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The Complexities of Engineering Design and System Modeling

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Conference

2012 ASEE Annual Conference & Exposition

Location

San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012

ISSN

2153-5965

Conference Session

Linking Engineering and Liberal Education

Tagged Division

Liberal Education/Engineering & Society

Page Count

16

Page Numbers

25.1279.1 - 25.1279.16

DOI

10.18260/1-2--22036

Permanent URL

https://peer.asee.org/22036

Download Count

124

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Paper Authors

biography

Gayle E. Ermer Calvin College

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Gayle Ermer is a professor of engineering at Calvin College in Grand Rapids, Mich. She teaches in the mechanical concentration in the areas of machine dynamics and manufacturing processes. Her master's degree was obtained from the University of Wisconsin, Madison, in manufacturing systems engineering (1987), and her Ph.D. from Michigan State University (1994). Her research interests include philosophy of technology, engineering ethics, and women in engineering.

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Abstract

The Complexities of Engineering Design and System ModelingOne of the many challenges facing the engineering profession and its system of engineeringeducation is the need for effective problem solving and decision making in the midst of theincreasing complexity of contemporary technological systems. Simple observation reveals thatengineered products are becoming more complicated over time. Perhaps more importantly, theinteractions between technological artifacts and the humans and societies who create and usethem, as well as the interactions between the technological artifacts and the living world in whichthey are embedded, are multiplying. Understanding the nature of these interactions is crucial tothe effectiveness of system operation and the reduction of risk.Engineers are currently taught to deal with this complexity by relying on predictions of systembehavior based on the abstract reductionist models of science. These models are typicallydeterministic and rely on modernist approaches to understanding reality. This paper will exploreand categorize some of these engineering modeling approaches. But, the question remainswhether the traditional approaches to system modeling are adequate to address the problems wecurrently face at this point in history, particularly for dealing with the inherent risks of ever morepowerful devices and the demands for development of more sustainable technologies.In order to encourage the development of a more comprehensive approach to modeling whichincludes the contexts in which physical systems are implemented, some engineering educatorshave tried to augment reductive models with consideration of a comprehensive set of designnorms. This paper will present a set of norms, which point to the need for a more expansivetoolbox of modeling approaches to better understand system behavior at multiple levels. Thesenorms address different aspects of the structure of lived reality and therefore attempt to take intoaccount the complexity and the situated-ness of engineered solutions.Finally, the relatively recent development of the inter-disciplinary field of complexity theorysuggests some new strategies for approaching engineering system design. Complexity theoryattempts to describe and model certain classes of systems, particularly biological systems, whichexhibit characteristics such as rich interaction between components, non-equilibrium responses,and emergent behavior. This paper will describe some conceptual modeling approaches ofcomplexity theory for the purpose of identifying new tools or principles for improvingengineering design. Some examples of the application of complexity theory to other disciplines,including homeland security, nursing, and sustainability, will be presented. Finally, somerecommendations will be made as to how to integrate the most useful insights of complexitytheory into the engineering curriculum.

Ermer, G. E. (2012, June), The Complexities of Engineering Design and System Modeling Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--22036

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