PROCESS ANALYSIS AND OPTIMIZATION MAPPING THROUGH DESIGN OF EXPERIMENTS AND ITS APPLICATION TO A POLYMERIZATION PROCESS

dc.creatorPontes, KV
dc.creatorMaciel, MRW
dc.creatorMaciel, R
dc.creatorEmbirucu, M
dc.date2011
dc.dateJAN-MAR
dc.date2014-07-30T18:08:24Z
dc.date2015-11-26T17:13:46Z
dc.date2014-07-30T18:08:24Z
dc.date2015-11-26T17:13:46Z
dc.date.accessioned2018-03-29T00:02:07Z
dc.date.available2018-03-29T00:02:07Z
dc.identifierBrazilian Journal Of Chemical Engineering. Brazilian Soc Chemical Eng, v. 28, n. 1, n. 137, n. 150, 2011.
dc.identifier0104-6632
dc.identifierWOS:000288301800015
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/70353
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/70353
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1281651
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionThe technique of experimental design is used on an ethylene polymerization process model in order to map the feasible optimal region as preliminary information for process optimization. Through the use of this statistical tool, together with a detailed deterministic model validated with industrial data, it is possible to identify the most relevant variables to be considered as degrees of freedom for the optimization and also to acquire significant process knowledge, which is valuable not only for future explicit optimization but also for current operational practice. The responses evaluated by the experimental design approach include the objective function and the constraints of the optimization, which also consider the polymer properties. A Plackett-Burman design with 16 trials is first carried out in order to identify the most important inlet variables. This reduces the number of decision variables, hence the complexity of the optimization model. In order to carry out a deeper investigation of the process, complete factorial designs are further implemented. They provide valuable process knowledge because interaction effects, including highly non-linear interactions between the variables, are treated methodically and are easily observed.
dc.description28
dc.description1
dc.description137
dc.description150
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionFAPESB (Fundacao de Amparo a Pesquisa do Estado da Bahia)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.languageen
dc.publisherBrazilian Soc Chemical Eng
dc.publisherSao Paulo
dc.publisherBrasil
dc.relationBrazilian Journal Of Chemical Engineering
dc.relationBraz. J. Chem. Eng.
dc.rightsaberto
dc.sourceWeb of Science
dc.subjectPolyethylene (PE)
dc.subjectDesign of Experiments
dc.subjectPolymerization
dc.subjectModeling and Simulation
dc.subjectOptimization
dc.subjectSemibatch Emulsion Copolymerization
dc.subjectNatta Ethylene Polymerizations
dc.subjectResponse-surface Analysis
dc.subjectFactorial-experiments
dc.subjectReactor Trains
dc.subjectKinetic-model
dc.subjectParameters
dc.subjectSimulation
dc.subjectResins
dc.titlePROCESS ANALYSIS AND OPTIMIZATION MAPPING THROUGH DESIGN OF EXPERIMENTS AND ITS APPLICATION TO A POLYMERIZATION PROCESS
dc.typeArtículos de revistas


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