A Decision-Analytic Concept Selection for a Commercial System Using Objective Data to Model Uncertainty
This paper presents decision-analytic concept selection framework for a commercial system and an uncertainty modeling using objective data. The selection of a system concept for which a final system is designed and manufactured is a decision making process with incomplete information. Decision analysis is a prescriptive approach for decision making under uncertainty. While realizing that humans make decisions violating the expected utility axioms, decision analysis uses a set of tools to guide a decision maker toward an unbiased and rational decision making. The objective of this research is to propose a decision-analytic framework for commercial system concept selection, and an approach to utilize as much objective data as possible in the uncertainty modeling. Toward this objective, this paper construct cost distribution using case-based reasoning and market share distribution applying bootstrap to customers' preference data obtained from conjoint analysis. The proposed approach is demonstrated in an illustrative example: a decision-analytic automobile concept selection. Copyright © 2009 by ASME.
S. Takai et al., "A Decision-Analytic Concept Selection for a Commercial System Using Objective Data to Model Uncertainty," Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference 2009, DETC2009, American Society of Mechanical Engineers (ASME), Jan 2010.
The definitive version is available at http://dx.doi.org/10.1115/DETC2009-86771
2009 ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, DETC2009
Mechanical and Aerospace Engineering
Keywords and Phrases
Bootstrap; Case-Based Reasoning; Clustering; Concept Selection; Conjoint Analysis; Decision Analysis
Article - Conference proceedings
© 2010 American Society of Mechanical Engineers (ASME), All rights reserved.