Construction and application of data-driven knowledge adjacency network for product CMF design
To solve the problems of over-reliance on personal experience, lack of thinking about users' perceptual preferences, and neglect of the overall coupling characteristics of CMF design, the construction and application methods of product CMF design knowledge adjacency network are proposed bas...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
The Japan Society of Mechanical Engineers
2023-03-01
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| Series: | Journal of Advanced Mechanical Design, Systems, and Manufacturing |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/jamdsm/17/2/17_2023jamdsm0032/_pdf/-char/en |
| _version_ | 1797806352576282624 |
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| author | Chao LIU KieSu KIM |
| author_facet | Chao LIU KieSu KIM |
| author_sort | Chao LIU |
| collection | DOAJ |
| description | To solve the problems of over-reliance on personal experience, lack of thinking about users' perceptual preferences, and neglect of the overall coupling characteristics of CMF design, the construction and application methods of product CMF design knowledge adjacency network are proposed based on the multi-layer network, intuitionistic fuzzy set, and gray correlation method theory. Firstly, the construction of the product CMF design multilayer network is completed by extracting and selecting the design resources of product families with similar imagery. Secondly, considering the product CMF design characteristics, a multi-layer network association division method based on leader nodes is proposed, and the construction of the CMF design knowledge adjacency network is further completed. Thirdly, based on intuitionistic fuzzy set theory, user preferences are considered to further improve the science of evaluation data. Finally, the calculation of association coefficients is combined with the gray correlation method, and the optimal matching between the adjacency network and the product surface assignment solution space is completed to assist designers to improve the design efficiency. The proposed method is applied to the CMF design work of a smart tractor, and perceptual experiments are set up to evaluate the design results, and the results show that this design meets the target requirements, which proves the usefulness of the method to assist the designer's work. |
| first_indexed | 2024-03-13T06:06:03Z |
| format | Article |
| id | doaj.art-241387ae0cde487a9a0696f6eda49b9b |
| institution | Directory Open Access Journal |
| issn | 1881-3054 |
| language | English |
| last_indexed | 2024-03-13T06:06:03Z |
| publishDate | 2023-03-01 |
| publisher | The Japan Society of Mechanical Engineers |
| record_format | Article |
| series | Journal of Advanced Mechanical Design, Systems, and Manufacturing |
| spelling | doaj.art-241387ae0cde487a9a0696f6eda49b9b2023-06-12T04:03:50ZengThe Japan Society of Mechanical EngineersJournal of Advanced Mechanical Design, Systems, and Manufacturing1881-30542023-03-01172JAMDSM0032JAMDSM003210.1299/jamdsm.2023jamdsm0032jamdsmConstruction and application of data-driven knowledge adjacency network for product CMF designChao LIU0KieSu KIM1College of Design, Silla UniversityCollege of Design, Silla UniversityTo solve the problems of over-reliance on personal experience, lack of thinking about users' perceptual preferences, and neglect of the overall coupling characteristics of CMF design, the construction and application methods of product CMF design knowledge adjacency network are proposed based on the multi-layer network, intuitionistic fuzzy set, and gray correlation method theory. Firstly, the construction of the product CMF design multilayer network is completed by extracting and selecting the design resources of product families with similar imagery. Secondly, considering the product CMF design characteristics, a multi-layer network association division method based on leader nodes is proposed, and the construction of the CMF design knowledge adjacency network is further completed. Thirdly, based on intuitionistic fuzzy set theory, user preferences are considered to further improve the science of evaluation data. Finally, the calculation of association coefficients is combined with the gray correlation method, and the optimal matching between the adjacency network and the product surface assignment solution space is completed to assist designers to improve the design efficiency. The proposed method is applied to the CMF design work of a smart tractor, and perceptual experiments are set up to evaluate the design results, and the results show that this design meets the target requirements, which proves the usefulness of the method to assist the designer's work.https://www.jstage.jst.go.jp/article/jamdsm/17/2/17_2023jamdsm0032/_pdf/-char/enproduct designadjacency networkuser preferenceresource matchingproduct cmf |
| spellingShingle | Chao LIU KieSu KIM Construction and application of data-driven knowledge adjacency network for product CMF design Journal of Advanced Mechanical Design, Systems, and Manufacturing product design adjacency network user preference resource matching product cmf |
| title | Construction and application of data-driven knowledge adjacency network for product CMF design |
| title_full | Construction and application of data-driven knowledge adjacency network for product CMF design |
| title_fullStr | Construction and application of data-driven knowledge adjacency network for product CMF design |
| title_full_unstemmed | Construction and application of data-driven knowledge adjacency network for product CMF design |
| title_short | Construction and application of data-driven knowledge adjacency network for product CMF design |
| title_sort | construction and application of data driven knowledge adjacency network for product cmf design |
| topic | product design adjacency network user preference resource matching product cmf |
| url | https://www.jstage.jst.go.jp/article/jamdsm/17/2/17_2023jamdsm0032/_pdf/-char/en |
| work_keys_str_mv | AT chaoliu constructionandapplicationofdatadrivenknowledgeadjacencynetworkforproductcmfdesign AT kiesukim constructionandapplicationofdatadrivenknowledgeadjacencynetworkforproductcmfdesign |