Abstract
The availability of resources in design plays a crucial role in innovative design. The importance of available resources increases as the solution to the problem approaches the Ideal Final Result (IFR). This paper introduces a method for mining resources in the product innovation process by integrating the Theory of Inventive Problem Solving (TRIZ) and AI, and demonstrates TRIZ’s application in various fields.
Firstly, through AI tools to obtain research hotspots to formulate product design goals, through the training of ChatGPT, with the help of AI tools to achieve the mining of internal resources. Additionally, an AI algorithm is employed to analyze patents and identify external available resources. We evaluate the value of these mined resources using a Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) comprehensive evaluation model that combines analytic hierarchy process with entropy weight method to select optimal available resources. Multi-criteria evaluation methods and AI technology are applied to resource mining and selection for product innovation.
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Du, R., Sun, J., Miao, R., Zhang, D. (2025). AI-Aided Resource Mining Method for Idealization-Driven Product Innovation. In: Cavallucci, D., Brad, S., Livotov, P. (eds) World Conference of AI-Powered Innovation and Inventive Design. TFC 2024. IFIP Advances in Information and Communication Technology, vol 735. Springer, Cham. https://doi.org/10.1007/978-3-031-75919-2_9
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DOI: https://doi.org/10.1007/978-3-031-75919-2_9
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