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Temizyürek, Büsra

University of British Columbia

Dilution is an important factor affecting the profitability and operational costs of mining activities, leading to a potential discrepancies between design intentions and actual operations, commonly referred to as reconciliation. This discrepancy may result in an increase in the tonnage of material to be milled while reducing its value. Despite variations influenced by deposit characteristics, location, and mining practices, dilution is often treated as a fixed value in open-pit mining operations. This study introduces a computer program designed to read and analyze extensive block model datasets. The program automates the computation of dilution, arising from operational errors, empowering users to assess its impact on mine productivity by generating a diluted block model under varied Cut-off Grade (COG) and dilution scenarios. Established for application in an initial phase of mine design and optimization in open pit mining, the program significantly expedites time-intensive dilution calculations. In this study, the program is applied through nine different COG scenarios and four diluting skin percentage applications. The results underscore the value of the program in comprehending the response of the ore body to variations in COG and dilution. It is noteworthy to state that the flexibility of the developed program in modifying conditions, saving time through automated computation, and capturing changes on the block model caused by operational dilution. This is an innovative program in terms of applicability before mine design, the substantial reduction in computation time from days to hours, and the providing of specific insights such as island scenarios. This innovative program offers a computationally affordable and practical solution for mining operations seeking to improve efficiency and accuracy in dilution calculations. By providing a dynamic tool for evaluating and visualizing the impact of dilution under different scenarios, it equips mining professionals with valuable insights in the early stages of mine planning, contributing to more informed decision-making processes.

Text

2023-12-18

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/86970

Mining Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/