Document Type
Conference Paper
Publication Date
2013
Abstract
Accuracy in haulage analysis is fundamental for reliable cost and productivity estimation. The level of detail to which haulage analysis is conducted can significantly influence these estimations. The recent advancement of computer processing has enabled a range of software to manage large datasets and run multiple and complex haulage scenarios, thus increasing the level of detail. Substantial evidence is available to affirm the benefits of detail in haulage analysis through the scope of truck cycle time and truck prediction methods. However, due to the novelty of advanced software, no literature that documents the level of detail and frequency of haul roads required for haulage analysis was found. It was therefore, the objective of ongoing work for this research project to quantify the value added through additional detail in haulage analysis, specifically, the benefit of frequently changing haul roads. To facilitate this process, nineteen haulage scenarios were analysed with varying detail. In addition, a geological model and topography was created. From the analysis conducted, a clear relationship was identified between decreasing haul road calculation frequency and inverse variance error from the mean cycle time. The research showed that performing two as opposed to a single haulage analyses for a strip can affect the calculated truck cycle times from 6% to 14%. Additionally, it was found that changes in horizontal distance from the endwall were more significant than the vertical change for the analysed strip.
Publication Details
P. Doig and M. S. Kizil, Improvements in truck requirement estimations using detailed haulage analysis, 13th Coal Operators' Conference, University of Wollongong, The Australasian Institute of Mining and Metallurgy & Mine Managers Association of Australia, 2013, 368-375.