A Comparison of Case-Based Reasoning and Regression Analysis Approaches for Cost Uncertainty Modeling
Abstract
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.
Recommended Citation
K. Banga and S. Takai, "A Comparison of Case-Based Reasoning and Regression Analysis Approaches for Cost Uncertainty Modeling," Proceedings of the ASME Design Engineering Technical Conference, American Society of Mechanical Engineers (ASME), Jan 2010.
The definitive version is available at https://doi.org/10.1115/DETC2010-28232
Meeting Name
ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC/CIE2010
Department(s)
Mechanical and Aerospace Engineering
Keywords and Phrases
Case-Based Reasoning; Clustering; Concept; Cost; Distribution
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2010 American Society of Mechanical Engineers (ASME), All rights reserved.
Publication Date
01 Jan 2010
