{"id":2134,"date":"2026-10-09T11:13:13","date_gmt":"2026-10-09T09:13:13","guid":{"rendered":"https:\/\/hightech.de\/?p=2134"},"modified":"2026-10-09T11:14:22","modified_gmt":"2026-10-09T09:14:22","slug":"fit-for-ai-technische-daten-bestimmen-den-ki-erfolg","status":"publish","type":"post","link":"https:\/\/hightech.de\/en\/fit-for-ai-technische-daten-bestimmen-den-ki-erfolg\/","title":{"rendered":"Fit for AI: Technische Daten bestimmen den KI-Erfolg"},"content":{"rendered":"<p class=\"wp-block-paragraph\"><strong>Vier von f\u00fcnf Unternehmen im Maschinenbau nutzen bereits K\u00fcnstliche Intelligenz (KI) oder planen den Einsatz. Doch erst sieben Prozent haben GenAI unternehmensweit systematisch ausgerollt. Der entscheidende Engpass liegt in der Datenbasis. Das neue Whitepaper \u201eFit for AI?\u201c von simus systems zeigt, wie Maschinenbauer CAD- und technische Stammdaten f\u00fcr KI-Anwendungen aufbereiten k\u00f6nnen.<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Wer \u00c4hnlichkeitssuche, automatisierte Kalkulation, Assistenzsysteme, Qualit\u00e4ts\u00fcberwachung oder Predictive Maintenance mit KI befeuern will, braucht die richtige Datenbasis. In gewachsenen CAD-, PDM-, PLM- und ERP-Landschaften sind dagegen meist heterogene Formate, Bezeichnungen und Strukturen abgelegt. In einer KPMG-Studie berichten 56 Prozent der Hersteller von datenbezogenen Schwierigkeiten bei der Implementierung von KI. Menschen k\u00f6nnen viele Zusammenh\u00e4nge aus ihrer Erfahrung heraus interpretieren \u2013 f\u00fcr KI schaffen fehlende Merkmale, Dubletten und uneinheitliche Strukturen Probleme.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>KI-taugliche Datenbasis schaffen<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Wie man diese verhindern kann, zeigt simus systems in dem Whitepaper Fit for AI: Anhand eines klar definierten KI-Anwendungsfalles sollte man zun\u00e4chst pr\u00fcfen, welche Daten ben\u00f6tigt werden. Eine repr\u00e4sentative Stichprobe l\u00e4sst fr\u00fch erkennen, welche Datenquellen geeignet sind, wo Qualit\u00e4tsl\u00fccken bestehen und welche Aufbereitung den gr\u00f6\u00dften Nutzen verspricht. So wird Datenoptimierung vom abstrakten Gro\u00dfprojekt zu einem \u00fcberschaubaren Schritt mit konkretem Ziel.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>CAD- und Stammdaten automatisch aufbereiten<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Mit manueller Bereinigung funktioniert das nicht. Deshalb hat simus systems die Software-Suite simus classmate entwickelt. Sie analysiert, strukturiert, erg\u00e4nzt und klassifiziert gro\u00dfe Datenbest\u00e4nde anhand nachvollziehbarer, unternehmensspezifischer Regeln. Uneinheitliche Schreibweisen, Dubletten, fehlende Beschreibungen und unterschiedliche Merkmale werden erkannt und in eine konsistente Zielstruktur \u00fcberf\u00fchrt.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Dies gilt auch f\u00fcr CAD-Daten: 3D-Modelle und Geometrieinformationen lassen sich automatisch auswerten und klassifizieren; generative KI unterst\u00fctzt zus\u00e4tzlich bei der Digitalisierung technischer Zeichnungen. Auf diese Weise verbindet simus classmate Informationen aus CAD-, PDM- und ERP-Systemen. Aus verteilten Datenbest\u00e4nden entsteht eine gemeinsame Informationsbasis f\u00fcr KI-Anwendungen, Suche, Wiederverwendung, Kostenkalkulation und weitere digitale Prozesse.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Das wirtschaftliche Potenzial ist hoch: Laut VDMA und Strategy&amp; kann GenAI im Maschinen- und Anlagenbau ein zus\u00e4tzliches Profitabilit\u00e4tspotenzial von bis zu 10,7 Prozentpunkten erschlie\u00dfen. \u201eMit einer belastbaren Datenbasis k\u00f6nnen Fertigungsunternehmen dieses Potenzial dauerhaft f\u00fcr sich gewinnen\u201c, sagt Dr.-Ing. Arno Michelis, Gesch\u00e4ftsf\u00fchrer von simus systems. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Zum Whitepaper geht es hier<\/strong> (Dateneingabe erforderlich): <a href=\"https:\/\/www.simus-systems.com\/whitepaper-fit-for-ai-ki-erfolg-maschinenbau\/\">https:\/\/www.simus-systems.com\/whitepaper-fit-for-ai-ki-erfolg-maschinenbau\/<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Bildunterschrift:<\/strong> <strong><\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Fit for AI: Das Whitepaper von simus systems zeigt, wie technische Daten zur Grundlage f\u00fcr KI-Anwendungen werden<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Bildrechte: simus systems GmbH, frei zur Ver\u00f6ffentlichung mit Nachweis<\/p>","protected":false},"excerpt":{"rendered":"<p>Fit for AI: Das Whitepaper von simus systems zeigt, wie technische Daten zur Grundlage f\u00fcr KI-Anwendungen werden<\/p>","protected":false},"author":2,"featured_media":2136,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[14],"tags":[],"class_list":["post-2134","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-maschinen-anlagenbau"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.6 - 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