Data-Driven Design-by-Analogy: State of the Art and Future Directions
Data-Driven Design-by-Analogy: State of the Art and Future Directions
复制标题
DOI：
10.1115/1.4051681
复制
发表时间：
2021-06
期刊：
影响因子：
--
通讯作者：
Shuo Jiang;Jie Hu;K. Wood;Jianxi Luo
中科院分区：
文献类型：
--
作者：
Shuo Jiang;Jie Hu;K. Wood;Jianxi Luo
类比设计（DbA）是一种设计方法，其中新的解决方案，机会或设计是基于从源域中汲取的灵感在目标域中生成的;它可以使设计师在减轻设计固定和改善设计构思结果方面受益。最近，越来越多的设计数据库和快速发展的数据科学和人工智能技术为开发数据驱动的方法和工具提供了新的机会。在这项研究中，我们调查现有的数据驱动的DbA的研究和分类的数据，方法和应用程序的四个类别，即类比编码，检索，映射和评估的个别研究。基于细致入微的有机回顾和结构化分析，本文阐述了迄今为止数据驱动的DbA研究的最新发展状况，并将其与数据科学和人工智能研究的前沿进行基准测试，以确定该领域有前途的研究机会和方向。最后，我们提出了一个未来的概念数据驱动的DbA系统，集成了所有的命题。
Design-by-Analogy (DbA) is a design methodology wherein new solutions, opportunities or designs are generated in a target domain based on inspiration drawn from a source domain; it can benefit designers in mitigating design fixation and improving design ideation outcomes. Recently, the increasingly available design databases and rapidly advancing data science and artificial intelligence technologies have presented new opportunities for developing data-driven methods and tools for DbA support. In this study, we survey existing data-driven DbA studies and categorize individual studies according to the data, methods, and applications in four categories, namely, analogy encoding, retrieval, mapping, and evaluation. Based on both nuanced organic review and structured analysis, this paper elucidates the state of the art of data-driven DbA research to date and benchmarks it with the frontier of data science and AI research to identify promising research opportunities and directions for the field. Finally, we propose a future conceptual data-driven DbA system that integrates all propositions.