SEABIRD: Scalable search for systematic biologically inspired design

Vandevenne, Dennis; Verhaegen, Paul-Armand; Dewulf, Simon; Duflou, Joost R.

doi:10.1017/s0890060415000177

Cited by 30 publications

(58 citation statements)

References 57 publications

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“…contributions that require complex model instantiation for each corpus entry (Chakrabarti, Sarkar, Leelavathamma, & Nataraju, 2005;Nagel & Stone, 2012;Vattam, Wiltgen, Helms, Goel, & Yen, 2010) and one recent approach based on technical patent and biological paper mining (Vandevenne, Verhaegen, & Duflou, 2015).…”

Section: Bid Supporting Toolsmentioning

confidence: 99%

Enhancing novelty with knowledge-based support for Biologically-Inspired Design

2016

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With a two-decade consistent research interest for Systematic BiologicallyInspired Design, a number of methods and tools to support bio-ideation have been proposed. However, objective quantification of the effects these aids have on the design outcomes is rare. This contribution presents an impact analysis of the most popular knowledge-based tool, AskNature, in the form of an outcomebased study. The results consistently support a common claim used in favour of bio-inspired design, i.e. the expectation of identifying more out-of-the-box solutions. Furthermore, to further facilitate biological solution analysis and cross-domain knowledge transfer, an adaptation to AskNature's stimuli format d i.e. adding a graphical illustration of the biological solution principle d is validated to further boost novelty. C reative problem solving is a key task for companies pursuing inventions that may grow into successful innovations. One strategy for solving new problems is learning from previously solved analogous problems. In Design-by-Analogy (DbA) a solution principle behind an already solved problem is transferred to solve a new problem. For example, when looking for new ways to unfold a tent, products with similar functionality, like for instance umbrellas, can be sources of inspiration and knowledge transfer. Biologically-Inspired Design (BID) is a specific type of between domain DbA where inspiration is taken from the natural world (source domain) to solve technical problems or challenges (target domain). Three frequently used arguments for looking at nature for inspiration are (1) the proven performance of biological systems, (2) the potential for sustainable products and (3) the potential for finding out-of-the-box solutions. The first, proven performance of biological systems, logically follows from the overwhelming evidence supporting evolution, i.e. the change in inherited characteristics of biological populations over successive generations, a continuous repetition of a non-random selection mechanism (survival of the fittest) applied to traits subject to random variation. The products of these continuous improvement iterations d solution principles of biological systems d Corresponding author: Dennis Vandevenne dennis.vandevenne@ kuleuven.be www.elsevier.com/locate/destud 0142-694X Design Studies --(2016) --e--http://dx.Please cite this article in press as: Vandevenne, D., et al., Enhancing novelty with knowledge-based support for Biologically-Inspired Design, Design Studies (2016), http://dx.

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Section: Bid Supporting Toolsmentioning

confidence: 99%

Enhancing novelty with knowledge-based support for Biologically-Inspired Design

2016

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“…A limitation is that the proposed software requires the user to detail function decomposition trees on a graphical user interface. Vandevenne et al (2016) proposed a scalable search for systematic biologically inspired design. This utilised functional characteristics to identify candidate products for design by analogy, thereby increasing the variety and novelty of ideas subsequently generated (Verhaegen et al 2011).…”

Section: Patent Clusteringmentioning

confidence: 99%

The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches

Wodehouse¹,

Vasantha²,

Corney³

et al. 2017

Des. Sci.

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This paper presents a new crowdsourcing approach to the construction of patent clusters, and systematically benchmarks it against previous expert and algorithmic approaches. Patent databases should be rich sources of inspiration which could lead engineering designers to novel solutions for creative problems. However, the sheer volume and complexity of patent information means that this potential is rarely realised. Rather than the keyword driven searches common in commercial systems, designers need tools that help them to understand patents in the context of the problem they are considering. This paper presents an approach to address this problem by using crowd intelligence for effective generation of patent clusters at lower cost and with greater rationale. A systematic study was carried out to compare the crowd's efficiency with both expert and algorithmic patent clusters, with the results indicating that the crowd was able to create 80% more patent pairs with appropriate rationale.

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“…Vandevenne et al [47] proposed a scalable search for systematic biologically inspired design (SEABIRD). SEABIRD represented product and biological elements extracted from patent and biological databases.…”

Section: Design-by-analogymentioning

confidence: 99%