文献类型：期刊文献

英文题名：Expert decision support system for biologically inspired product design integrating emotional preferences and image generation

作者：Yang, Chaoxiang[1];Huang, Xiaoying[1];Zhang, Yimin[2];Huang, Zhengyang[2];Liu, Fei[1];Wan, Yongjing[2]

机构：[1]East China Univ Sci & Technol, Sch Art Design & Media, 130 Meilong Rd, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Sch Informat Sci & Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China

年份：2025

卷号：66

外文期刊名：ADVANCED ENGINEERING INFORMATICS

收录：;EI(收录号：20252018446129);WOS:【SCI-EXPANDED(收录号:WOS:001496542500001)】；

基金：The authors would like to thank all of the anonymous referees for the comments and suggestions, which have helped to improve the paper. In addition, the authors wish to thank the Shanghai Pujiang Program and the Chinese Universities Scientific Fund, for financially supporting under Contract No. 2020PJC025 and No. JKZ01212202.

语种：英文

外文关键词：Expert decision support; Biologically inspired design; Image generation; Emotional preference; Electric kettle

摘要：Influenced by the experience economy, customers put more emotional expression and spiritual needs on products. Bionic design can create products that align more with users' psychological preferences by imitating and learning from the forms of natural creatures. However, the success of bionic design is not easy, because it mainly depends on the designer's experience and knowledge. On the one hand, users and designers have different preferences for bionic creatures. On the other hand, designers face the problems of stereotyped thinking and lack of inspiration. This can easily lead to poor decision-making, resulting in the designs that do not meet the user's preferences. Therefore, this paper proposed an expert decision support system for product bionic design that integrates emotional preferences and image generation to support designers in the Biologically Inspired Design (BID) process. This paper took the electric kettle as a case study. First, the biological features are matched with the product semantics to propose the bionic conversion factor. Users' emotional preferences are analyzed to build a correlation model with the bionic conversion factors, thereby calculating product preference data. Second, the raw biometric data is calculated based on the bionic conversion factors. An intuitive fuzzy number emotional scale is used to measure users' preferences for these bionic features. A linear function model is constructed between user preferences and the bionic conversion factors to calculate biological preference data. By fitting the product preference data, bionic creatures that align with user preferences are selected. Finally, eye-tracking experiments are conducted to identify the critical biological features. StyleGAN is then applied to integrate these features with product images, resulting in a conceptual solution that serves as a reference for designers. Based on the analysis of users concerned emotional needs, the designer optimizes the details of the concept design to create the final product scheme. User evaluation of the design outputs shows that the electric kettle designed by the proposed system has the highest score and meets the user's expectations, which verifies the effectiveness and scientificity.