Development of a predictive model of fragmentation using drilling and blasting data in open pit mining

J. D. Silva; J. G. Amaya; F. Basso

doi:10.17159/2411-9717/2017/v117n11a14

Development of a predictive model of fragmentation using drilling and blasting data in open pit mining

J. D. Silva, J. G. Amaya, F. Basso

Research output: Contribution to journal › Article › peer-review

12 Scopus citations

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, ie. burden, spacing, explosive, among others, to be optimized in order to obtain a more efficient size distribution.

Original language	English
Pages (from-to)	1089-1094
Number of pages	6
Journal	Journal of the Southern African Institute of Mining and Metallurgy
Volume	117
Issue number	11
DOIs	https://doi.org/10.17159/2411-9717/2017/v117n11a14
State	Published - Nov 2017
Externally published	Yes

Keywords

Blast fragmentation
Linear models
Open pit blasting

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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, ie. burden, spacing, explosive, among others, to be optimized in order to obtain a more efficient size distribution.",

keywords = "Blast fragmentation, Linear models, Open pit blasting",

author = "Silva, {J. D.} and Amaya, {J. G.} and F. Basso",

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AU - Amaya, J. G.

AU - Basso, F.

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PY - 2017/11

Y1 - 2017/11

N2 - 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, ie. burden, spacing, explosive, among others, to be optimized in order to obtain a more efficient size distribution.

AB - 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, ie. burden, spacing, explosive, among others, to be optimized in order to obtain a more efficient size distribution.

KW - Blast fragmentation

KW - Linear models

KW - Open pit blasting

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JF - Journal of the Southern African Institute of Mining and Metallurgy

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Development of a predictive model of fragmentation using drilling and blasting data in open pit mining

Abstract

Keywords

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