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SEABIRD: Scalable search for systematic biologically inspired design

Published online by Cambridge University Press:  29 April 2015

Dennis Vandevenne ,
Paul-Armand Verhaegen ,
Simon Dewulf  and
Joost R. Duflou
Dennis Vandevenne*
Affiliation:
Centre for Industrial Management, Department of Mechanical Engineering, Katholieke Universiteit Leuve, Celestijnenlaan, Leuven, Belgium
Paul-Armand Verhaegen
Affiliation:
Centre for Industrial Management, Department of Mechanical Engineering, Katholieke Universiteit Leuve, Celestijnenlaan, Leuven, Belgium
Simon Dewulf
Affiliation:
AULIVE NV, Ieper, Belgium
Joost R. Duflou
Affiliation:
Centre for Industrial Management, Department of Mechanical Engineering, Katholieke Universiteit Leuve, Celestijnenlaan, Leuven, Belgium
*
Reprint requests to: Dennis Vandevenne, Centre for Industrial Management, Department of Mechanical Engineering, Katholieke Universiteit Leuve, Celestijnenlaan 300A, 3001 Leuven, Belgium. E-mail: dennis.vandevenne@kuleuven.be
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Abstract

As more and more people are increasingly turning to nature for design inspiration, tools and methodologies are developed to support the systematic bioideation process. State-of-the-art approaches struggle with expanding their knowledge bases because of interactive work required by humans per biological strategy. As an answer to this persistent challenge, a scalable search for systematic biologically inspired design (SEABIRD) system is proposed. This system leverages experience from the product aspects in design by analogy tool that identifies candidate products for between-domain design by analogy. SEABIRD is based on two conceptual representations, product and organism aspects, extracted from, respectively, a patent and a biological database, that enable leveraging the ever growing body of natural-language biological texts in the systematic bioinspired design process by eliminating interactive work by humans during corpus expansion. SEABIRD's search is illustrated and validated with three well-known biologically inspired design cases.

Keywords

Bioinspired DesignBiologically Inspired DesignBiomimicryCreativity and Ideation
Type
Regular Articles
Information
AI EDAM , Volume 30 , Issue 1 , February 2016 , pp. 78 - 95
Copyright
Copyright © Cambridge University Press 2015 

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References

REFERENCES

Altshuller, G.S. (1984). Creativity as an Exact Science: The Theory of the Solution of Inventive Problems. New York: Gordon & Breach Science Publishers.CrossRefGoogle Scholar
Autumn, K., Dittmore, A., Santos, D., Spenko, M., & Cutkosky, M. (2006). Frictional adhesion: a new angle on gecko attachment. Journal of Experimental Biology 209(18), 3569–3579.CrossRefGoogle ScholarPubMed
Bajželj, B., Allwood, J.M., & Cullen, J.M. (2013). Designing climate change mitigation plans that add up. Environmental Science and Technology 47(14), 8062–8069.CrossRefGoogle ScholarPubMed
Bar-Cohen, Y. (2006). Biomimetics—using nature to inspire human innovation. Bioinspiration & Biomimetics 1(1), 1–12.CrossRefGoogle ScholarPubMed
Bar-Cohen, Y. (2011). Biomimetics: Nature-Based Innovation. New York: CRC/Taylor & Francis.Google Scholar
Bartol, I.K., Gharib, M., Webb, P.W., Weihs, D., & Gordon, M.S. (2005). Body-induced vortical flows: a common mechanism for self-corrective trimming control in boxfishes. Journal of Experimental Biology 208(Pt. 2), 327–344.CrossRefGoogle ScholarPubMed
Benyus, J.M. (1997). Biomimicry: Innovation Inspired by Nature. New York: Harper Perennial.Google Scholar
Berry, M.W., Dumais, S.T., & O'Brien, G.W. (1995). Using linear algebra for intelligent information retrieval. SIAM Review 37(4), 573–595.CrossRefGoogle Scholar
Bhushan, B. (2009). Biomimetics: lessons from nature–an overview. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367(1893), 1445–1486.CrossRefGoogle ScholarPubMed
Bonser, R.H.C. (2006). Patented biologically-inspired technological innovations: a twenty year review. Journal of Bionic Engineering 3(1), 39–41.CrossRefGoogle Scholar
Bonser, R.H.C., & Vincent, J.F.V. (2007). Technology trajectories, innovation, and the growth of biomimetics. Journal of Mechanical Engineering Science 221(10), 1177–1180.CrossRefGoogle Scholar
Brants, T. (2000). TnT: a statistical part-of-speech tagger. Proc. 6th Conf. Applied Natural Language Processing, ANLC ‘00, pp. 224–331. Stroudsburg, PA: Association for Computational Linguistics.Google Scholar
Chakrabarti, A., Sarkar, P., Leelavathamma, B., & Nataraju, B.S. (2005). A functional representation for aiding biomimetic and artificial inspiration of new ideas. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 19(2), 113–132.CrossRefGoogle Scholar
Charniak, E. (1997). Statistical techniques for natural language parsing. AI Magazine 18(4), 33–43.Google Scholar
Cheong, H., Chiu, I., Shu, L.H., Stone, R.B., & McAdams, D.A. (2011) Biologically meaningful keywords for functional terms of the functional basis. Journal of Mechanical Design 133(2), 021007.CrossRefGoogle Scholar
Cheong, H., Hallihan, G., & Shu, L.H. (2012). Understanding analogical reasoning in biomimetic design: an inductive approach. Proc. Design Computing and Cognition Conf., DCC'12 (Gero, J.S., Ed.). Berlin: Springer.Google Scholar
Cheong, H., & Shu, L.H. (2013). Reducing cognitive bias in biomimetic design by abstracting nouns. CIRP Annals Manufacturing Technology 62(1), 111–114.CrossRefGoogle Scholar
Cheong, H, & Shu, L.H. (2014). A method to retrieve causally related functions from natural-language text for biomimetic design. Journal of Mechanical Design. Advance online publication. doi:10.1115/1.4027494CrossRefGoogle Scholar
Chiu, I., & Shu, L.H. (2005). Bridging cross-domain terminology for biomimetic design. Proc. ASME 2005 Int. Design Engineering Technical Conf., Paper No. DETC2005-84908, Long Beach, CA, September 24–28.CrossRefGoogle Scholar
Chiu, I., & Shu, L.H. (2007). Biomimetic design through natural language analysis to facilitate cross-domain information retrieval. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 21(1), 45–59.CrossRefGoogle Scholar
Deerwester, S.C., Dumais, S.T., Landauer, T.K., Furnas, G.W., & Harshman, R.A. (1990). Indexing by latent semantic analysis. Journal of the American Society of Information Science 41(6), 391–407.3.0.CO;2-9>CrossRefGoogle Scholar
Deldin, J.M., & Schuknecht, M. (2014). The AskNature database: enabling solutions in biomimetic design. In Biologically Inspired Design (Goel, A.K., McAdams, D.A., & Stone, R.B., Eds.), pp. 17–27. London: Springer–Verlag.CrossRefGoogle Scholar
Fall, C.J., Törcsvári, A., Benzineb, K., & Karetka, G. (2003) Automated categorization in the international patent classification. ACM Special Interest Group on Information Retrieval Forum 37(1), 10–25.Google Scholar
Fellbaum, C. (1998). WordNet: An Electronic Lexical Database. Cambridge, MA: MIT Press.CrossRefGoogle Scholar
Fox, C. (1989). A stop list for general text. ACM Special Interest Group on Information Retrieval Forum 24(1–2), 19–21.Google Scholar
Gebeshuber, I.C., Gruber, P., & Drack, M. (2009). A gaze into the crystal ball: biomimetics in the year 2059. Journal of Mechanical Engineering Science 223(12), 2899–2918.CrossRefGoogle Scholar
Gentner, D., & Markman, A.B. (1997). Structure mapping in analogy and similarity. American Psychologist 52(1), 45–56.CrossRefGoogle Scholar
Gerner, M., Nenadic, G., & Bergman, C.M. (2010). LINNAEUS: a species name identification system for biomedical literature. BMC Bioinformatics 11(85). doi:10.1186/1471-2105-11-85CrossRefGoogle ScholarPubMed
Goel, A.K., Vattam, S., Wiltgen, B., & Helms, M. (2012). Cognitive, collaborative, conceptual and creative: four characteristics of the next generation of knowledge-based CAD systems: a study in biologically inspired design. Computer-Aided Design 44(10), 879–900.CrossRefGoogle Scholar
Google Merchant Center. (2014). Categorize your products. Accessed at https://support.google.com/merchants/answer/160081?hl=en on May 14, 2008.Google Scholar
Helms, M., Vattam, S.S., & Goel, A.K. (2009). Biologically inspired design: process and products. Design Studies 30(5), 606–622.CrossRefGoogle Scholar
Intergovernmental Panel on Climate Change. (2007). IPCC Fourth Assessment Report Working Group I Report: The Physical Science Basis. New York: Cambridge University Press.Google Scholar
Kaiser, H.F. (1958). The Varimax criterion for analytic rotation in factor analysis. Psychometrika 23(3), 187–200.CrossRefGoogle Scholar
Kaiser, M.K., Farzaneh, H.H., & Lindemann, U. (2012). An approach to support searching for biomimetic solutions based on system characteristics and its environmental interactions. Proc. Design 2012, pp. 969–978, Cavtat-Dubrovnik, Croatia, September 24–28.Google Scholar
Kaiser, M.K., Farzaneh, H.H., & Lindemann, U. (2014). BIOscrabble—the role of different types of search terms when searching for biological inspiration in biological research articles. Proc. Design 2014, pp. 241–250, Cavtat-Dubrovnik, Croatia, May 19–22.Google Scholar
Landauer, T.K., & Dumais, S.T. (1997). A solution to Plato's problem: the latent semantic analysis theory of acquisition, induction, and representation of knowledge. Psychological Review 104(2), 211–240.CrossRefGoogle Scholar
Larkey, L.S. (1999) A patent search and classification system. Proc. 4th ACM Conf. Digital Libraries, pp. 179–187. New York: ACM Press.CrossRefGoogle Scholar
Lenau, T., Dentel, A., Ingvarsdóttir, Þ., & Guðlaugsson, T. (2010). Engineering design of an adaptive leg prosthesis using biological principles. Proc. Design 2010, pp. 331–340, Cavtat-Dubrovnik, Croatia, May 17–20.Google Scholar
Lepora, N.F., Verschure, P., & Prescott, T.J. (2013). The state of the art in biomimetics. Bioinspiration & Biomimetics 8(1), 013001.CrossRefGoogle ScholarPubMed
Linnaeus, C. (1767). Systema Naturae. Amsterdam: Author.Google Scholar
Mak, T.W., & Shu, L.H. (2008). Using descriptions of biological phenomena for idea generation. Research in Engineering Design 19(1), 21–28.CrossRefGoogle Scholar
Mirasol. (2009). Competitive display technologies [White paper]. Accessed at http://www.qualcomm.com/sites/default/files/uploads/competitivedisplaytechnologies-06-2009.pdfGoogle Scholar
Murphy, J.T. (2011). Patent-based analogy search tool for innovative concept generation. PhD Thesis. University of Texas at Austin, Department of Mechanical Engineering.Google Scholar
Nagel, J.K.S., Nagel, B.I., Stone, R.B., & McAdams, D.A. (2010). Function-based, biologically inspired concept generation. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24(4), 521–535.CrossRefGoogle Scholar
Nagel, J.K.S., & Stone, R.B. (2012). A computational approach to biologically inspired design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 26(2), 161–176.CrossRefGoogle Scholar
Nelson, B., Wilson, J., & Yen, J. (2009). A study of biologically-inspired design as a context for enhancing student innovation. Proc. 39th ASEE/IEEE Frontiers in Education Conf., pp. 1–5, San Antonio, TX, October 18–21.CrossRefGoogle Scholar
Purves, W.K., Sadava, D., Orians, G.H., & Heller, H.C. (2001). Life: The Science of Biology, 6th ed., Sunderland, MA: Sinauer Associates.Google Scholar
Randolph, J.J. (2005). Free-marginal multirater kappa: an alternative to Fleiss’ fixed-marginal multirater kappa. Proc. Joensuu University Learning and Instruction Symp., Joensuu, Finland.Google Scholar
Salton, G., & Buckley, C. (1988) Term-weighting approaches in automated text retrieval. Information Processing & Management 24(5), 513–523.CrossRefGoogle Scholar
Salton, G., Wong, A., & Yang, C.S. (1975). A vector space model for automatic indexing. Communications of the ACM 18(11), 613–620.CrossRefGoogle Scholar
Sartori, J., Pal, U., & Chakrabarti, A. (2010). A methodology for supporting “transfer” in biomimetic design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24(4), 483–505.CrossRefGoogle Scholar
Shu, L.H. (2010). A natural-language approach to biomimetic design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24(4), 507–519.CrossRefGoogle Scholar
Skillicorn, D. (2007). Understanding Complex Datasets: Data Mining with Matrix Decompositions. New York: Chapman & Hall.CrossRefGoogle Scholar
Srinivasan, V., Chakrabarti, A., & Lindemann, U. (2012). Towards an ontology of engineering design using SAPPhIRE model. Proc. CIRP Design 2012, pp. 17–26. London: Springer.Google Scholar
Turner, S., & Soar, R. (2008). Beyond biomimicry: what termites can tell us about realizing the living building. Proc. 1st Int. Conf. Industrialized, Intelligent Construction (13CON), pp. 221–237, Loughborough, May 14–16.Google Scholar
Vandevenne, D., Verhaegen, P.-A., & Duflou, J.R. (2014). Methods and algorithms for systematic biologically-inspired design. PhD Thesis. KU Leuven.Google Scholar
Vandevenne, D., Kellens, K., Banck, M., Clijsters, H., Verhaegen, P.-A., & Duflou, J.R. (2012). A framework for assessing the sustainability of biologically-inspired products. Proc. Innovation for Sustainable Production, Bruges, Belgium, May 6–9.Google Scholar
Vandevenne, D., Verhaegen, P.-A., Dewulf, S., & Duflou, J.R. (2011). A scalable approach for the integration of large knowledge repositories in the biologically-inspired design process. Proc. 18th Int. Conf. Engineering Design (ICED11) 6, pp. 210–219, Copenhagen, Denmark, August 15–19.Google Scholar
Vandevenne, D., Verhaegen, P.-A., Dewulf, S., & Duflou, J.R. (2014). A scalable approach for ideation in biologically inspired design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing. Advance online publication. doi:10.1017/S0890060414000122CrossRefGoogle Scholar
Vandevenne, D., Verhaegen, P.-A., & Duflou, J.R. (2015). Mention and focus organism detection and their applications for scalable systematic bio-ideation tools. Journal of Mechanical Design, 136, Article 111104.Google Scholar
Vattam, S.S., Helms, M.E., & Goel, A.K. (2010). A content account of creative analogies in biologically inspired design. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 24(4), 467–481.CrossRefGoogle Scholar
Vattam, S.S., Wiltgen, B., Helms, M., Goel, A.K., & Yen, J. (2010). DANE: fostering creativity in and through biologically inspired design. Proc. Int. Conf. Design Creativity, pp. 115–122, Kobe, Japan, November.Google Scholar
Vattam, S.S., & Goel, A.K. (2011). Semantically annotating research articles for interdisciplinary design. K-CAP'11, pp. 165–166. New York: ACM.CrossRefGoogle Scholar
Verhaegen, P.-A., D'hondt, J., Vertommen, J., Dewulf, S., & Duflou, J.R. (2009). Quantifying and formalizing product aspects through patent mining. Proc. ETRIA TRIZ Future 2009, Timisoara, Romania.Google Scholar
Verhaegen, P.-A., D'hondt, J., Vandevenne, D., Dewulf, S., & Duflou, J.R. (2011). Identifying candidates for design-by-analogy. Computers in Industry 62(4), 446–459.CrossRefGoogle Scholar
Verhaegen, P.-A., & Duflou, J.R. (2013). Methods and algorithms for systematic innovation. PhD Thesis. KU Leuven.Google Scholar
Verhaegen, P., Peeters, J., Vandevenne, D., Dewulf, S., & Duflou, J.R. (2011). Effectiveness of the PAnDA ideation tool. Procedia Engineering 9, 63–76.CrossRefGoogle Scholar
Vincent, J.F.V., Bogatyreva, O.A., Bogatyrev, N.R., Bowyer, A., & Pahl, A.K. (2006) Biomimetics: its practice and theory. Journal of the Royal Society: Interface 3(9), 471–482.Google ScholarPubMed
Vukusic, P. (2006). Structural colour in Lepidoptera. Current Biology 16(16), R621–R623.CrossRefGoogle ScholarPubMed
Wilson, J.O., Rosen, D., Nelson, B.A., & Yen, J. (2010). The effects of biological examples in idea generation. Design Studies 31(2), 169–186.CrossRefGoogle Scholar
Zipf, G.K. (1932). Selective Studies and the Principle of Relative Frequency in Language. Cambridge, MA: Harvard University Press.CrossRefGoogle Scholar