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A Comparison of Case-Based Reasoning and Regression Analysis Approaches for Cost Uncertainty Modeling

[+] Author Affiliations
Karan Banga, Shun Takai

Missouri University of Science and Technology, Rolla, MO

Paper No. DETC2010-28232, pp. 213-222; 10 pages
  • ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 6: 15th Design for Manufacturing and the Lifecycle Conference; 7th Symposium on International Design and Design Education
  • Montreal, Quebec, Canada, August 15–18, 2010
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4414-4 | eISBN: 978-0-7918-3881-5
  • Copyright © 2010 by ASME


This paper presents cost uncertainty modeling for a concept selection using case-based reasoning (CBR) and compares this method with the regression analysis approach. During the product development stage, a number of decisions must be made under uncertainty, including selection of an ideal product concept. The cost of a concept, i.e., the cost of the final product developed from a concept, is a key factor influencing the choice of an ideal concept. The CBR approach creates a knowledge base (or database) containing past cases, defines a new case, retrieves cases similar to the new case, and adapts the solution of the retrieved cases to the new case. This paper illustrates the proposed approach using automobiles as an example.

Copyright © 2010 by ASME



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