Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/jspui/handle/123456789/9054
Title: Regression model utilization to estimate the mass recovery of a phosphate mine in Brazil.
Authors: Fernandes, Fernanda Gontijo
Cabral, Ivo Eyer
Keywords: Geometallurgy
Multiple regression analysis
Phosphate
Mass recovery
Issue Date: 2016
Citation: 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.
Abstract: 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.
URI: http://www.repositorio.ufop.br/handle/123456789/9054
metadata.dc.identifier.doi: https://doi.org/10.1590/0370-44672015690155
ISSN: 1807-0360
metadata.dc.rights.license: 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.
Appears in Collections:DEMIN - Artigos publicados em periódicos

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