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    Engineering and Mining Journal

    Access Status
    Fulltext not available
    Authors
    Thompson, Roger
    Date
    2018
    Type
    Journal Article
    
    Metadata
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    Citation
    Thompson, R. 2018. Using big data to predict haul road performance. E&MJ Engineering and Mining Journal. 219 (3): pp. 34-37.
    Source Title
    E&MJ Engineering and Mining Journal
    ISSN
    0095-8948
    School
    WASM: Minerals, Energy and Chemical Engineering (WASM-MECE)
    URI
    http://hdl.handle.net/20.500.11937/74306
    Collection
    • Curtin Research Publications
    Abstract

    Mining companies today are collecting vast amounts of data from equipment to monitor and optimize fleet performance. These same techniques could be used to determine how haul roads perform and how they hold up at the mine site. That knowledge could be integrated with day-to-day haul road management to improve the entire network by focusing maintenance resources where they are needed to make the biggest impact on the bottom line. Haulage represents one of the largest cost elements, especially for deep, large open-pit operations. Today, more than 50% of mining costs are associated with loading and hauling material out of such pits. That translates into significant opportunity to realize cost savings through improved haul road performance. The primary measure of mine road performance is often based on rolling resistance which, when combined with the road grade, is the resistance a haul truck must overcome to move forward. Whilst road grade is fixed by mine geometry, rolling resistance is variable from road to road and also with time and traffic volumes too. All roads deteriorate over time and under the action of traffic and it’s this deterioration that is expressed in the form of rolling resistance. Rolling resistance appears in many forms. With soft underfoot conditions, the truck tire creates a depression, out of which it has to constantly climb as it moves. In this case, rolling resistance occurs as a result of the deformation of the road’s construction layerworks materials. All mine roads will have a minimum amount of rolling resistance – even on the best designed, built and maintained roads – typically 2%-2.5%, but in this case, resistance is primarily from surface defects as opposed to the layerworks as a whole. With poorly designed roads, both sources combine to generate high rolling resistance – a problem that gets worse with rain or excessive watering, which softens construction materials further, leading to yet higher resistance. Accurately measuring, evaluating and modeling rolling resistance can be complicated, but the value of the information is high since it’s rolling resistance that ultimately dictates how a mine’s unit cost of haulage changes in response to road deterioration and its impact on productivity and costs.

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      In truck-based hauling systems, the mine haul road network is a critical and vital component of the production process. As such, under-performance of a haul road will impact immediately on mine productivity and costs. ...
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      The drive for greater cost efficiencies in surface mining has led to the development of ultra-heavy off highway trucks currently capable of hauling payloads of 345 tons. Typical axle loads in excess of 400 tons are ...
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      Well designed and maintained haul roads are the key to minimising truck haulage on-road hazards and costs, as well as increasing productivity. However, practically designing and managing a haul road for optimal performance ...
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