2018
DOI: 10.1017/s0890060418000136
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Evaluating the impact of Idea-Inspire 4.0 on analogical transfer of concepts

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 des… Show more

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Cited by 36 publications
(33 citation statements)
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“…The US patent database contains useful technical knowledge from patents but was not in the form of semantic networks. Idea Inspire 4.0 (Siddharth and Chakrabarti, 2018) is an idea generation support tool providing access to biological information in a human-curated knowledge base.…”
Section: Semantic Network As Knowledge Bases For Engineering Designmentioning
confidence: 99%
“…The US patent database contains useful technical knowledge from patents but was not in the form of semantic networks. Idea Inspire 4.0 (Siddharth and Chakrabarti, 2018) is an idea generation support tool providing access to biological information in a human-curated knowledge base.…”
Section: Semantic Network As Knowledge Bases For Engineering Designmentioning
confidence: 99%
“…For instance, to redesign a wheel, the keyword search must include "to move" and "locomotion" which will yield suggestions like "flagella of bacteria" and the "rolling locomotion of the moth caterpillar". Furthermore, it was found that adequate expertise with these models are required to add data to these databases [22].…”
Section: Function Driven Bionic Designmentioning
confidence: 99%
“…The literature on FR does not provide evidence using examples that the model could be used for decomposing objects. The latest developments on the SAPPhIRE model indicate that it can facilitate the decomposition of complex systems …”
Section: Representing a Case Of Failurementioning
confidence: 99%
“…The proposed model describes state transitions according to physical effects, unlike IBIS‐FAD. The use of a causality model in View III allows learning patterns across several abstractions and analogically map from one case to the other; the ability of SAPPhIRE model to do so is empirically validated by Siddharth and Chakrabarti …”
Section: Support Deployment and Benchmarkingmentioning
confidence: 99%