Estimation of incremental haulage costs by mining historical data and their influence in the final pit limit definition

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

This paper describes the application of modern data-analysis tools, such as data mining, to determine a representative cost driver for haulage activity. This cost driver was subsequently used to trace incurred haul costs by bench for openpit optimization. For this purpose, large amount of previously unused cost and production data from an open pit mine was extracted, loaded, transformed and integrated into a data warehouse. Predictive modeling was performed using Microsoft Decision Trees algorithm to compute expected unit haul costs by bench for future mine expansions. Finally, a sensitivity analysis was carried out to determine the effect of two cost drivers (if any) for incremental haul costs in the final pit outline process.

Original languageEnglish (US)
Pages (from-to)44-49
Number of pages6
JournalMining Engineering
Volume60
Issue number10
StatePublished - Oct 2008

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haulage
Data mining
cost
Costs
open pit mine
Data warehouses
data mining
Decision trees
Sensitivity analysis
sensitivity analysis
modeling

ASJC Scopus subject areas

  • Geotechnical Engineering and Engineering Geology

Cite this

Estimation of incremental haulage costs by mining historical data and their influence in the final pit limit definition. / Benito, R.; Dessureault, Sean D.

In: Mining Engineering, Vol. 60, No. 10, 10.2008, p. 44-49.

Research output: Contribution to journalArticle

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