32 research outputs found

    ODREĐIVANJE ELASTIČNE GRANICE ISKOPA KOD VELIKIH PODZEMNIH RUDARSKIH PROJEKATA

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    Uncertainty-based stope boundary optimization is a complex part of underground mine planning, especially in mass mining projects and notably block caving. Besides, grade variation and grade uncertainty are significant sources of error in mining projects. This paper presents a procedure to determine a resilient block-cave stope boundary considering the ore grade uncertainties. The procedure applies the floating stope algorithm, the maximum upside/minimum downside, and the value at risk for design evaluation. The floating stope algorithm is customized for block caving and is used to determine the stope boundary over some simulated grade models. The idea fits into a multi-criteria decision-making problem. Finally, the most resilient stope boundary is selected by considering several criteria and the TOPSIS method. According to the results, the resilient stope boundary covers an area where the mineable reserve is 977 Mt with an average copper grade of 0.51%.Optimizacija granica iskopa metodom temeljenom na nesigurnosti složen je dio projektiranja podzemnih rudnika, posebno u projektima masovnoga rudarenja te u metodi blokovskoga iskopa. Osim toga, varijacija u stupnju i nesigurnost sadržaja rude česti su izvori pogrešaka u rudarskim projektima. Ovaj rad predstavlja postupak za određivanje elastične granice blokovskoga iskopa uzimajući u obzir nesigurnosti sadržaja rude. Postupak primjenjuje algoritam plutajućih granica iskopa, maksimalno dobru / minimalno lošu stranu i rizičnu vrijednost za ocjenu dizajna. Algoritam plutajućih granica iskopa prilagođen je za blokovsku metodu iskopa i koristi se za određivanje granice iskopa preko određenih simuliranih stupnjevitih modela. Ideja se uklapa u višekriterijski problem odlučivanja. Konačno, odabire se najelastičnija granica iskopa uzimajući u obzir nekoliko kriterija i TOPSIS metodu. Prema rezultatima elastična granica iskopa pokriva područje gdje eksploatacijske rezerve iznose 977 Mt s prosječnim sadržajem bakra od 0,51 %

    Unplanned dilution and ore-loss optimisation in underground mines via cooperative neuro-fuzzy network

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    The aim of study is to establish a proper unplanned dilution and ore-loss (UB: uneven break) management system. To achieve the goal, UB prediction and consultation systems were established using artificial neural network (ANN) and fuzzy expert system (FES). Attempts have been made to illuminate the UB mechanism by scrutinising the contributions of potential UB influence factors. Ultimately, the proposed UB prediction and consultation systems were unified as a cooperative neuro fuzzy system
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