{"id":1685,"date":"2024-05-29T15:57:52","date_gmt":"2024-05-29T15:57:52","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=1685"},"modified":"2024-05-29T15:58:13","modified_gmt":"2024-05-29T15:58:13","slug":"vol22-no1-art2","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol22-no1\/vol22-no1-art2\/","title":{"rendered":"Real-Time Detection of Customer-Induced Damage in Printed Circuit Boards Using Mobile Devices and YOLO Detectors"},"content":{"rendered":"<p>Jo\u00e3o Pedro Santiago <a href=\"https:\/\/orcid.org\/0009-0005-2454-3397\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Victor Aguiar de Farias <a href=\"https:\/\/orcid.org\/0000-0001-6244-625X\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Lucas Sena <a href=\"https:\/\/orcid.org\/0009-0004-9318-6867\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>, Joao Paulo Pordeus <a href=\"https:\/\/orcid.org\/0000-0003-1686-595X\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a>&amp; Javam Machado <a href=\"https:\/\/orcid.org\/0000-0002-8430-9421\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-1167\" src=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2020\/09\/orcid.jpg\" alt=\"orcid\" width=\"20\" height=\"20\" \/><\/a><\/p>\n<p><strong>Abstract:<\/strong> The identification of Consumer-induced damage is essential for electronics manufacturers\u2019 warranty programs. Consumer Induced Damage (CID) is any damage caused by an unauthorized person, including the consumer. The product warranty does not cover these damages, avoiding expenses in the manufacturer\u2019s revenue. The consumer-induced damage warranty process is usually done manually by technically trained people. However, this task demands a lot of attention to detail, can be time-consuming, and is susceptible to human errors. With this in mind, this work presents an object detection model for low-computational-cost devices that uses computer vision and deep learning methods with YOLO detectors embedded in mobile devices to identify consumer-induced damages on printed circuit boards (PCB). We conducted sixteen experiments with four YOLO neural network architectures and successfully developed a mobile application for CID detection. Our best model achieved a mAP@0.5 of 33.1% and an average of 5.7 FPS on real mobile devices.<\/p>\n<p><strong>Keywords:<\/strong> Customer Induced Damage, Printed Circuit Board (PCB), Deep Learning, Computer Vision.<\/p>\n<p><strong>DOI code:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol22-no1-art2\">10.21528\/lnlm-vol22-no1-art2<\/a><\/p>\n<p><strong>PDF file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2024\/12\/vol22-no1-art2.pdf\">vol22-no1-art2.pdf<\/a><\/p>\n<p><strong>BibTex file:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/2024\/12\/vol22-no1-art2.bib\">vol22-no1-art2.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Jo\u00e3o Pedro Santiago , Victor Aguiar de Farias , Lucas Sena , Joao Paulo Pordeus &amp; Javam Machado Abstract: The identification of Consumer-induced damage is essential for electronics manufacturers\u2019 warranty programs. Consumer Induced Damage (CID) is any damage caused by <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol22-no1\/vol22-no1-art2\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1675,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-1685","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Real-Time Detection of Customer-Induced Damage in Printed Circuit Boards Using Mobile Devices and YOLO Detectors - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol22-no1\/vol22-no1-art2\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Real-Time Detection of Customer-Induced Damage in Printed Circuit Boards Using Mobile Devices and YOLO Detectors - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"Jo\u00e3o Pedro Santiago , Victor Aguiar de Farias , Lucas Sena , Joao Paulo Pordeus &amp; Javam Machado Abstract: The identification of Consumer-induced damage is essential for electronics manufacturers\u2019 warranty programs. 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