Generative AI for Industrial Design Engineering

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SBFI

Projektnummer

25.00229

Projekttitel

Generative AI for Industrial Design Engineering

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Abstract (Englisch)	Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are profoundly disrupting business sectors worldwide by fundamentally altering existing processes presenting unique opportunities. In industrial engineering design, there is a significant and growing demand for experts proficient in AI and engineering disciplines to drive the digital transformation and enhance productivity and efficiency. Our doctoral training program GenAIDE: Generative AI for Industrial Design Engineering provides top-class training to 14 Doctoral Candidates, who will explore disruptive AI technologies and evolve computer-aided engineering from being mere support tools to becoming proactive AI partners within hybrid engineering teams. The DCs will investigate and develop emerging concepts, methods, and infrastructures to deliver an integrated vision of Human-AI collaboration in design engineering teams. GenAIDE seeks to address unmet needs in doctoral training at both European and international levels, leveraging the complementary expertise of 16 leading academic and non-academic partners. This program explores novel synergies between natural language-based Human-AI interaction, nature-inspired optimization and exploration, social impacts of Human-AI cooperation on the team dynamics and advanced machine learning in the engineering domain. GenAI substantially changes the way engineers interact with and benefit from AI and access domain-specific knowledge, marking a phase transition that not only enhances the productivity of engineering teams but also expands the complexity of solvable design problems. GenAIDE will attract and prepare the necessary researchers and practitioners for contributions to industry and academia across Europe. Our training programme will serve as a blueprint for new curricula in AI-assisted engineering, ensuring the integration of innovative AI methodologies into the educational framework and shaping the future of AI-augmented design engineering.

Kategorie

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Abstract
(Englisch)

Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are profoundly disrupting business sectors worldwide by fundamentally altering existing processes presenting unique opportunities. In industrial engineering design, there is a significant and growing demand for experts proficient in AI and engineering disciplines to drive the digital transformation and enhance productivity and efficiency. Our doctoral training program GenAIDE: Generative AI for Industrial Design Engineering provides top-class training to 14 Doctoral Candidates, who will explore disruptive AI technologies and evolve computer-aided engineering from being mere support tools to becoming proactive AI partners within hybrid engineering teams. The DCs will investigate and develop emerging concepts, methods, and infrastructures to deliver an integrated vision of Human-AI collaboration in design engineering teams. GenAIDE seeks to address unmet needs in doctoral training at both European and international levels, leveraging the complementary expertise of 16 leading academic and non-academic partners. This program explores novel synergies between natural language-based Human-AI interaction, nature-inspired optimization and exploration, social impacts of Human-AI cooperation on the team dynamics and advanced machine learning in the engineering domain. GenAI substantially changes the way engineers interact with and benefit from AI and access domain-specific knowledge, marking a phase transition that not only enhances the productivity of engineering teams but also expands the complexity of solvable design problems. GenAIDE will attract and prepare the necessary researchers and practitioners for contributions to industry and academia across Europe. Our training programme will serve as a blueprint for new curricula in AI-assisted engineering, ensuring the integration of innovative AI methodologies into the educational framework and shaping the future of AI-augmented design engineering.