{"id":87517,"date":"2025-02-18T11:24:21","date_gmt":"2025-02-18T03:24:21","guid":{"rendered":"https:\/\/solomon-3d.mesvr.tw\/?p=87517"},"modified":"2025-02-26T09:43:52","modified_gmt":"2025-02-26T01:43:52","slug":"welding-bead-defect-detection-using-ar-ai","status":"publish","type":"post","link":"https:\/\/solomon-3d.mesvr.tw\/pt\/casos-de-sucesso\/welding-bead-defect-detection-using-ar-ai\/","title":{"rendered":"Detec\u00e7\u00e3o de defeitos no cord\u00e3o de soldagem usando AR + AI"},"content":{"rendered":"
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META-aiviCaso de Estudo<\/span><\/h2>\n\n\n\n
<\/span><\/a>Autom\u00f3vel<\/a><\/span> | Manufatura<\/a><\/div>\n<\/div><\/div>\n\n\n\n
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Detec\u00e7\u00e3o de defeitos no cord\u00e3o de soldagem usando AR + AI<\/h1><\/div><\/div>\n\n\n\n
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Cliente<\/h2>\n\n\n\n

O cliente \u00e9 um fabricante de autom\u00f3veis com sede na \u00c1sia.<\/p>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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Caso<\/h2>\n\n\n\n
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Desafios no exame da qualidade da soldagem<\/h3>\n\n\n\n

Os carros t\u00eam m\u00faltiplas superf\u00edcies e caracter\u00edsticas complexas, levando a varia\u00e7\u00f5es nos locais e t\u00e9cnicas de soldagem. O exame da qualidade da soldagem automotiva requer inspe\u00e7\u00e3o de v\u00e1rios \u00e2ngulos devido ao formato irregular do chassi do ve\u00edculo e dos pain\u00e9is da carroceria. Automatizar esse processo \u00e9 desafiador e caro, levando \u00e0 depend\u00eancia da inspe\u00e7\u00e3o manual. No entanto, se o pessoal for descuidado na sua inspe\u00e7\u00e3o, produtos defeituosos podem entrar no mercado, representando um risco para a seguran\u00e7a na condu\u00e7\u00e3o.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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\"close<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Desafio<\/h2>\n\n\n\n
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Limita\u00e7\u00f5es da inspe\u00e7\u00e3o manual para defeitos irregulares em soldagem automotiva<\/h3>\n\n\n\n

A inspe\u00e7\u00e3o manual da qualidade da soldagem automotiva pode fazer com que defeitos irregulares sejam ignorados. Apesar das t\u00e9cnicas avan\u00e7adas de soldagem, garantir uma soldagem perfeita continua sendo um desafio. As estruturas t\u00eam v\u00e1rios pontos de inspe\u00e7\u00e3o e recursos multifacetados, tornando a inspe\u00e7\u00e3o manual a confian\u00e7a atual, mas a qualidade inconsistente \u00e9 uma preocupa\u00e7\u00e3o.<\/p>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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Solu\u00e7\u00e3o<\/h2>\n\n\n\n
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Melhorando a precis\u00e3o da inspe\u00e7\u00e3o manual com META-aivi<\/h3>\n\n\n\n

Ao utilizar a fun\u00e7\u00e3o de detec\u00e7\u00e3o de defeitos do META-aivi<\/a>, os modelos de IA podem ser treinados e carregados no sistema para obter pontos de soldagem qualificados. Isso permite a inspe\u00e7\u00e3o de se\u00e7\u00f5es soldadas por IA usando \u00f3culos AR ou um tablet para reconhecer rapidamente soldas defeituosas. O feedback de realidade aumentada \u00e9 fornecido em tempo real, permitindo que o pessoal corrija erros por meio de instru\u00e7\u00f5es na tela, garantindo a qualidade da soldagem. O META-aivi tamb\u00e9m pode distinguir entre tipos de defeitos, como soldagem incompleta, furos de areia, carboniza\u00e7\u00e3o e respingos. Por exemplo, se defeitos em furos de areia forem detectados continuamente, isso sugere a necessidade de substituir os fios de soldagem, enquanto casos frequentes de soldagem incompleta podem exigir inspe\u00e7\u00e3o do bocal. Os dados acumulados podem ser usados \u200b\u200bpara fins subsequentes de an\u00e1lise e manuten\u00e7\u00e3o de big data. Al\u00e9m disso, hist\u00f3ricos de inspe\u00e7\u00e3o de produtos podem ser gerados, digitalizando efetivamente o processo de inspe\u00e7\u00e3o.<\/p>\n\n\n\n

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Resultados da inspe\u00e7\u00e3o META-aivi<\/strong><\/h4>\n\n\n\n
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\"an<\/div>\n\n\n\n
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Durante a inspe\u00e7\u00e3o AI, o META-aivi detecta quaisquer defeitos de soldagem<\/h5>\n<\/div>\n\n\n\n
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\"AI<\/div>\n\n\n\n
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Os resultados da inspe\u00e7\u00e3o de IA s\u00e3o exibidos em tempo real na tela do dispositivo AR<\/h5>\n<\/div>\n <\/div><\/div>\n<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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Resultado<\/h2>\n\n\n\n
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<\/path><\/svg>A tecnologia AI da META-aivi detectou defeitos de soldagem em tempo real, permitindo uma identifica\u00e7\u00e3o r\u00e1pida e precisa<\/span><\/div>
<\/path><\/svg>O META-aivi tamb\u00e9m foi capaz de identificar v\u00e1rios tipos de defeitos de soldagem e acumular dados para an\u00e1lise posterior<\/span><\/div>
<\/path><\/svg>META-aivi reduziu as taxas de erro e garantiu a qualidade dos produtos que passaram na inspe\u00e7\u00e3o<\/span><\/div><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>","protected":false},"excerpt":{"rendered":"

Os modelos de IA podem ser treinados e carregados no sistema para obter pontos de soldagem qualificados. Isso permite a inspe\u00e7\u00e3o de se\u00e7\u00f5es soldadas por IA usando \u00f3culos AR ou um tablet para reconhecer rapidamente soldas defeituosas.<\/p>","protected":false},"author":36,"featured_media":37887,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_gspb_post_css":"#gspb_heading-id-gsbp-98a71402-b1a0{font-size:60px;line-height:100px;text-align:center!important;color:var(--gs-colorone);margin-top:50px}#gspb_heading-id-gsbp-98a71402-b1a0 .gsap-g-line{text-align:center!important}#gspb_heading-id-gsbp-98a71402-b1a0 .gspb_heading_subtitle,#gspb_subheading-id-gsbp-98a71402-b1a0{display:block;line-height:22px;margin-top:5px;font-size:30px;color:var(--wp--preset--color--white, #ffffff)}.gspb_text-id-gsbp-c3844e90-556c{font-size:20px;text-align:center!important;font-weight:500!important}.gspb_text-id-gsbp-c3844e90-556c 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