{"id":7148,"date":"2022-03-03T12:28:17","date_gmt":"2022-03-03T12:28:17","guid":{"rendered":"https:\/\/iconpro.com?casestudies=commercial-vehicles-min-failures"},"modified":"2023-08-08T16:12:13","modified_gmt":"2023-08-08T16:12:13","slug":"commercial-vehicles-min-failures","status":"publish","type":"casestudies","link":"https:\/\/iconpro.com\/en\/casestudy\/commercial-vehicles-min-failures\/","title":{"rendered":"Commercial Vehicles \u2013 Min. Failures"},"content":{"rendered":"<p><strong>Project Subtitle<\/strong><br \/>\nKI-basiertes Fehlermanagement in Wertsch\u00f6pfungsketten<\/p>\n<p><strong>Companies &amp; Partners<\/strong><br \/>\nBernard KRONE Holding SE &amp; Co. KG, MAN Trucks, Fraunhofer IPT, Machine Tool Laboratory WZL, DATAbility GmbH, i2solutions GmbH<\/p>\n<p><strong>Problem<\/strong><br \/>\nThe commercial vehicle industry is an extremely challenging industry. With the ever-rising demands from industry and logistics customers, it is highly important to have defect-free manufacturing of commercial vehicles, optimal operation, and identify errors along the product life cycle as early as possible.<\/p>\n<p><strong>Solution<\/strong><br \/>\nAn AI-based failure management system is developed across the whole value chain of commercial vehicles from the raw material to the actual operation based on machine learning models. These models are trained also on production and quality data from the manufacturing processes of commercial vehicles.<br \/>\nThe resultant model is used for error management by predicting deviations from quality targets in production as well as necessary maintenance and foreseeable damages in operation of the vehicles. Further, to reduce the defects, optimal process parameter for the manufacturing process will be recommended based on the trained models.<\/p>\n<p><strong>Outcome<\/strong><br \/>\nA system for error management and minimal defect manufacturing of commercial vehicles.\u00a0Reduced production and operation costs, minimal failures, increased service life, higher customer satisfaction.<\/p>\n","protected":false},"featured_media":6869,"template":"","tags":[154,155],"case_studies_category":[],"class_list":["post-7148","casestudies","type-casestudies","status-publish","has-post-thumbnail","hentry","tag-case-study-en-2","tag-predictive-quality-en-2"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v25.9 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Commercial Vehicles \u2013 Min. Failures - IconPro<\/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:\/\/iconpro.com\/en\/casestudy\/commercial-vehicles-min-failures\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Commercial Vehicles \u2013 Min. Failures - IconPro\" \/>\n<meta property=\"og:description\" content=\"Project Subtitle KI-basiertes Fehlermanagement in Wertsch\u00f6pfungsketten Companies &amp; Partners Bernard KRONE Holding SE &amp; Co. KG, MAN Trucks, Fraunhofer IPT, Machine Tool Laboratory WZL, DATAbility GmbH, i2solutions GmbH Problem The commercial vehicle industry is an extremely challenging industry. 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