EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS

Detalhes bibliográficos
Autor(a) principal: Chiaramonte de Castro, Bruno José
Data de Publicação: 2019
Outros Autores: Bernardo, Andre
Tipo de documento: Artigo
Idioma: eng
Título da fonte: The Journal of Engineering and Exact Sciences
Texto Completo: https://periodicos.ufv.br/jcec/article/view/2588
Resumo: In sugarcane industries, process monitoring has the main purpose of maximizing sugar and ethanol production, meeting the quality parameters demanded by customers. The aim of this work was to identify industrial process variables that presented the greatest impacts on the quantity and quality of the produced sugar, by applying principal component analysis (PCA) and partial least squares regression (PLS) to the process data of a sugar and ethanol industry. The PCA correlation matrix highlighted the correlation between the presence of alcoholic flocs in sugar and the concentrations of starch and dextran in it. Both PCA and PLS showed that the color of the sugar was highly correlated to its moisture content. The first three principal components accounted for 40.92% of the total data variability.
id UFV-6_53e9b2d4fd379a97323608bc73e7077f
oai_identifier_str oai:ojs.periodicos.ufv.br:article/2588
network_acronym_str UFV-6
network_name_str The Journal of Engineering and Exact Sciences
repository_id_str
spelling EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODSSugar industryProcess monitoringSugar qualityMultivariate statisticsIn sugarcane industries, process monitoring has the main purpose of maximizing sugar and ethanol production, meeting the quality parameters demanded by customers. The aim of this work was to identify industrial process variables that presented the greatest impacts on the quantity and quality of the produced sugar, by applying principal component analysis (PCA) and partial least squares regression (PLS) to the process data of a sugar and ethanol industry. The PCA correlation matrix highlighted the correlation between the presence of alcoholic flocs in sugar and the concentrations of starch and dextran in it. Both PCA and PLS showed that the color of the sugar was highly correlated to its moisture content. The first three principal components accounted for 40.92% of the total data variability.Universidade Federal de Viçosa - UFV2019-06-28info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/jcec/article/view/258810.18540/jcecvl5iss3pp0228-0237The Journal of Engineering and Exact Sciences; Vol. 5 No. 3 (2019); 0228-0237The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0228-0237The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0228-02372527-1075reponame:The Journal of Engineering and Exact Sciencesinstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/jcec/article/view/2588/3398Chiaramonte de Castro, Bruno JoséBernardo, Andreinfo:eu-repo/semantics/openAccess2019-08-14T20:37:03Zoai:ojs.periodicos.ufv.br:article/2588Revistahttp://www.seer.ufv.br/seer/rbeq2/index.php/req2/oai2527-10752527-1075opendoar:2019-08-14T20:37:03The Journal of Engineering and Exact Sciences - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
title EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
spellingShingle EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
Chiaramonte de Castro, Bruno José
Sugar industry
Process monitoring
Sugar quality
Multivariate statistics
title_short EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
title_full EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
title_fullStr EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
title_full_unstemmed EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
title_sort EVALUATION OF CANE SUGAR PRODUCTION USING MULTIVARIATE STATISTICAL METHODS
author Chiaramonte de Castro, Bruno José
author_facet Chiaramonte de Castro, Bruno José
Bernardo, Andre
author_role author
author2 Bernardo, Andre
author2_role author
dc.contributor.author.fl_str_mv Chiaramonte de Castro, Bruno José
Bernardo, Andre
dc.subject.por.fl_str_mv Sugar industry
Process monitoring
Sugar quality
Multivariate statistics
topic Sugar industry
Process monitoring
Sugar quality
Multivariate statistics
description In sugarcane industries, process monitoring has the main purpose of maximizing sugar and ethanol production, meeting the quality parameters demanded by customers. The aim of this work was to identify industrial process variables that presented the greatest impacts on the quantity and quality of the produced sugar, by applying principal component analysis (PCA) and partial least squares regression (PLS) to the process data of a sugar and ethanol industry. The PCA correlation matrix highlighted the correlation between the presence of alcoholic flocs in sugar and the concentrations of starch and dextran in it. Both PCA and PLS showed that the color of the sugar was highly correlated to its moisture content. The first three principal components accounted for 40.92% of the total data variability.
publishDate 2019
dc.date.none.fl_str_mv 2019-06-28
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufv.br/jcec/article/view/2588
10.18540/jcecvl5iss3pp0228-0237
url https://periodicos.ufv.br/jcec/article/view/2588
identifier_str_mv 10.18540/jcecvl5iss3pp0228-0237
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/jcec/article/view/2588/3398
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
dc.source.none.fl_str_mv The Journal of Engineering and Exact Sciences; Vol. 5 No. 3 (2019); 0228-0237
The Journal of Engineering and Exact Sciences; Vol. 5 Núm. 3 (2019); 0228-0237
The Journal of Engineering and Exact Sciences; v. 5 n. 3 (2019); 0228-0237
2527-1075
reponame:The Journal of Engineering and Exact Sciences
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str The Journal of Engineering and Exact Sciences
collection The Journal of Engineering and Exact Sciences
repository.name.fl_str_mv The Journal of Engineering and Exact Sciences - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv
_version_ 1808845245147774976

Registros relacionados