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Applying Information Economics and Imprecise Probabilities to Data Collection in Design

[+] Author Affiliations
Jason Matthew Aughenbaugh, Jay Ling, Christian J. J. Paredis

Georgia Institute of Technology

Paper No. IMECE2005-81181, pp. 81-94; 14 pages
doi:10.1115/IMECE2005-81181
From:
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Computers and Information in Engineering
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Computers and Information in Engineering Division
  • ISBN: 0-7918-4214-2 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME

abstract

One important aspect of the engineering design process is the sequence of design decisions, each consisting of a formulation phase and a solution phase. As part of the decision formulation, engineers must decide what information to use to support the decision. Since information comes at a cost, a cost-benefit trade-off must be made. Previous work has considered these trade-offs in cases in which all relevant probability distributions were precisely known. However, engineers frequently must estimate these distributions by gathering sample data during the information collection phase of the decision process. In this paper, we introduce principles of information economics to guide decisions on information collection. We present a method that enables designers to bound the value of information in the case of unknown distributions by using imprecise probabilities to characterize the current state of information. We illustrate this method with an example material strength characterization for a pressure vessel design problem, in which we explore the basic performance, subtleties, and limitations of the method.

Copyright © 2005 by ASME

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