{"id":89300,"date":"2025-02-25T14:04:06","date_gmt":"2025-02-25T06:04:06","guid":{"rendered":"https:\/\/solomon-3d.mesvr.tw\/?p=89300"},"modified":"2025-02-25T14:05:56","modified_gmt":"2025-02-25T06:05:56","slug":"detection-des-defauts-de-chaussettes-utilisant-lia","status":"publish","type":"post","link":"https:\/\/solomon-3d.mesvr.tw\/fr\/etudes-de-cas\/detection-des-defauts-de-chaussettes-utilisant-lia\/","title":{"rendered":"D\u00e9tection des d\u00e9fauts de chaussettes utilisant l’IA"},"content":{"rendered":"
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SolVision\u00c9tude de cas<\/strong><\/span><\/h2>\n\n\n\n
Textiles et chaussures<\/a><\/div>\n<\/div><\/div>\n\n\n\n
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D\u00e9tection des d\u00e9fauts de chaussettes utilisant l’IA<\/h1><\/div><\/div>\n\n\n\n
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Client<\/h2>\n\n\n\n

Le client est un fabricant de chaussettes de premier plan cherchant \u00e0 am\u00e9liorer le contr\u00f4le qualit\u00e9 et l’efficacit\u00e9 op\u00e9rationnelle gr\u00e2ce \u00e0 l’inspection visuelle aliment\u00e9e par l’IA.<\/p>\n\n\n\n

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Cas<\/h2>\n\n\n\n
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Inspection Visuelle des Chaussettes avec IA<\/h3>\n\n\n\n

Le processus de fabrication des chaussettes se compose de plusieurs \u00e9tapes cl\u00e9s : conception, tricotage, couture, mise en forme, inspection et emballage. Dans cette industrie laborieuse, le contr\u00f4le qualit\u00e9 est souvent effectu\u00e9 manuellement \u00e0 divers points de contr\u00f4le. Malheureusement, la d\u00e9pendance \u00e0 des inspecteurs humains peut entra\u00eener de faibles taux de d\u00e9tection des d\u00e9fauts des chaussettes, la fatigue visuelle affectant couramment les travailleurs. Cette inefficacit\u00e9 ralentit non seulement la production, mais augmente \u00e9galement le risque de compromettre la qualit\u00e9 du produit.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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\"screenshot<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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D\u00e9fi<\/h2>\n\n\n\n
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Limitations des M\u00e9thodes d’Inspection Traditionnelles<\/h3>\n\n\n\n

Les chaussettes sont susceptibles de pr\u00e9senter divers d\u00e9fauts, notamment des d\u00e9fauts de couture, des trous et des d\u00e9chirures, qui peuvent varier en taille et en emplacement. Bien que les syst\u00e8mes de vision bas\u00e9s sur des r\u00e8gles traditionnels puissent inspecter l’ensemble des pi\u00e8ces de tissu, ils ont souvent du mal \u00e0 d\u00e9tecter les d\u00e9fauts irr\u00e9guliers des chaussettes. Cette limitation dans la d\u00e9tection des d\u00e9fauts n\u00e9cessite g\u00e9n\u00e9ralement des v\u00e9rifications manuelles suppl\u00e9mentaires, r\u00e9duisant encore l’efficacit\u00e9 et augmentant le risque de d\u00e9tections manqu\u00e9es. Pour relever ces d\u00e9fis, il existe un besoin urgent de solutions de d\u00e9tection de d\u00e9fauts avanc\u00e9es aliment\u00e9es par l’IA qui peuvent am\u00e9liorer la pr\u00e9cision et rationaliser le processus d’inspection.<\/p>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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Solution<\/h2>\n\n\n\n
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D\u00e9tection des D\u00e9fauts en Temps R\u00e9el avec SolVision<\/h3>\n\n\n\n

SolVision<\/a>, le syst\u00e8me de d\u00e9tection de d\u00e9fauts aliment\u00e9 par l’IA de Solomon, est form\u00e9 \u00e0 l’aide d’un petit ensemble d’images \u00e9chantillons pour identifier les chaussettes d\u00e9fectueuses en temps r\u00e9el. Le syst\u00e8me excelle \u00e0 reconna\u00eetre rapidement et avec pr\u00e9cision divers d\u00e9fauts de chaussettes, les classifiant pour garantir que les produits d\u00e9fectueux ne passent pas sur la ligne de production. En analysant les d\u00e9fauts en temps r\u00e9el, SolVision aide \u00e0 prot\u00e9ger la qualit\u00e9 des produits tout en am\u00e9liorant consid\u00e9rablement l’efficacit\u00e9 de la production.<\/p>\n\n\n\n

<\/div>\n\n\n\n
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D\u00e9tection et Classification des D\u00e9fauts des Chaussettes<\/h4>\n\n\n\n
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\"Needle<\/figure>\n<\/div>\n\n\n

Marque d’Aiguille<\/strong><\/p>\n<\/div>\n\n\n\n

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\"Seam<\/figure>\n<\/div>\n\n\n

Pliage de Couture<\/strong><\/p>\n<\/div>\n\n\n\n

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\"Needle<\/figure>\n<\/div>\n\n\n

Marque d’Aiguille<\/strong><\/p>\n<\/div>\n\n\n\n

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\"Broken<\/figure>\n<\/div>\n\n\n

Aiguille Cass\u00e9e<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n

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R\u00e9sultat<\/h2>\n\n\n\n
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<\/path><\/svg>Am\u00e9lioration du contr\u00f4le qualit\u00e9<\/span><\/div>
<\/path><\/svg>R\u00e9duction des erreurs humaines<\/span><\/div>
<\/path><\/svg>Augmentation de l’efficacit\u00e9 de la production<\/span><\/div><\/div>\n<\/div>\n<\/div>\n <\/div><\/div>\n\n\n\n
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<\/div>\n<\/div>\n <\/div><\/div>","protected":false},"excerpt":{"rendered":"

L’IA SolVision de Solomon identifie rapidement les d\u00e9fauts des chaussettes gr\u00e2ce \u00e0 une d\u00e9tection des d\u00e9fauts en temps r\u00e9el, am\u00e9liorant ainsi le contr\u00f4le qualit\u00e9 et l’efficacit\u00e9 des fabricants de textile.<\/p>","protected":false},"author":875,"featured_media":79922,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_gspb_post_css":"#gspb_heading-id-gsbp-5f6009ef-2b72{font-size:60px;line-height:100px;text-align:center!important;color:var(--gs-colorone);margin-top:50px}#gspb_heading-id-gsbp-5f6009ef-2b72 .gsap-g-line{text-align:center!important}#gspb_heading-id-gsbp-5f6009ef-2b72 .gspb_heading_subtitle,#gspb_subheading-id-gsbp-5f6009ef-2b72{display:block;line-height:22px;margin-top:5px;font-size:30px;color:var(--wp--preset--color--white, 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