Impact variables in mining scheduling
DOI:
https://doi.org/10.33448/rsd-v11i12.34146Keywords:
Optimization; Principal component analysis; Advances; Scheduling.Abstract
Mine planning is developed considering economic variables, grades, lithology, spatial position. These variables are used to determine the final pit limit and sequencing of operations. Normally, only the variables related to the grade are exhaustively sampled. The other variables are configured with average values. Multivariate statistical techniques make it possible to determine the variables with the greatest impact. Using a geological model of copper and gold, the final pit and mining sequencing will be determined using the Lerchs-Grossmann algorithm. The resulting block model will be evaluated for non-standard variables in the population. The population elements were standardized and properly transformed into continuous variables. The principal component analysis technique will be used to determine the most important variables of the mine and final pit sequencing. The objective of this work is to determine the most influential variables in determining the final pit and mining sequencing. Mine planning tools only present the end result of planning. They do not point out the most sensitive variables. It is important to determine the variables in which a small change in value is capable of turning a mined block into barren. The work confirmed the importance of economic variables related to the benefit function, however, it quantified that the spatial positioning of the block has similar importance to some economic variables.
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