Conference Proceedings
MetPlant 2008
Conference Proceedings
MetPlant 2008
MillMapper Experiences - A Mill Condition Monitoring and Operational Improvement Case Study
This paper describes the MillMapper technology developed for condition monitoring of liners and other operational parameters in grinding mills used for mineral comminution, by presenting a case study of its application. MillMapper provides maintenance engineers, operations managers and process and plant metallurgists with quantitative, accurate and reliable condition monitoring data for informed decision making regarding the maintenance and metallurgical aspects of such mills._x000D_
MillMapper uses calibrated laser scanners for the capture of three-dimensional surface representations inside a mill during a shutdown so as to determine shell, feed and discharge liner thickness at a resolution of several million data points, a procedure that nominally takes five minutes to complete. Once several data sets over time have been collected inside a mill, MillMapper can be used for liner wear, liner wear zone, liner weight, ball charge volume, ball charge weight and intelligent profile tracking over time. Liner tracking in combination with site defined reline and failure criteria and with throughput tonnage data is utilised for change out prediction of each separate liner segment type._x000D_
FORMAL CITATION:Franke, J, 2008. MillMapper experiences - a mill condition monitoring and operational improvement case study, in Proceedings MetPlant 2008, pp 65-80 (The Australasian Institute of Mining and Metallurgy: Melbourne).
MillMapper uses calibrated laser scanners for the capture of three-dimensional surface representations inside a mill during a shutdown so as to determine shell, feed and discharge liner thickness at a resolution of several million data points, a procedure that nominally takes five minutes to complete. Once several data sets over time have been collected inside a mill, MillMapper can be used for liner wear, liner wear zone, liner weight, ball charge volume, ball charge weight and intelligent profile tracking over time. Liner tracking in combination with site defined reline and failure criteria and with throughput tonnage data is utilised for change out prediction of each separate liner segment type._x000D_
FORMAL CITATION:Franke, J, 2008. MillMapper experiences - a mill condition monitoring and operational improvement case study, in Proceedings MetPlant 2008, pp 65-80 (The Australasian Institute of Mining and Metallurgy: Melbourne).
Contributor(s):
J Franke
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- Published: 2008
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