Research Papers: Analogy Evaluation

Using Stochastic Multicriteria Acceptability Analysis in Biologically Inspired Design as a Multidisciplinary Tool to Assess Biology-to-Engineering Transfer Risk for Candidate Analogs

[+] Author and Article Information
M. Lindsey Williams

Mechanical Engineering,
Texas Tech University,
7th and Boston,
Lubbock, TX 79409
e-mail: lindsey.williams@ttu.edu

Atila Ertas

Department of Mechanical Engineering,
Texas Tech University,
7th and Boston,
Lubbock, TX 79409
e-mail: atila.ertas@ttu.edu

Derrick Tate

Associate Professor
Founding Head
Department of Industrial Design,
XI'an Jiaotong-Liverpool University,
Suzhou, Jiangsu 215123, China
e-mail: d.tate@ttu.edu

1Corresponding author.

Contributed by the Design Theory and Methodology Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received January 22, 2014; final manuscript received July 25, 2014; published online October 8, 2014. Assoc. Editor: Ashok K. Goel.

J. Mech. Des 136(11), 111107 (Oct 08, 2014) (7 pages) Paper No: MD-14-1073; doi: 10.1115/1.4028170 History: Received January 22, 2014; Revised July 25, 2014

Inherent in biologically inspired design (BID) is the selection of one or more analogs from which one or more strategies are extracted and transferred into the engineering domain. The selection of an analog is a fundamental step in biomimetic process, but locating relevant biological analogies can be challenging. Often, designers may fixate on an analogy or choose an established analogy without rigorous examination of alternatives. This practice is problematic—as basing a new design on an invalid assumption can lead to suboptimal results. This paper makes contribution to evaluation of analogy utility. The contribution is made by combining stochastic multicriteria acceptability analysis (SMAA) with a set of criteria, derived from BID, to assist multidisciplinary decision makers (DMs) in evaluating candidate design analogs. The resulting framework, which we call the biotransferability framework, is being developed to assist multidisciplinary teams to choose, rank, or sort candidate design analogs by assessing biology-to-engineering transfer risk.

Copyright © 2014 by ASME
Topics: Design , Biology , Risk , Teams , Shells
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Grahic Jump Location
Fig. 1

Use of SMAA during the BID process can help to choose, rank, or sort alternatives (analogs)




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