Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.

Detalhes bibliográficos
Autor(a) principal: Fernandes, Fernanda Gontijo
Data de Publicação: 2016
Outros Autores: Cabral, Ivo Eyer
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFOP
Texto Completo: http://www.repositorio.ufop.br/handle/123456789/9054
https://doi.org/10.1590/0370-44672015690155
Resumo: The construction of block models with an estimation of grades in situ is a common practice throughout resource evaluation. However, this information is not enough to understand the behavior of the ore in the beneficiation process. Geometallurgy proposes the addition of the ore´s metallurgical behavior in the block model, making it more dependable and adhering when it comes to production capacity, which generates financial earnings and brings risks down. Mass recovery is an important metallurgical variable for economic and mine planning. This is often underused, due to the lack of data, making it hard to use in the planning process. In order to achieve better use of the data available, the multiple regression analysis technique was used so as to develop a statistic model that would relate the mass recovery with the in situ grades, allowing that deposit regions with no available metallurgical information have an estimation of this variable’s values.
id UFOP_5886c2c7a6e29c0946a5f574fddf89d5
oai_identifier_str oai:localhost:123456789/9054
network_acronym_str UFOP
network_name_str Repositório Institucional da UFOP
repository_id_str 3233
spelling Fernandes, Fernanda GontijoCabral, Ivo Eyer2017-10-26T11:53:13Z2017-10-26T11:53:13Z2016FERNANDES, F. G.; CABRAL, I. E. Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil. Revista Escola de Minas, v. 69, p. 75-77, 2016. Disponível em: <http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672016000100075>. Acesso em: 25 ago. 2017.1807-0360http://www.repositorio.ufop.br/handle/123456789/9054https://doi.org/10.1590/0370-44672015690155The construction of block models with an estimation of grades in situ is a common practice throughout resource evaluation. However, this information is not enough to understand the behavior of the ore in the beneficiation process. Geometallurgy proposes the addition of the ore´s metallurgical behavior in the block model, making it more dependable and adhering when it comes to production capacity, which generates financial earnings and brings risks down. Mass recovery is an important metallurgical variable for economic and mine planning. This is often underused, due to the lack of data, making it hard to use in the planning process. In order to achieve better use of the data available, the multiple regression analysis technique was used so as to develop a statistic model that would relate the mass recovery with the in situ grades, allowing that deposit regions with no available metallurgical information have an estimation of this variable’s values.A REM - International Engineering Journal - autoriza o depósito de cópia de artigos dos professores e alunos da UFOP no Repositório Institucional da UFOP. Licença concedida mediante preenchimento de formulário online em 12 set. 2013.info:eu-repo/semantics/openAccessGeometallurgyMultiple regression analysisPhosphateMass recoveryRegression model utilization to estimate the mass recovery of a phosphate mine in Brazil.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPLICENSElicense.txtlicense.txttext/plain; charset=utf-8924http://www.repositorio.ufop.br/bitstream/123456789/9054/2/license.txt62604f8d955274beb56c80ce1ee5dcaeMD52ORIGINALARTIGO_RegressionModelUtilization.pdfARTIGO_RegressionModelUtilization.pdfapplication/pdf143111http://www.repositorio.ufop.br/bitstream/123456789/9054/1/ARTIGO_RegressionModelUtilization.pdf189b04b3c3cd48cd16ee1eeae0c17027MD51123456789/90542020-02-17 10:54:17.443oai:localhost: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ório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332020-02-17T15:54:17Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false
dc.title.pt_BR.fl_str_mv Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
title Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
spellingShingle Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
Fernandes, Fernanda Gontijo
Geometallurgy
Multiple regression analysis
Phosphate
Mass recovery
title_short Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
title_full Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
title_fullStr Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
title_full_unstemmed Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
title_sort Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
author Fernandes, Fernanda Gontijo
author_facet Fernandes, Fernanda Gontijo
Cabral, Ivo Eyer
author_role author
author2 Cabral, Ivo Eyer
author2_role author
dc.contributor.author.fl_str_mv Fernandes, Fernanda Gontijo
Cabral, Ivo Eyer
dc.subject.por.fl_str_mv Geometallurgy
Multiple regression analysis
Phosphate
Mass recovery
topic Geometallurgy
Multiple regression analysis
Phosphate
Mass recovery
description The construction of block models with an estimation of grades in situ is a common practice throughout resource evaluation. However, this information is not enough to understand the behavior of the ore in the beneficiation process. Geometallurgy proposes the addition of the ore´s metallurgical behavior in the block model, making it more dependable and adhering when it comes to production capacity, which generates financial earnings and brings risks down. Mass recovery is an important metallurgical variable for economic and mine planning. This is often underused, due to the lack of data, making it hard to use in the planning process. In order to achieve better use of the data available, the multiple regression analysis technique was used so as to develop a statistic model that would relate the mass recovery with the in situ grades, allowing that deposit regions with no available metallurgical information have an estimation of this variable’s values.
publishDate 2016
dc.date.issued.fl_str_mv 2016
dc.date.accessioned.fl_str_mv 2017-10-26T11:53:13Z
dc.date.available.fl_str_mv 2017-10-26T11:53:13Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.citation.fl_str_mv FERNANDES, F. G.; CABRAL, I. E. Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil. Revista Escola de Minas, v. 69, p. 75-77, 2016. Disponível em: <http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672016000100075>. Acesso em: 25 ago. 2017.
dc.identifier.uri.fl_str_mv http://www.repositorio.ufop.br/handle/123456789/9054
dc.identifier.issn.none.fl_str_mv 1807-0360
dc.identifier.doi.none.fl_str_mv https://doi.org/10.1590/0370-44672015690155
identifier_str_mv FERNANDES, F. G.; CABRAL, I. E. Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil. Revista Escola de Minas, v. 69, p. 75-77, 2016. Disponível em: <http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0370-44672016000100075>. Acesso em: 25 ago. 2017.
1807-0360
url http://www.repositorio.ufop.br/handle/123456789/9054
https://doi.org/10.1590/0370-44672015690155
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFOP
instname:Universidade Federal de Ouro Preto (UFOP)
instacron:UFOP
instname_str Universidade Federal de Ouro Preto (UFOP)
instacron_str UFOP
institution UFOP
reponame_str Repositório Institucional da UFOP
collection Repositório Institucional da UFOP
bitstream.url.fl_str_mv http://www.repositorio.ufop.br/bitstream/123456789/9054/2/license.txt
http://www.repositorio.ufop.br/bitstream/123456789/9054/1/ARTIGO_RegressionModelUtilization.pdf
bitstream.checksum.fl_str_mv 62604f8d955274beb56c80ce1ee5dcae
189b04b3c3cd48cd16ee1eeae0c17027
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)
repository.mail.fl_str_mv repositorio@ufop.edu.br
_version_ 1801685780591017984