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A methodology for supporting “transfer” in biomimetic design

Published online by Cambridge University Press:  25 October 2010

Julian Sartori
Affiliation:
Biomimetics Innovation Centre, University of Applied Sciences, Bremen, Germany
Ujjwal Pal
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, India
Amaresh Chakrabarti
Affiliation:
Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore, India

Abstract

Biomimetics involves transfer from one or more biological examples to a technical system. This study addresses four questions. What are the essential steps in a biomimetic process? What is transferred? How can the transferred knowledge be structured in a way useful for biologists and engineers? Which guidelines can be given to support transfer in biomimetic design processes? In order to identify the essential steps involved in carrying out biomimetics, several procedures found in the literature were summarized, and four essential steps that are common across these procedures were identified. For identification of mechanisms for transfer, 20 biomimetic examples were collected and modeled according to a model of causality called the SAPPhIRE model. These examples were then analyzed for identifying the underlying similarity between each biological and corresponding analogue technical system. Based on the SAPPhIRE model, four levels of abstraction at which transfer takes place were identified. Taking into account similarity, the biomimetic examples were assigned to the appropriate levels of abstraction of transfer. Based on the essential steps and the levels of transfer, guidelines for supporting transfer in biomimetic design were proposed and evaluated using design experiments. The 20 biological and analogue technical systems that were analyzed were similar in the physical effects used and at the most abstract levels of description of their functionality, but they were the least similar at the lowest levels of abstraction: the parts involved. Transfer most often was carried out at the physical effect level of abstraction. Compared to a generic set of guidelines based on the literature, the proposed guidelines improved design performance by about 60%. Further, the SAPPhIRE model turned out to be a useful representation for modeling complex biological systems and their functionality. Databases of biological systems, which are structured using the SAPPhIRE model, have the potential to aid biomimetic concept generation.

Type
Special Issue Articles
Copyright
Copyright © Cambridge University Press 2010

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References

REFERENCES

Barthlott, W., & Neinhuis, C. (1997). Purity of the sacred lotus, or escape from contamination in biological surfaces. Planta 202(1), 18.CrossRefGoogle 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), 113132.CrossRefGoogle Scholar
Chakrabarti, A., & Taura, T. (2006). Computational support of synthesis and analysis of behaviour of artefacts using physical effects: some challenges. Proc. 9th Int. Design Conf., DESIGN 2006, pp. 18.Google 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), 4559.CrossRefGoogle Scholar
DaimlerChrysler. (2005). DaimlerChrysler Hightech Report 2005, pp. 58–63. Accessed at http://www.daimlerchrysler.com/Projects/c2c/channel/documents/783295_Gone_Fishin.pdfGoogle Scholar
Gramann, J. (2004). Problemmodelle und Bionik als Methode. PhD Thesis. Technical University Munich.Google Scholar
Helms, M.E., Vattam, S.S., & Goel, A.K. (2009). Biologically inspired design: process and products. Design Studies 30(5), 606622.CrossRefGoogle Scholar
Hill, B. (1997). Innovationsquelle Natur: Naturorientierte Innovationsstrategie für Entwickler, Konstrukteure und Designer. Aachen, Germany: Shaker.Google Scholar
Hill, B. (2005). Goal setting through contradiction analysis in the bionics-oriented construction process. Creativity and Innovation Management 14(1), 5965.CrossRefGoogle Scholar
Kesel, A., & Liedert, R. (2007). Learning from nature: non-toxic biofouling control by shark skin effect. Comparative Biochemistry and Physiology 146A(Suppl. 1), 130.CrossRefGoogle Scholar
Korzybski, A. (1933). A non-Aristotelian system and its necessity for rigour in mathematics and physics. Science and Sanity [n.v.], 747761.Google Scholar
Mann, D. (2001). System operator tutorial–9—windows on the world. TRIZ Journal. Accessed at http://www.triz-journal.com/archives/2001/09/c/index.htm on April 20, 2010.Google Scholar
Mattheck, C., & Bethge, K. (1998). The structural optimization of trees. Naturwissenschaften 85(1), 110.CrossRefGoogle Scholar
Mayer, G. (2005). Rigid biological systems as models for synthetic composites. Science 310, 11441147.CrossRefGoogle ScholarPubMed
Milwich, M., Speck, T., Speck, O., Stegmaier, T., & Planck, H. (2006). Biomimetics and technical textiles: solving engineering problems with the help of nature's wisdom. American Journal of Botany 93(10), 14551465.CrossRefGoogle ScholarPubMed
Nachtigall, W. (2002). Bionik: Grundlagen und Beispiele für Ingenieure und Naturwissenschaftler. Berlin: Springer.CrossRefGoogle Scholar
Nachtigall, W., & Bluechel, K.G. (2000). Das große Buch der Bionik. Stuttgart: DVA.Google Scholar
Pahl, G., & Beitz, W. (1996). Engineering Design: A Systematic Approach. New York: Springer.CrossRefGoogle Scholar
Rodenacker, W. (1976). Methodisches Konstruieren. Berlin: Springer.CrossRefGoogle Scholar
Sachs, L., & Hedderich, J. (2006). Angewandte Statistik, 12th ed.Berlin: Springer.Google Scholar
Schild, K., Herstatt, C., & Lüthje, C. (2004). How to Use Analogies for Breakthrough Innovations. Hamburg: Technical University of Hamburg, Institute of Technology and Innovation Management.Google Scholar
Schmidt, J.C. (2005). Bionik und Interdisziplinarität. Wege zu einer bionischen Zirkulationstheorie der Interdisziplinarität. In Bionik. Aktuelle Forschungsergebnisse aus Natur-, Ingenieur- und Geisteswissenschaften (Rossmann, T., & Tropea, C., Eds.), pp. 219246. Berlin: Springer.Google Scholar
Srinivasan, V., & Chakrabarti, A. (2009). An empirical evaluation of novelty–SAPPhIRE relationship. ASME 2009 Int. Design Engineering Technical Conf. Computers and Information in Engineering Conf., IDETC/CIE, San Diego, CA, August 30–September 2.CrossRefGoogle Scholar
Suhr, S.H., Song, Y.S., Lee, S.J., & Sitti, M. (2005). Biologically inspired miniature water strider robot. Proc. Robotics: Science and Systems I, pp. 42–48. Cambridge, MA: MIT Press.Google Scholar
Terninko, J., Zusman, A., & Zlotin, B. (1998). Systematic Innovation. An introduction to TRIZ (Theory of Inventive Problem Solving). Boca Raton, FL: St. Lucie Press.CrossRefGoogle Scholar
Turner, J.S. (2001). On the mound of macrotermes michaelseni as an organ of respiratory gas exchange. Physiological and Biochemical Zoology 74(6), 798822.CrossRefGoogle ScholarPubMed
Vattam, S.S., Helms, M.E., & Goel, A.K. (2008). Compound analogical design: interaction between problem decomposition and analogical transfer in biologically inspired design. Proc. 3rd Int. Conf. Design Computing and Cognition, pp. 377396. Berlin: Springer.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), 471482.Google Scholar
Vogel, S., Ellington, C.P., & Kilgore, D.L. (1973). Wind-induced ventilation of the burrow of the prairie-dog, Cynomys ludovicianus. Journal of Comparative Physiology 85A(1), 114.Google Scholar