{"data":{"id":"10.6084/m9.figshare.6273293","type":"dois","attributes":{"doi":"10.6084/m9.figshare.6273293","prefix":"10.6084","suffix":"m9.figshare.6273293","identifiers":[],"alternateIdentifiers":[],"creators":[{"name":"Seretis, Georgios","nameType":"Personal","givenName":"Georgios","familyName":"Seretis","affiliation":[],"nameIdentifiers":[]},{"name":"Kouzilos, Georgios","nameType":"Personal","givenName":"Georgios","familyName":"Kouzilos","affiliation":[],"nameIdentifiers":[]},{"name":"Manolakos, Dimitrios","nameType":"Personal","givenName":"Dimitrios","familyName":"Manolakos","affiliation":[],"nameIdentifiers":[]},{"name":"Provatidis, Christopher","nameType":"Personal","givenName":"Christopher","familyName":"Provatidis","affiliation":[],"nameIdentifiers":[]}],"titles":[{"title":"Multi-Objective Curing Cycle Optimization for Glass Fabric/Epoxy Composites Using Poisson Regression and Genetic Algorithm"}],"publisher":"SciELO journals","container":{},"publicationYear":2018,"subjects":[{"subject":"90499 Chemical Engineering not elsewhere classified","subjectScheme":"FOR"},{"subject":"FOS: Chemical engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Chemical engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"91207 Metals and Alloy Materials","subjectScheme":"FOR"},{"subject":"FOS: Materials engineering","schemeUri":"http://www.oecd.org/science/inno/38235147.pdf","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"FOS: Materials engineering","subjectScheme":"Fields of Science and Technology (FOS)"},{"subject":"91299 Materials Engineering not elsewhere classified","subjectScheme":"FOR"}],"contributors":[],"dates":[{"date":"2018-05-16","dateType":"Created"},{"date":"2018-05-16","dateType":"Updated"},{"date":"2018","dateType":"Issued"}],"language":null,"types":{"ris":"DATA","bibtex":"misc","citeproc":"dataset","schemaOrg":"Dataset","resourceType":"Dataset","resourceTypeGeneral":"Dataset"},"relatedIdentifiers":[{"relationType":"IsSupplementTo","relatedIdentifier":"10.1590/1980-5373-mr-2017-0815","relatedIdentifierType":"DOI"}],"relatedItems":[],"sizes":["3181525 Bytes"],"formats":[],"version":null,"rightsList":[{"rights":"Creative Commons Attribution 4.0 International","rightsUri":"https://creativecommons.org/licenses/by/4.0/legalcode","schemeUri":"https://spdx.org/licenses/","rightsIdentifier":"cc-by-4.0","rightsIdentifierScheme":"SPDX"}],"descriptions":[{"description":"In this study, a multi-parameter design of experiments, using Taguchi method, has been conducted in order to investigate the optimum curing conditions for glass fabric/epoxy laminated composites, followed by a statistical analysis and genetic algorithm optimization. Heating rate a, temperature T1 and duration h1 were treated as independent variables in a L25 Taguchi orthogonal array addressing five levels each. Tensile load and flexural strength were examined as pre-selected quality objectives. The results of the analysis of variance performed showed that the significant parameters for both tensile and flexural strength were temperature and duration, at a 95% confidence level. The estimation of the curing parameters for optimum tensile and flexural performance was achieved with an error considerably lower than 1%. The Poisson regression analysis was introduced to achieve a highly accurate regression model, with R2 greater than 97% for both optimization criteria. Finally, these two regression models were converted into a two-fold function for maximizing both criteria, and used as fitness function for a multi-objective optimization genetic 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