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A Method for Inspiring Radical Innovative Design Based on Cross-Domain Knowledge Mining

Authors :
Fei Yu
Xiuchuan Jia
Xiaowei Zhao
Jing Li
Source :
Systems, Vol 12, Iss 3, p 102 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

The reasonable application of cross-domain knowledge tends to promote the generation of radical innovation. However, it is difficult to accurately capture the cross-domain knowledge needed for radical innovation. To solve this problem, this paper proposes a method for inspiring radical innovative design based on FOS and technological distance measurement. First, the functional analysis of the problem product is carried out to determine the target function. Second, the patent sets of problem domain and target domains are constructed based on FOS. Then, this study optimizes the method of technological distance measurement and uses it to determine the optimal target domain. After further categorizing and screening the patents contained in the optimal target domain, specific cross-domain knowledge is pushed to designers. This method can help firms select the most appropriate cross-domain knowledge to design solutions for different problems, thus increasing the possibility of generating radical innovation. In the end, the method is validated in the design of a stovetop cleaning device.

Details

Language :
English
ISSN :
20798954
Volume :
12
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Systems
Publication Type :
Academic Journal
Accession number :
edsdoj.90177dd6a2874a89825b7eb34b6fe219
Document Type :
article
Full Text :
https://doi.org/10.3390/systems12030102