dc.contributorBernardo, André
dc.contributorhttp://lattes.cnpq.br/5705402824877708
dc.contributorhttp://lattes.cnpq.br/9306599334757765
dc.creatorCastro, Bruno José Chiaramonte de
dc.date.accessioned2019-04-17T17:49:39Z
dc.date.available2019-04-17T17:49:39Z
dc.date.created2019-04-17T17:49:39Z
dc.date.issued2019-02-25
dc.identifierCASTRO, Bruno José Chiaramonte de. Avaliação da produção de açúcar utilizando reconciliação de dados, estatística multivariada e modelagem fenomenológica da cristalização. 2019. Dissertação (Mestrado em Engenharia Química) – Universidade Federal de São Carlos, São Carlos, 2019. Disponível em: https://repositorio.ufscar.br/handle/ufscar/11254.
dc.identifierhttps://repositorio.ufscar.br/handle/ufscar/11254
dc.description.abstractSugarcane, grown in more than a hundred countries, is one of the major crops of the world. Brazil is the world’s largest producer. Sugarcane industries are constantly seeking to reduce the industrial process losses, to reduce the process variability, and to greater understand and control the phenomena involved in the sucrose crystallization. Thus, the first approach of this work aimed at quantifying the contribution of the sugar manufacturing sector to the total undetermined losses of a sugar and ethanol plant. To this end, a method based on data reconciliation for the process flow rates and concentrations was used. This method could be applied to any equipment or sector of the industry in order to rapidly identify sugar losses that are not currently quantified. The second approach of the work aimed at identifying the major sources of variation in the quantity and quality of the produced sugar, by applying two multivariate statistical techniques (PCA – Principal Component Analysis, and PLS – Partial Least Squares) to the data from the same industry. Lastly, the third objective of the work was to implement a model to the two-massecuite system for sucrose crystallization, based on the first principles of mass and energy conservations, and on the crystal population balance, including the phenomena of nucleation and growth rate dispersion. Microsoft Excel was used for the process data reconciliation, software Minitab for the multivariate statistical analyses, and EMSO simulator for the implementation of the phenomenological model of the crystallization process. From data reconciliation, 37.3% of undetermined losses were found to occur in the sugar manufacturing sector, between juice concentration and sugar bagging. The PCA highlighted the high 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, indicating that the phenomena of inclusion and occlusion of molasses in the crystals contributed significantly to increased crystal color. In the simulation of the two-massecuite crystallization process, the crystal mean size reached 0.64 mm, with coefficient of variation equal to 30.58%. These results approximated the real data of the studied plant, in which the crystal mean size was 0.65 mm, with coefficient of variation equal to 25.36%.
dc.languagepor
dc.publisherUniversidade Federal de São Carlos
dc.publisherUFSCar
dc.publisherPrograma de Pós-Graduação em Engenharia Química - PPGEQ
dc.publisherCâmpus São Carlos
dc.rightsAcesso aberto
dc.subjectPerdas indeterminadas
dc.subjectReconciliação de dados
dc.subjectIndústria de açúcar
dc.subjectAnálise multivariada
dc.subjectCristalização da sacarose
dc.subjectModelagem fenomenológica
dc.subjectSimulação
dc.subjectUndetermined losses
dc.subjectData reconciliation
dc.subjectSugar industry
dc.subjectMultivariate analysis
dc.subjectSucrose crystallization
dc.subjectPhenomenological modelling
dc.subjectSimulation
dc.titleAvaliação da produção de açúcar utilizando reconciliação de dados, estatística multivariada e modelagem fenomenológica da cristalização
dc.typeTesis


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