughput.
- Research Organization:
- Univ. of Missouri, Columbia, MO (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- FC26-03NT41785
- OSTI ID:
- 876104
- Country of Publication:
- United States
- Language:
- English
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Total Ore Processing Integration and Management
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