Otomotiv Üretim Hatlarindaki 3D Parçalarin Kalite Kontrolü Için Endüstri 4.0 Ile Uyumlu Yapay Görme Sisteminin Geliştirilmesi

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dc.contributor.authorBayrak, Gökay
dc.contributor.authorCakiroglu, Abdullah
dc.contributor.authorYilmaz, Imren Ozturk
dc.contributor.authorBilici, Abdullah Yasin
dc.contributor.authorCandemir, Yasin Atalay
dc.date.accessioned2026-02-12T21:02:49Z
dc.date.available2026-02-12T21:02:49Z
dc.date.issued2022
dc.departmentBursa Teknik Üniversitesi
dc.description6th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2022 -- 2022-10-20 through 2022-10-22 -- Ankara -- 184355
dc.description.abstractImage processing technology is a technology that is increasingly used in almost all sectors and continues to develop today. When its usage areas are examined, it is frequently used in mold design and manufacturing, metal part production, and quality control applications after sheet metal forming. The most important advantages of image processing technology are that it reduces human labor, has a low error rate, and accelerates the processing time in the area where it is used. In this study, a machine vision system compatible with Industry 4.0 has been developed for the quality control of 3D parts in automotive production lines. An image processing-based quality control system, which is compatible with Industry 4.0, is designed with a high control sensitivity compared to existing methods, low processing time, and error detection of post-production parts, various metric measurements. The designed system consists of two main parts, the control software, and the image acquisition cabinet. First, the raw image taken in the image acquisition cabinet with appropriate lighting was transferred to the image processing software and then all the measurement results were obtained. Image processing software was performed with LabVIEW Vision Builder AI (Automated Inspection) program. A suitable software infrastructure was created for the parts by performing pixel-based measurements and morphological operations on the image. When the results obtained are examined, it is seen that error detection and measurement processes can be performed with an error rate of less than 0.04%. © 2022 IEEE.
dc.identifier.doi10.1109/ISMSIT56059.2022.9932814
dc.identifier.endpage628
dc.identifier.isbn9781665470131
dc.identifier.scopus2-s2.0-85142826012
dc.identifier.scopusqualityN/A
dc.identifier.startpage624
dc.identifier.urihttps://doi.org/10.1109/ISMSIT56059.2022.9932814
dc.identifier.urihttps://hdl.handle.net/20.500.12885/6554
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartofISMSIT 2022 - 6th International Symposium on Multidisciplinary Studies and Innovative Technologies, Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.snmzKA_Scopus_20260212
dc.subjectAutomated fault detection
dc.subjectImage processing
dc.subjectIndustry 4.0
dc.subjectQuality control
dc.titleOtomotiv Üretim Hatlarindaki 3D Parçalarin Kalite Kontrolü Için Endüstri 4.0 Ile Uyumlu Yapay Görme Sisteminin Geliştirilmesi
dc.typeConference Object

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