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    Mining truck scheduling with stochastic maintenance cost

    Access Status
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    Authors
    Topal, Erkan
    Ramazan, S.
    Date
    2012
    Type
    Journal Article
    
    Metadata
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    Citation
    Topal, E. and Ramazan, S. 2012. Mining truck scheduling with stochastic maintenance cost. Journal of Coal Science and Engineering. 18 (3): pp. 313-319.
    Source Title
    Journal of Coal Science and Engineering
    DOI
    10.1007/s12404-012-0316-4
    ISSN
    1866-6566
    School
    WASM Mining Engineering Teaching Area
    URI
    http://hdl.handle.net/20.500.11937/49389
    Collection
    • Curtin Research Publications
    Abstract

    Open pit mining operations utilize large scale and expensive equipment. For the mines implementing shovel and truck operation system, trucks constitute a large portion of these equipment and are used for hauling the mined materials. In order to have sustainable and viable operation, these equipment need to be utilized efficiently with minimum operating cost. Maintenance cost is a significant proportion of the overall operating costs. The maintenance cost of a truck changes non-linearly depending on the type, age and truck types. A new approach based on stochastic integer programming (SIP) techniques is used for annually scheduling a fixed fleet of mining trucks in a given operation, over the life of mine (multi-year time horizon) to minimize maintenance cost. The maintenance cost data in mining usually has uncertainty caused from the variability of the operational conditions at mines. To estimate the cost, usually historic data from different operations for new mines, and/or the historic data at the operating mines are used. However, maintenance cost varies depending on road conditions, age of equipment and many other local conditions at an operation. Traditional models aim to estimate the maintenance cost as a deterministic single value and financial evaluations are based on the estimated value. However, it does not provide a confidence on the estimate. The proposed model in this study assumes the truck maintenance cost is a stochastic parameter due to the significant level of uncertainty in the data and schedules the available fleet to meet the annual production targets. The scheduling has been performed by applying both the proposed stochastic and deterministic approaches. The approach provides a distribution for the maintenance cost of the optimized equipment schedule minimizing the cost.

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