Towards a Complete Automation Feature Recognition System for Sheet Metal Manufacturing

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annif.suggestionsautomation|metal plates|technology|recognition|thin sheet metal|tooling|production|manufacturing|machine shop engineering|neural networks (information technology)|enen
annif.suggestions.linkshttp://www.yso.fi/onto/yso/p11477|http://www.yso.fi/onto/yso/p2080|http://www.yso.fi/onto/yso/p2339|http://www.yso.fi/onto/yso/p8265|http://www.yso.fi/onto/yso/p2079|http://www.yso.fi/onto/yso/p1542|http://www.yso.fi/onto/yso/p944|http://www.yso.fi/onto/yso/p8606|http://www.yso.fi/onto/yso/p8081|http://www.yso.fi/onto/yso/p7292en
dc.contributor.authorEltahawy, Bahaa
dc.contributor.authorYlihärsilä, Mikko
dc.contributor.authorVirrankoski, Reino
dc.contributor.authorPetäjä, Esko
dc.contributor.departmentfi=Ei tutkimusalustaa|en=No platform|-
dc.contributor.facultyfi=Tekniikan ja innovaatiojohtamisen yksikkö|en=School of Technology and Innovations|-
dc.contributor.orcidhttps://orcid.org/0000-0001-6372-7547-
dc.contributor.organizationfi=Vaasan yliopisto|en=University of Vaasa|
dc.date.accessioned2022-06-28T12:37:55Z
dc.date.accessioned2025-06-25T13:45:58Z
dc.date.available2022-06-28T12:37:55Z
dc.date.issued2017
dc.description.abstractSheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.-
dc.description.notification© 2017 World Academy of Science, Engineering and Technology.-
dc.description.reviewstatusfi=vertaisarvioimaton|en=nonPeerReviewed|-
dc.format.bitstreamtrue
dc.format.contentfi=kokoteksti|en=fulltext|-
dc.format.extent10-
dc.format.pagerange815-824-
dc.identifier.olddbid16669
dc.identifier.oldhandle10024/14430
dc.identifier.urihttps://osuva.uwasa.fi/handle/11111/2704
dc.identifier.urnURN:NBN:fi-fe2022062850246-
dc.language.isoeng-
dc.publisherWorld Academy of Science, Engineering and Technology-
dc.relation.conferenceWorld Academy of Science, Engineering and Technology-
dc.relation.doi10.5281/zenodo.1130217-
dc.relation.ispartofjournalInternational Journal of Mechanical and Mechatronics Engineering-
dc.relation.issn2010-3778-
dc.relation.issue4-
dc.relation.urlhttps://doi.org/10.5281/zenodo.1130217-
dc.relation.volume11-
dc.source.identifierhttps://osuva.uwasa.fi/handle/10024/14430
dc.subjectFeature recognition-
dc.subjectsheet metal manufacturing-
dc.subjectCAM-
dc.subjectCAD-
dc.subject.disciplinefi=Tietotekniikka|en=Computer Science|-
dc.subject.ysoautomation-
dc.titleTowards a Complete Automation Feature Recognition System for Sheet Metal Manufacturing-
dc.type.okmfi=B3 Vertaisarvioimaton artikkeli konferenssijulkaisussa|en=B3 Non-refereed article in conference proceeding|sv=B3 Icke-referentgranskad artikel i konferenspublikation|-
dc.type.publicationarticle-
dc.type.versionpublishedVersion-

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