The complexities of engineering design and system modeling

Abstract

One of the many challenges facing the engineering profession and its system of engineering education is the need for effective problem solving and decision making in the midst of the increasing complexity of contemporary technological systems. Simple observation reveals that engineered products are becoming more complicated over time. Perhaps more importantly, the interactions between technological artifacts and the humans and societies who create and use them, as well as the interactions between the technological artifacts and the living world in which they are embedded, are multiplying. Understanding the nature of these interactions is crucial to the effectiveness of system operation and the reduction of risk. Engineers are currently taught to deal with this complexity by relying on predictions of system behavior based on the abstract reductionist models of science. These models are typically deterministic and rely on modernist approaches to understanding reality. This paper will explore and categorize some of these engineering modeling approaches. Also, in order to encourage the development of a more comprehensive approach to modeling which includes the contexts in which physical systems are implemented, some engineering educators have tried to augment reductive models with consideration of a comprehensive set of design norms. This paper will present a set of norms that point to the need for a more expansive toolbox of modeling approaches to better understand system behavior at multiple levels. These norms address different aspects of the structure of lived reality and therefore attempt to take into account the complexity and the situated-ness of engineered solutions. Finally, the relatively recent development of the inter-disciplinary field of complexity theory suggests some new strategies for approaching engineering system design. Complexity theory attempts to describe and model certain classes of systems, particularly biological systems, which exhibit characteristics such as rich interaction between components, non-equilibrium responses, and emergent behavior. This paper will describe some conceptual modeling approaches to dealing with complexity for the purpose of identifying new tools or principles for improving engineering design. Finally, some recommendations will be made as to how to integrate the most useful insights of complexity theory into the engineering curriculum. © 2012 American Society for Engineering Education.