{"title":"Measuring ideation effectiveness in bioinspired design","authors":"Sunil Sharma, Suraj Gururani, P. Sarkar","doi":"10.1017/S0890060423000070","DOIUrl":null,"url":null,"abstract":"Abstract Analogies provide better concept generation in engineering design. This ideation can be measured by metrics such as usefulness, novelty, variety, quality, completeness, and quantity. In bioinspired design, biological analogies are used to inspire design concepts. Biological analogies have been provided in earlier studies to measure ideation effectiveness. Tools like IDEA-INSPIRE, DANE, etc., allow designers to search analogies using functions, behaviors, and structures. However, we wanted to inquire about the effect of providing a very large number of biological analogies (26), fulfilling the same function to develop bioinspired solutions. In this paper, an empirical study has been performed to analyze the effect of biological analogies on ideation. The designers are exposed to provided multiple biological analogies and generate concepts for which four ideation metrics: novelty, variety, quality, and quantity metrics are evaluated. The results are compared to the unaided condition where other designers are given the same task. A new method to measure variety using a 2D matrix has been presented. The results suggest that designers can generate bioinspired solutions when multiple biological analogies performing similar functions are provided in a presentable format. Statistically, exposure to multiple biological analogies in idea generation can significantly increase the variety of design ideas. The novelty, quality, and quantity for the biological group and control group remain the same.","PeriodicalId":50951,"journal":{"name":"Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2023-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ai Edam-Artificial Intelligence for Engineering Design Analysis and Manufacturing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1017/S0890060423000070","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Analogies provide better concept generation in engineering design. This ideation can be measured by metrics such as usefulness, novelty, variety, quality, completeness, and quantity. In bioinspired design, biological analogies are used to inspire design concepts. Biological analogies have been provided in earlier studies to measure ideation effectiveness. Tools like IDEA-INSPIRE, DANE, etc., allow designers to search analogies using functions, behaviors, and structures. However, we wanted to inquire about the effect of providing a very large number of biological analogies (26), fulfilling the same function to develop bioinspired solutions. In this paper, an empirical study has been performed to analyze the effect of biological analogies on ideation. The designers are exposed to provided multiple biological analogies and generate concepts for which four ideation metrics: novelty, variety, quality, and quantity metrics are evaluated. The results are compared to the unaided condition where other designers are given the same task. A new method to measure variety using a 2D matrix has been presented. The results suggest that designers can generate bioinspired solutions when multiple biological analogies performing similar functions are provided in a presentable format. Statistically, exposure to multiple biological analogies in idea generation can significantly increase the variety of design ideas. The novelty, quality, and quantity for the biological group and control group remain the same.
期刊介绍:
The journal publishes original articles about significant AI theory and applications based on the most up-to-date research in all branches and phases of engineering. Suitable topics include: analysis and evaluation; selection; configuration and design; manufacturing and assembly; and concurrent engineering. Specifically, the journal is interested in the use of AI in planning, design, analysis, simulation, qualitative reasoning, spatial reasoning and graphics, manufacturing, assembly, process planning, scheduling, numerical analysis, optimization, distributed systems, multi-agent applications, cooperation, cognitive modeling, learning and creativity. AI EDAM is also interested in original, major applications of state-of-the-art knowledge-based techniques to important engineering problems.