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Modeling Evolution of Uncertainty in Sustainable Product Design

[+] Author Affiliations
Hamid Afshari, Qingjin Peng

University of Manitoba, Winnipeg, MB, Canada

Paper No. DETC2014-34317, pp. V004T06A052; 11 pages
  • ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 4: 19th Design for Manufacturing and the Life Cycle Conference; 8th International Conference on Micro- and Nanosystems
  • Buffalo, New York, USA, August 17–20, 2014
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-4635-3
  • Copyright © 2014 by ASME


Although a large number of research activities have been conducted for sustainable product development, it is not easy to find a practical method applied in sustainable product design as there are many uncertain factors existed in particular problems faced in different phases of product development. Based on reviewed literature, it is found that it is necessary to have an optimization metric accompanied with uncertainty effects in product development. A model is proposed in this research to evaluate the effects of uncertainty in product life cycle. The goal is to quantify various types of uncertainty from internal and external sources to assess the design efficiency for mitigating undesirable effects of uncertainty. The design phase is aimed in the research to look at product parameters that are subject to change in the design process. Inaccuracy, indecision and imprecision are selected as information uncertainty levels to quantify the evolution of uncertainty. Using the proposed concept, the discrete-event simulation (DES) is used to model and evaluate scenarios to minimize design phase duration of a sustainable wheelchair. Suggested improvements are compared to search the optimal solution. The analysis and comparison of scenarios show ways to reduce design time by (1) revision of the design process, (2) breaking down the product into design details, and (3) providing a clear and technical definition of uncertainty to be mitigated. The model is also used to locate areas for sustainability improvement in the studied case.

Copyright © 2014 by ASME



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