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2025 | OriginalPaper | Buchkapitel

AI-Aided Resource Mining Method for Idealization-Driven Product Innovation

verfasst von : Ranye Du, Jianguang Sun, Runze Miao, Delong Zhang

Erschienen in: World Conference of AI-Powered Innovation and Inventive Design

Verlag: Springer Nature Switzerland

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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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Vorheriges Kapitel Research on the Identification and Analysis of Technological Opportunities Utilizing the BERT Model and MULTIMOORA Approach
Nächstes Kapitel Use of AI in the TRIZ Innovation Process: A TESE-Based Forecast
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Metadaten
Titel
AI-Aided Resource Mining Method for Idealization-Driven Product Innovation
verfasst von
Ranye Du
Jianguang Sun
Runze Miao
Delong Zhang
Copyright-Jahr
2025
Buch
World Conference of AI-Powered Innovation and Inventive Design

Print ISBN: 978-3-031-75918-5

Electronic ISBN: 978-3-031-75919-2

Copyright-Jahr: 2025

DOI
https://doi.org/10.1007/978-3-031-75919-2_9

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