A knowledge-based ideation approach for bio-inspired design
Year: 2023
Editor: Kevin Otto, Boris Eisenbart, Claudia Eckert, Benoit Eynard, Dieter Krause, Josef Oehmen, Nad
Author: Chen, Liuqing (1,2); Cai, Zebin (1); Jiang, Zhaojun (3); Long, Qi (4); Sun, Lingyun (1,2); Childs, Peter (5); Zuo, Haoyu (5)
Series: ICED
Institution: 1: Department of Computer Science and Technology, Zhejiang University, Hangzhou 310030, China;
2: Singapore Innovation and AI Joint Research Lab, Zhejiang University, Hangzhou 310030, China;
3: School of mechanical engineering, Tianjin University, Tianjin 300350, China;
4: Zhejiang University-University of Illinois at Urbana-Champaign Institute, Haining 314400, China;
5: Dyson School of Design Engineering, Imperial College London, London SW7 2AZ, UK
Section: Design Methods
Page(s): 0231-0240
DOI number: https://doi.org/10.1017/pds.2023.24
ISBN: -
ISSN: -
Abstract
Bio-inspired design (BID) involves generating innovative ideas for engineering design by drawing inspiration from natural biological phenomena and systems, using a form of design-by-analogy. Despite its many successes, BID approaches encounter research challenges including unstructured data and existing models that hinder comprehension and processing, limited focus on finding biological knowledge compared to defined problems, and insufficient guidance of the ideation process with algorithms. This paper proposes a knowledge-based approach to address the challenges. The approach involves transforming unstructured data into structured knowledge, including information about natural sources, their benefits, and applications. The structured knowledge is then used to construct a semantic network, enabling designers to retrieve information for BID in two ways. Furthermore, a three-step ideation method is developed to encourage divergent thinking and explore additional potential solutions by drawing inspiration and utilizing knowledge. The knowledge-based BID approach is implemented as a tool and design cases are conducted to illustrate the process of applying this tool for BID.
Keywords: Bio-inspired design / biomimetics, Big data, Design methods, Semantic network, Data-driven-design