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Title: Total Ore Processing Integration and Management

Abstract

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.

Authors:
Publication Date:
Research Org.:
University of Missouri
Sponsoring Org.:
USDOE
OSTI Identifier:
876104
DOE Contract Number:  
FC26-03NT41785
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; AMBIENT TEMPERATURE; AVAILABILITY; ENGINEERS; MANAGEMENT; MONITORS; NEURAL NETWORKS; ORE PROCESSING; PERFORMANCE; PRODUCTIVITY; REGRESSION ANALYSIS; SIMULATION

Citation Formats

Leslie Gertsch. Total Ore Processing Integration and Management. United States: N. p., 2006. Web. doi:10.2172/876104.
Leslie Gertsch. Total Ore Processing Integration and Management. United States. doi:10.2172/876104.
Leslie Gertsch. Mon . "Total Ore Processing Integration and Management". United States. doi:10.2172/876104. https://www.osti.gov/servlets/purl/876104.
@article{osti_876104,
title = {Total Ore Processing Integration and Management},
author = {Leslie Gertsch},
abstractNote = {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.},
doi = {10.2172/876104},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 30 00:00:00 EST 2006},
month = {Mon Jan 30 00:00:00 EST 2006}
}

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