Knowledge is subject to constant change and expansion as the central raw material of technical progress. However, preservation in textbooks, industry standards, and algorithms limits the potential for actual revision. Machine learning methods now pen up new ways for knowledge acquisition and dissemination. Ongoing recording of tasks and associated job results provides data for the creation of AI models. When knowledge is provided continuously by professional communities or dedicated departments of companies, information not only reflects current data flow but also hints at the dynamics of the business. The aim of the considerations presented is to show how knowledge is embedded into dynamic procedures and processes by Artificial Intelligence. Constantly updated AI models replace the former implicit and scattered knowledge and can be distributed online. Assisting employees with their qualifications and automating complete working environments, AI-refined knowledge will accelerate engineering sales and design considerably.
AI-Based Knowledge Processing and Dissemination in Engineering Design
Proceedings in Automotive Engineering
International Congress of Automotive and Transport Engineering ; 2024 ; Brasov, Romania November 06, 2024 - November 08, 2024
CONAT 2024 International Congress of Automotive and Transport Engineering ; Kapitel : 28 ; 325-336
20.11.2024
12 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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