Development of a predictive model of fragmentation using drilling and blasting data in open pit mining
Author
dc.contributor.author
Silva, J. D.
Author
dc.contributor.author
Amaya Arriagada, Jorge
Author
dc.contributor.author
Basso, F.
Admission date
dc.date.accessioned
2018-05-10T16:52:05Z
Available date
dc.date.available
2018-05-10T16:52:05Z
Publication date
dc.date.issued
2017
Cita de ítem
dc.identifier.citation
Journal of the Southern African institute of mining and metallurgy Vol. 117 (11): 1089-1094
es_ES
Identifier
dc.identifier.other
10.17159/2411-9717/2017/v117n11a14
Identifier
dc.identifier.uri
https://repositorio.uchile.cl/handle/2250/147634
Abstract
dc.description.abstract
This article presents predictive statistical models for fragmentation in open pit mines using drill-and-blast data. The main contribution of this work is the proposing of statistical models to determine the correlations between operational data and fragmentation. The practical use of these models allows the drill-and-blast parameters, i.e. burden, spacing, explosive, among others, to be optimized in order to obtain a more efficient size distribution.