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Selection criteria for loading and hauling equipment - open pit mining applications

Methods for estimating productivity and costs, and dependent equipment selection process, have needed to be increasingly reliable. Estimated productivity and costs must be as accurate as possible in reflecting actual productivity and costs experienced by mining operations to accommodate the long-term trend for diminishing commodity prices, For loading and hauling equipment operating in open pit mines, some of the interrelated estimating criteria have been investigated for better understanding; and, consequently, more reliable estimates of production and costs, also more effective equipment selection process. Analysis recognizes many of the interrelated criteria as random variables that can most effectively be reviewed, analyzed and compared in terms of statistical mathematical parameters. Emphasized throughout is the need for management of the cyclical loading and hauling system using conventional shovels/excavators/loaders and mining trucks to sustain an acceptable “rhythm” for best practice productivity and most-competitive unit-production costs. Outcomes of the research include an understanding that variability of attributes needs to be contained within acceptable limits. Attributes investigated include truck payloads, bucket loads, loader cycle time, truck loading time and truck cycle time. Selection of “ultra-class” mining trucks (≥ 290 -tonne payload) and suitable loading equipment is for specialist mining applications only. Where local operating environment and cost factors favourably supplement diminishing cost-benefits of truck scale, ultra-class trucks may be justified. Bigger is not always better – only where bigger can be shown to be better by reasons in addition to the modest cost benefits of ultra-class equipment. Truck over-loading may, to a moderate degree, increase productivity, but only at increased unit cost. / From a unit-cost perspective it is better to under-load than overload mining trucks. Where unit production cost is more important than absolute productivity, under-trucking is favoured compared with over-trucking loading equipment. Bunching of mining trucks manifests as a queuing effect – a loss of effective truck hours. To offset the queuing effect, required productivity needs to be adjusted to anticipate “bunching inefficiency”. The “basic number of trucks” delivered by deterministic estimating must provide for bunching inefficiency before application of simulation applications or stochastic analysis is used to determine the necessary number of trucks in the fleet. In difficult digging conditions it is more important to retain truck operating rhythm than to focus on achieving target payload by indiscriminately adding loader passes. Where trucks are waiting to load, operational tempo should be restored by sacrificing one or more passes. Trucks should preferably be loaded by not more than the nominal (modal) number plus one pass. The research has: • Identified and investigated attributes that affect the dispersion of truck payloads, bucket loads, bucket-cycle time, loading time and truck-cycle time. • The outcomes of the research indicate a need to correlate drilling and blasting quality control and truck payload dispersion. Further research can be expected to determine the interrelationship between accuracy of drilling and blasting attributes including accuracy of hole location and direction. • Preliminary investigations indicate a relationship between drill-and-blast attributes through blasting quality control to bucket design, dimensions and shape; also discharge characteristics that affect bucket cycle time that needs further research.

Identiferoai:union.ndltd.org:ADTP/222956
Date January 2007
CreatorsHardy, Raymond J
PublisherCurtin University of Technology, Western Australian School of Mines.
Source SetsAustraliasian Digital Theses Program
LanguageEnglish
Detected LanguageEnglish
Rightsunrestricted

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