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Optimization and influence of GMAW parameters for weld geometrical and mechanical properties using the Taguchi method and variance analysis

dc.contributor.authorCasarini, Arthur
dc.contributor.authorCoelho, João Paulo
dc.contributor.authorOlívio, Emillyn
dc.contributor.authorBraz-César, Manuel
dc.contributor.authorRibeiro, J.E.
dc.date.accessioned2020-07-31T13:51:39Z
dc.date.available2020-07-31T13:51:39Z
dc.date.issued2020
dc.description.abstractGas metal arc welding is one of the arc fusion processes that is widely used in industry due to its high efficiency. The correct selection of the input parameters has direct influence on the weld quality and, with the control of those parameters, it is possible to reduce the amount of weld material, improve its properties and then increase the productivity of the process. This study intends to take a group of weld parameters and submit them to the optimization by the Taguchi Method and check the influence of those through a Variance Analysis (ANOVA). An L9 orthogonal array gathered three parameters (weld voltage, weld speed and weld torch angle) into three levels, then, with all combinations set and performed, the macrography and the transversal tensile strength test provided, respectively, the geometrical and the mechanical properties. The signal-to-noise ratios enable the optimization and the ANOVA provided the influence of the input parameters on the response parameters. The weld speed appeared as the most influent parameter for the weld geometry, contributing 63.54% to reinforcement, 66.36% to width and 66.94% to penetration, and the weld torch angle the most influent to the ultimate transversal tensile strength (41.39%). The optimum levels to the reinforcement are 22.4 [V], 400 [mm/min] and 30 [°], to the width 22.4 [V], 300 [mm/min], 0 [°], to the penetration 23.3 [V], 400 [mm/min], 0 [°] and, lastly, to the ultimate transversal tensile strength 24.1 [V], 200 [mm/min], 15 [°]. The Taguchi method showed to be suitable for this kind of problem and giving an efficient experiment design and good results.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationCasarini, Arthur; Coelho, J.P.; Olívio, Emillyn; Braz-César, M.T.; Ribeiro, J.E. (2020). Optimization and influence of GMAW parameters for weld geometrical and mechanical properties using the Taguchi method and variance analysis. In ICEUBI2019 International Congress on Engineering — Engineering for Evolution. p.781-794pt_PT
dc.identifier.doi10.18502/keg.v5i6.7097pt_PT
dc.identifier.urihttp://hdl.handle.net/10198/22605
dc.language.isoengpt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectTaguchi methodpt_PT
dc.subjectOptimizationpt_PT
dc.subjectGMAWpt_PT
dc.titleOptimization and influence of GMAW parameters for weld geometrical and mechanical properties using the Taguchi method and variance analysispt_PT
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.endPage794pt_PT
oaire.citation.startPage781pt_PT
oaire.citation.titleICEUBI2019 International Congress on Engineering — Engineering for Evolutionpt_PT
person.familyNameCoelho
person.familyNameBraz-César
person.familyNameRibeiro
person.givenNameJoão Paulo
person.givenNameManuel
person.givenNameJ.E.
person.identifierR-001-EXZ
person.identifierR-000-6Y8
person.identifier.ciencia-idD61E-A586-7D4A
person.identifier.ciencia-id5C10-B764-22E3
person.identifier.ciencia-id0F15-FB62-29DB
person.identifier.orcid0000-0002-7616-1383
person.identifier.orcid0000-0001-5640-0714
person.identifier.orcid0000-0001-6300-148X
person.identifier.ridJ-6887-2013
person.identifier.ridG-3839-2018
person.identifier.scopus-author-id55137039300
person.identifier.scopus-author-id53663179600
person.identifier.scopus-author-id25638652400
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
relation.isAuthorOfPublication2861f33b-b49a-421d-9bfa-92b4304d2668
relation.isAuthorOfPublicationa99f08f6-5b97-4571-a6e4-07dee53fb527
relation.isAuthorOfPublicationc90169e6-7889-4270-a096-35b98c75f9f9
relation.isAuthorOfPublication.latestForDiscoveryc90169e6-7889-4270-a096-35b98c75f9f9

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