{"id":9958,"date":"2022-03-25T12:37:01","date_gmt":"2022-03-25T11:37:01","guid":{"rendered":"https:\/\/www.dimacsrl.com\/home\/?p=9958"},"modified":"2024-05-15T17:34:28","modified_gmt":"2024-05-15T15:34:28","slug":"how-to-improve-quality-control-uning-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.dimacsrl.com\/de\/archives\/how-to-improve-quality-control-uning-artificial-intelligence\/","title":{"rendered":"Wie man die Qualit\u00e4tskontrolle mit k\u00fcnstlicher Intelligenz verbessert"},"content":{"rendered":"
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Aus Fehlern lernen, um die Qualit\u00e4tskontrolle zu verbessern<\/span><\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Wie bei jedem gr\u00f6\u00dferen oder komplexen Fertigungsprojekt ist es technisch nicht m\u00f6glich, Null-Fehler zu erreichen - aber dennoch w\u00fcnschenswert. Deshalb setzt Dimac k\u00fcnstliche Intelligenz ein, um aus Fehlern zu lernen und die Qualit\u00e4tskontrolle zu verbessern, und stattet seine Pr\u00fcf- und Sortiermaschinen der neuesten Generation mit dieser Technologie aus.<\/i><\/b><\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Die Abmessungen und die Materialstruktur k\u00f6nnen mit modernster Pr\u00fcf- und Sortiermaschinentechnik 100% kontrolliert werden, aber es gibt immer noch M\u00e4ngel der Aspekte<\/b> die oft eine visuelle Endkontrolle erfordern, die nur das menschliche Auge durch manuelles Sortieren gew\u00e4hrleisten kann.<\/span><\/p>

Dimac hat daher Folgendes eingef\u00fchrt neu\u00a0<\/b><\/span>K\u00fcnstliche Intelligenz<\/b><\/a>\u00a0(AI) Algorithmen<\/b> zur Verarbeitung der Bilder von digitalen Fl\u00e4chenkameras und zur Unterst\u00fctzung des Bedieners beim Teach-in-Prozess. Defekte Teile werden unter den Fl\u00e4chenkameras positioniert, das System nimmt dann die Bilder auf und der Bediener markiert den Fehler im Bild auf dem Touchscreen mit den verf\u00fcgbaren Werkzeugen.<\/span><\/p>

Fehler wie Risse, Flecken, Verformungen, Andeutungen, Dellen und Materialm\u00e4ngel, die die Abmessungen des Teils nicht beeintr\u00e4chtigen, werden vom Bediener hervorgehoben und in das System eingelernt.<\/b> Nach dem vorl\u00e4ufigen Schnelllernprozess wird das System in der Lage sein, \u00e4hnliche Fehler in der Charge zu erkennen, und die Maschine wird in der Lage sein, die Teile zu sortieren. Die KI-Algorithmen erfordern die Verf\u00fcgbarkeit einer Galerie von NOK-Mustern, um eine Bibliothek von Bildern visueller Fehler zu erstellen, die als Referenz f\u00fcr das Training des Systems dient.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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Die Vorteile der k\u00fcnstlichen Intelligenz beschr\u00e4nken sich nicht auf die Inspektion<\/span><\/h3>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Die Algorithmen k\u00f6nnen mit dem ERP-System eines Unternehmens interagieren.<\/b> eine gro\u00dfe Menge an Daten \u00fcber den Sortierzyklus jeder Charge von Verbindungselementen auszutauschen - gemessene Merkmale, attributierte Fehler und Verfolgungsstatistiken \u00fcber die Fehlerverteilung in der Charge.<\/span><\/p>

KI-Funktionen sind in der letzten Generation der f\u00fcr die Marke optimierten Dimac mcvx Vision Inspection Software enthalten neue hochgeschwindigkeits-inspektions- und sortiermaschine mcv6<\/b>, basierend auf einem Glasdrehtisch. Die mcv6 stellt f\u00fcr Dimac einen weiteren wichtigen Schritt nach vorn dar\u00a0<\/span>der Weg zum Null-Fehler-Ziel, denn es ist ein <\/span>Native AI-Maschine<\/b><\/span>, Generation von Intel mit 2660 Mhz DDR4 mit GigE-Anschl\u00fcssen f\u00fcr hochaufl\u00f6sende Digitalkameras und ultimativen USB-Anschl\u00fcssen f\u00fcr externe Ger\u00e4te.<\/span><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

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\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tMEHR \u00dcBER MCV6<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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Learning from defects to improve quality control Like any sizable or complex manufacturing project attaining zero defects is technically not possible \u2013 but still desirable. That\u2019s why Dimac is using Artificial Intelligence to learn from defects and improve quality control, as well as adding the technology to its latest generation inspection and sorting machines. Dimensional […]<\/p>\n","protected":false},"author":1,"featured_media":13459,"comment_status":"closed","ping_status":"open","sticky":false,"template":"elementor_theme","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"footnotes":"","_members_access_role":[],"_members_access_error":""},"categories":[13],"tags":[8,20,21,22,6,23,24,9,25,26,27,28,29,30],"class_list":["post-9958","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-ai-tools","tag-controllo-ottico","tag-controllo-predittivo","tag-fasteners","tag-glass-table","tag-industria-4-0","tag-inspection","tag-mcv6","tag-measure-it","tag-misura","tag-raccolta-dati","tag-selezione","tag-sorting-it","tag-zero-defects"],"yoast_head":"\nHow to improve quality control using Artificial Intelligence - Dimac - Automatic Quality Control Systems<\/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:\/\/www.dimacsrl.com\/de\/archives\/how-to-improve-quality-control-uning-artificial-intelligence\/\" \/>\n<meta property=\"og:locale\" content=\"de_DE\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How to improve quality control using Artificial Intelligence - Dimac - Automatic Quality Control Systems\" \/>\n<meta property=\"og:description\" content=\"Learning from defects to improve quality control Like any sizable or complex manufacturing project attaining zero defects is technically not possible \u2013 but still desirable. 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