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Evaluating the impact of Idea-Inspire 4.0 on analogical transfer of concepts

Siddharth, L and Chakrabarti, Amaresh (2018) Evaluating the impact of Idea-Inspire 4.0 on analogical transfer of concepts. In: AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING, 32 (4, SI). pp. 431-448.

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Official URL: http://dx.doi.org/10.1017/S0890060418000136

Abstract

The biological domain has the potential to offer a rich source of analogies to solve engineering design problems. However, due to the complexity embedded in biological systems, adding to the lack of structured, detailed, and searchable knowledge bases, engineering designers find it hard to access the knowledge in the biological domain, which therefore poses challenges in understanding the biological concepts in order to apply these concepts to engineering design problems. In order to assist the engineering designers in problem-solving, we report, in this paper, a web-based tool called Idea-Inspire 4.0 that supports analogical design using two broad features. First, the tool provides access to a number of biological systems using a searchable knowledge base. Second, it explains each one of these biological systems using a multi-modal representation: that is, using function decomposition model, text, function model, image, video, and audio. In this paper, we report two experiments that test how well the multi-modal representation in Idea-Inspire 4.0 supports understanding and application of biological concepts in engineering design problems. In one experiment, we use Bloom's method to test ``analysis'' and ``synthesis'' levels of understanding of a biological system. In the next experiment, we provide an engineering design problem along with a biological-analogous system and examine the novelty and requirement-satisfaction (two major indicators of creativity) of resulting design solutions. In both the experiments, the biological system (analogue) was provided using Idea-Inspire 4.0 as well as using a conventional text-image representation so that the efficacy of Idea-Inspire 4.0 is tested using a benchmark.

Item Type: Journal Article
Publication: AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING
Publisher: CAMBRIDGE UNIV PRESS
Additional Information: Copy right for this article belong to CAMBRIDGE UNIV PRESS
Keywords: Analogical and bio-inspired design; creativity and ideation; novelty; requirement-satisfaction; understanding
Department/Centre: Division of Mechanical Sciences > Centre for Product Design & Manufacturing
Date Deposited: 29 Oct 2018 15:32
Last Modified: 29 Oct 2018 15:32
URI: http://eprints.iisc.ac.in/id/eprint/60979

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