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A computational approach to biologically inspired design

Published online by Cambridge University Press:  20 April 2012

Jacquelyn K.S. Nagel  and
Robert B. Stone
Jacquelyn K.S. Nagel*
Affiliation:
School of Engineering, James Madison University, Harrisonburg, Virginia, USA
Robert B. Stone
Affiliation:
Design Engineering Lab, Department of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, Oregon, USA
*
Reprint requests to: Jacquelyn K.S. Nagel, School of Engineering, James Madison University, 801 Carrier Drive, MSC 4113, Harrisonburg, VA 22807, USA. E-mail: nageljk@jmu.edu
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Abstract

The natural world provides numerous cases for analogy and inspiration in engineering design. During the early stages of design, particularly during concept generation when several variants are created, biological systems can be used to inspire innovative solutions to a design problem. However, identifying and presenting the valuable knowledge from the biological domain to an engineering designer during concept generation is currently a somewhat disorganized process or requires extensive knowledge of the biological system. To circumvent the knowledge requirement problem, we developed a computational approach for discovering biological inspiration during the early stages of design that integrates with established function-based design methods. This research defines and formalizes the information identification and knowledge transfer processes that enable systematic development of biologically inspired designs. The framework that supports our computational design approach is provided along with an example of a smart flooring device to demonstrate the approach. Biologically inspired conceptual designs are presented and validated through a literature search and comparison to existing products.

Keywords

BiomimicryConcept GenerationDesignFunction
Type
Special Issue Articles
Information
AI EDAM , Volume 26 , Issue 2: Design Computing and Cognition (DCC'10) , May 2012 , pp. 161 - 176
Copyright
Copyright © Cambridge University Press 2012

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