Abstract: The Function Impact Method (FIM) is a semi-quantitative eco-design methodology that is targeted specifically towards the early stages of the design process. The FIM allows a designer to predict the environmental impacts associated with a new functional embodiment by extrapolating knowledge from Life cycle assessment (LCA) of similar existing designs. LCA however, is associated with substantial sources of uncertainty. Furthermore, the FIM uses a subjective weighting scheme for representing function-structure affinities. In the authors’ previous work, a Monte-Carlo variation analysis was used to estimate sensitivity of the input data and select the preferred redesign strategy. This paper proposes a method to formalize the input uncertainties in the FIM by modeling the uncertainties present in the results of the LCA’s and the involved function-structure affinities using Info-gap decision theory. The desirability of redesigning a particular function based on the magnitude of its function-connectivity and eco-impact is estimated, and a decision making methodology based on robust satisficing is discussed. This method is applied for making robust redesign decisions with regards to re-designing a pneumatic impact wrench for sustainability.
Addressing Uncertainties within Product Redesign for Sustainability: A Function Based Framework
Authors: Devarajan Ramanujan, William Z Bernstein, Fu Zhao, Karthik Ramani
Proceedings of the ASME 2011 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference IDETC/CIE 2011, August 28-31, 2011, Washington, DC, USA
Dev Ramanujan
Dev is starting as an Assistant Professor - Design Research at Aarhus University this in Fall 2017. He was a Postdoctoral Associate in the Global Engineering and Research Lab at the Massachusetts Institute of Technology from Feb 2016 - June 2017. He received his PhD in Dec 2015 from the School of Mechanical Engineering at Purdue. His research work in the C Design Lab focused on data representation and visualization models for supporting environmentally conscious product design. He has co-authored publications in the Journal of Mechanical Design, Journal of Computing and Information Science, Computer-Aided Design, Association for Computing Machinery Conference on Human Factors in Computing Systems, and the American Society of Mechanical Engineering International Design Engineering Technical Conferences. He has received the American Society of Mechanical Engineering Design for Manufacturing and the Lifecycle Scholar Development Award in 2014, and the Estus H. and Vashti L. Magoon Award for Teaching Excellence in 2015.
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