Development of a semi-autonomous scale dragline excavation research tool

Leonard, Samuel, Lever, P. and Shekhar, R. (2009). Development of a semi-autonomous scale dragline excavation research tool. In: Peter Knights and Paul J. A. Lever, Proceedings of the 2009 Australian Mining Technology Conference: Technology Solutions for Challenging Financial Times. 2009 Australian Mining Technology Conference: Technological Solutions for Challenging Financial Times, Brisbane, QLD, Australia, (45-54). 27-28 October 2009.

Author Leonard, Samuel
Lever, P.
Shekhar, R.
Title of paper Development of a semi-autonomous scale dragline excavation research tool
Conference name 2009 Australian Mining Technology Conference: Technological Solutions for Challenging Financial Times
Conference location Brisbane, QLD, Australia
Conference dates 27-28 October 2009
Convener CRC Mining
Proceedings title Proceedings of the 2009 Australian Mining Technology Conference: Technology Solutions for Challenging Financial Times
Place of Publication Carlton, VIC, Australia
Publisher The Australasian Institute of Mining and Metallurgy (AusIMM)
Publication Year 2009
Sub-type Fully published paper
ISBN 9781921522130
1921522135
Editor Peter Knights
Paul J. A. Lever
Start page 45
End page 54
Total pages 10
Collection year 2010
Language eng
Formatted Abstract/Summary
In open pit coal mines of the Bowen Basin and Hunter Valley region, draglines are responsible for the largest share of overburden excavation. These machines operate 24 hours a day, seven days a week. Previous research has calculated that for every per cent increase in efficiency the benefit to the mine is roughly one million dollars per annum. Due to the high opportunity cost for a dragline any downtime is unfavourable. Thus sufficient access to an operational dragline for research purposes is a key problem. One solution to this problem is to use scale models.

There are however many problems associated with implementing a scale dragline. Operator variability has been shown to be as high as 40 per cent. This may be due to many reasons such as; digging style, skill level or fatigue. Using human operators on a scale dragline will generate the same type of variability. Material properties such as particle size distribution, moisture content, rock shape, rock length, overburden composition variability can also significantly impact digging performance. Careful consideration of the material properties is required to achieve similarity between scale models and real scale draglines.

This paper presents the development of a semi-autonomous scale dragline to address these problems. An automated digging algorithm that eliminates the variability of a human operator tackles operator variability. As the dig algorithm will always respond with the same digging style, results are reproducible. The problem of material variability has been eliminated by measuring material properties from a coal mine and accurately reproducing those properties in scale. The combination of a computer controlled digging algorithm and accurately scaled materials produces results that are statistically similar to real full scale dragline results.
Subjects E1
091405 Mining Engineering
861404 Mining Machinery and Equipment
Keyword Dragline
Pit coal mine
Excavation
Q-Index Code E1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published under "Automated Mining Technologies".

 
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Created: Wed, 14 Apr 2010, 13:56:06 EST by Katie Gollschewski on behalf of School of Mechanical and Mining Engineering