Institutional Repository
Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/D0A8E5B0-0C65-46FF-BC3E-22647FFF0365 | ||
| Year | 2025 | ||
| Type of Item | Master Thesis | ||
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| Bibliographic Citation | Dimitrios Biniaris, "Stochastic determination of optimal selection of loaders–trucks in open-pit mines/quarries", Master Thesis, School of Mineral Resources Engineering, Technical University of Crete, Chania, Greece, 2025 https://doi.org/10.26233/heallink.tuc.104794 | ||
| Appears in Collections |
This present thesis examines the application of queuing theory to simulate the haulage operation of surface mining operations, aiming to optimize mechanical fleet productivity. The methodology examines the impact of truck waiting time variability at loading points (idle times) in two different case studies, by modifying operational parameters such as dumping locations and equipment layout. Additionally, it includes the estimation of CO₂ emissions and proposes alternative scenarios to reduce emissions per unit of transported material.The queuing theory is applied to two real-world cases: the Ernest Henry Mine in Australia and the SKYRA VASA LTD aggregates quarry in Cyprus. For each case, production is simulated under real conditions, considering key performance indicators (KPIs) of M/M/c/k service systems, mathematically modelled using data provided by SKYRA VASA LTD and literature sources for the case study of Ernest Henry. The models incorporate technical specifications of equipment (e.g., loading, transport, and dumping times) as well as topographical features of each site.Based on the results derived from the M/M/c/k service system models, which were used to evaluate and optimize the efficiency of loading and transport operations in surface mining, considering both productivity and environmental impact, the following findings emerged:• Ernest Henry Mine: The simulation models identified the optimal fleet configu-ration and analyzed scenarios involving the implementation of hybrid trucks equipped with a Trolley Assist System (ST), demonstrating a potential reduction in CO₂ emissions of up to 62%.• SKYRA VASA LTD Quarry: Real operational data were utilized to evaluate system performance and environmental impact. The Match Factor (MF) and queuing theory analysis emphasized the importance of a balanced loader-to-truck ratio and effective equipment layout. These factors significantly influenced productivity, truck waiting times, and fuel consumption. CO₂ emissions were estimated using both theoretical models and actual measurements based on an enhanced Load Factor (LF), highlighting the value of real-world data for accurate energy performance assessment.
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