Illumination of parameter contributions on uneven break phenomenon in underground stoping mines

© 2016 Published by Elsevier B.V. on behalf of China University of Mining & Technology. One of the most serious conundrum facing the stope production in underground metalliferous mining is uneven break (UB: unplanned dilution and ore-loss). Although the UB has a huge economic fallout to the e...

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Main Authors: Jang, Hyong Doo, Topal, Erkan, Kawamura, Y.
Format: Journal Article
Published: Elsevier 2016
Online Access:http://hdl.handle.net/20.500.11937/38837
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author Jang, Hyong Doo
Topal, Erkan
Kawamura, Y.
author_facet Jang, Hyong Doo
Topal, Erkan
Kawamura, Y.
author_sort Jang, Hyong Doo
building Curtin Institutional Repository
collection Online Access
description © 2016 Published by Elsevier B.V. on behalf of China University of Mining & Technology. One of the most serious conundrum facing the stope production in underground metalliferous mining is uneven break (UB: unplanned dilution and ore-loss). Although the UB has a huge economic fallout to the entire mining process, it is practically unavoidable due to the complex causing mechanism. In this study, the contribution of ten major UB causative parameters has been scrutinised based on a published UB predicting artificial neuron network (ANN) model to put UB under the engineering management. Two typical ANN sensitivity analysis methods, i.e., connection weight algorithm (CWA) and profile method (PM) have been applied. As a result of CWA and PM applications, adjusted Q rate (AQ) revealed as the most influential parameter to UB with contribution of 22.40% in CWA and 20.48% in PM respectively. The findings of this study can be used as an important reference in stope design, production, and reconciliation stages on underground stoping mine.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-388372020-09-07T05:56:23Z Illumination of parameter contributions on uneven break phenomenon in underground stoping mines Jang, Hyong Doo Topal, Erkan Kawamura, Y. © 2016 Published by Elsevier B.V. on behalf of China University of Mining & Technology. One of the most serious conundrum facing the stope production in underground metalliferous mining is uneven break (UB: unplanned dilution and ore-loss). Although the UB has a huge economic fallout to the entire mining process, it is practically unavoidable due to the complex causing mechanism. In this study, the contribution of ten major UB causative parameters has been scrutinised based on a published UB predicting artificial neuron network (ANN) model to put UB under the engineering management. Two typical ANN sensitivity analysis methods, i.e., connection weight algorithm (CWA) and profile method (PM) have been applied. As a result of CWA and PM applications, adjusted Q rate (AQ) revealed as the most influential parameter to UB with contribution of 22.40% in CWA and 20.48% in PM respectively. The findings of this study can be used as an important reference in stope design, production, and reconciliation stages on underground stoping mine. 2016 Journal Article http://hdl.handle.net/20.500.11937/38837 10.1016/j.ijmst.2016.09.019 Elsevier restricted
spellingShingle Jang, Hyong Doo
Topal, Erkan
Kawamura, Y.
Illumination of parameter contributions on uneven break phenomenon in underground stoping mines
title Illumination of parameter contributions on uneven break phenomenon in underground stoping mines
title_full Illumination of parameter contributions on uneven break phenomenon in underground stoping mines
title_fullStr Illumination of parameter contributions on uneven break phenomenon in underground stoping mines
title_full_unstemmed Illumination of parameter contributions on uneven break phenomenon in underground stoping mines
title_short Illumination of parameter contributions on uneven break phenomenon in underground stoping mines
title_sort illumination of parameter contributions on uneven break phenomenon in underground stoping mines
url http://hdl.handle.net/20.500.11937/38837