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图学学报

• 智能设计与数字化设计 • 上一篇    下一篇

多目标驱动的产品形态基因网络模型研究

  

  1. 1. 贵州大学现代制造技术教育部重点实验室，贵州 贵阳 550025； 
    2. 贵州民族大学美术学院，贵州 贵阳 550025； 
    3. 贵阳学院机械工程学院，贵州 贵阳 550025
  • 出版日期:2019-04-30 发布日期:2019-05-10
  • 基金资助:
    国家自然科学基金项目(51505094)；贵州省科技项目(LH字[2016]7467、[2016]2327、[2017]1046、[2017]2016、[2018]1049、[2016]12)；贵 州省教育厅高等学校人文社会科学研究项目(2018qn46)；贵州省教育厅青年科技人才成长项目(黔教合KY字[2017]239)

Research on Model of Product Form Gene Network Driven by Multi-Objective

  1. 1. Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang Guizhou 550025, China; 
    2. The Ares College of Guizhou Minzu University, Guiyang Guizhou 550025, China; 
    3. School of Mechanical Engineering, Guiyang University, Guiyang Guizhou 550025, China
  • Online:2019-04-30 Published:2019-05-10

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摘要： 为解决产品设计过程中用户需求的主观性、模糊性问题，进一步提高产品意象传 达的准确度，提出一种多目标驱动的产品形态基因网络模型(M-FGN)构建方法。以品牌形象、 用户偏好、社会情境为驱动目标，构建多目标驱动空间；分析产品形态基因节点与边的设计， 以产品形态基因为节点，以节点之间的相关性为边，构建 M-FGN 网络；对网络进行拓扑分析， 析出隐性设计知识辅助设计师进行产品形态设计。以某国有企业 AGV 小车形态设计为例，通 过分析 AGV 小车侧面形态 M-FGN 网络，将析出知识提供给设计师进行针对性形态方案设计， 对子代方案进行对比评价，验证了 M-FGN 网络模型的有效性。

关键词: 多目标意象, 基因网络, 形态设计, 用户需求

Abstract: To solve the subjectivity and ambiguity of user demands in the product design process, and to enhance the accuracy of express product image, this study proposed a product form gene network driven by multi-objective (M-FGN). Taking brand image, user preference and social context as the driving targets, we constructed the multi-object goal driven space and analyzed the product form gene node and the edge design. Thus the product form gene was set as node, the correlation of nodes as edges, so as to construct the M-FGN network. The network with topology was also analyzed to generate the implicit design knowledge to assist designers in product form design. Taking a state-owned enterprise tobacco logistics equipment AGV design as an example, we analyzed the side form of AGV’s M-FGN network, provided the knowledge generated to the designers for the specific form design, and made a comparative evaluation of the sub-design, which verified the effectiveness of the M-FGN network model.

Key words: multi-objective image, gene network, form design, user demands