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dc.creatorRubino, Felice
dc.creatorCarlone, Pierpaolo
dc.creatorAleksendrić, Dragan
dc.creatorĆirović, Velimir
dc.creatorSorrentino, Luca
dc.creatorBellini, Costanzo
dc.date.accessioned2022-09-19T18:00:03Z
dc.date.available2022-09-19T18:00:03Z
dc.date.issued2016
dc.identifier.issn0094-243X
dc.identifier.urihttps://machinery.mas.bg.ac.rs/handle/123456789/2418
dc.description.abstractThe curing process of thermosetting resins plays a key role on the final quality of the composite material components. Soft computing techniques proved to be an efficient method to control and optimize the curing process, replacing the conventional experimental and numerical approaches. In this paper artificial neural network (ANN) and fuzzy logic control (FLC) were implemented together to predict and control the temperature and degree of cure profile during the autoclave curing process. The obtained outcomes proved the capability of ANNs and FLC with respect to the hard computing methods.en
dc.publisherAmer Inst Physics, Melville
dc.rightsrestrictedAccess
dc.sourceProceedings of The 19th International Esaform Conference on Material Forming (Esaform 2016)
dc.titleHard and Soft Computing Models of Composite Curing Process Looking Toward Monitoring and Controlen
dc.typeconferenceObject
dc.rights.licenseARR
dc.citation.other1769: -
dc.citation.rankM33
dc.citation.volume1769
dc.identifier.doi10.1063/1.4963438
dc.identifier.scopus2-s2.0-84994121536
dc.identifier.wos000392692600034
dc.type.versionpublishedVersion


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