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Generating TRIZ-inspired guidelines for eco-design using Generative Artificial Intelligence
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AI
DOI：10.1016/j.aei.2024.102846.png)
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Abstract
En 中文
Environmental considerations are emerging as stimuli for innovation during the eco-design ideation process. Integrating TRIZ (Teoriya Resheniya Izobretatelskikh Zadatch & horbar;Theory of Inventive Problem Solving) methodology into eco-design offers a structured problem-solving approach to address sustainability challenges. However, developing innovative designs requires expertise in TRIZ concepts and access to resources, which makes it a time-consuming process and can limit its application for eco-design innovation quickly. This study leverages the analytical and generative capabilities of large language models (LLMs) to enhance the TRIZ methodology and automate the ideation process in eco-design. An intelligent tool, Eco-innovate Assistant, is designed to provide users with eco-innovative solutions with design sketches. Its effectiveness is validated and evaluated through comparative studies. The findings demonstrate the potential of LLMs in automating design processes, catalyzing a transformation in AI-driven innovation and ideation in eco-design.
Keywords:
Eco-design
TRIZ
Large Language Models
Generative AI
Journal
IF:
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4.0K
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1.7W