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Research on new creative conceptual design system using adapted case-based reasoning technique

  • Jie Hu (a1), Jin Ma (a1), Jin-Feng Feng (a1) and Ying-Hong Peng (a1)

Abstract

Creative conceptual design requires significant previous design knowledge. Case-based reasoning enables learning from previous design experience and has a great potential in supporting creative conceptual design by means of seeking to retrieve, reuse, and revise most appropriate cases to generate inspired solutions. However, traditional case-based reasoning based creative conceptual design models focus on design strategies research, pay little attention to defining a consistent knowledge representation model, and neglect the research to make various types of knowledge retrieval tractable. Faced with such drawbacks, the expected design knowledge cannot be retrieved properly, especially in cases where multidisciplinary knowledge is concerned or exact query terms are absent. In order to solve these issues, this paper presents a combined approach to support creative conceptual design process. First, function–behavior–structure knowledge cell is introduced as a unified consistent design knowledge representation model. Second, a hybrid similarity measure is proposed to increase the overall possibility of obtaining useful design knowledge by considering semantic understanding ability. Third, an intelligent creative conceptual design system has been developed with a case study of a novel insulin pump design to demonstrate its usage, and two experiments are conducted to evaluate the performance of the proposed approach. The results show that the proposed approach outperforms other case-based reasoning based creative conceptual design models.

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Copyright

Corresponding author

Reprint requests to: Jie Hu, Institute of Knowledge Based Engineering, School of Mechanical Engineering, Shanghai Jiao Tong University, Dongchuan Rd.800, Minhang District, Shanghai 200240, China. E-mail: hujie@sjtu.edu.cn

References

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Research on new creative conceptual design system using adapted case-based reasoning technique

  • Jie Hu (a1), Jin Ma (a1), Jin-Feng Feng (a1) and Ying-Hong Peng (a1)

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