Journal article
Integration of Possibility-Based Optimization and Robust Design for Epistemic Uncertainty
Journal of mechanical design (1990), Vol.129(8), pp.876-882
08/01/2007
DOI: 10.1115/1.2717232
Abstract
In practical engineering applications, there exist two different types of uncertainties: aleatory and epistemic uncertainties. This study attempts to develop a robust design optimization with epistemic uncertainty. For epistemic uncertainties, a possibility-based design optimization improves the failure rate, while a robust design optimization minimizes the product quality loss. In general, product quality loss is described using the first two statistical moments for aleatory uncertainty: mean and standard deviation. However, there is no metric for product quality loss defined when having epistemic uncertainty. This paper first proposes a new metric for product quality loss with epistemic uncertainty, and then a possibility-based robust design optimization. For numerical efficiency and stability, an enriched performance measure approach is employed for possibility-based robust design optimization, and the maximal possibility search is used for a possibility analysis. Three different types of robust objectives are considered for possibility-based robust design optimization: smaller-the-better type (S-Type), larger-the-better type (L-Type), and nominal-the-better type (N-Type). Examples are used to demonstrate the effectiveness of possibility-based robust design optimization using the proposed metric for product quality loss with epistemic uncertainty.
Details
- Title: Subtitle
- Integration of Possibility-Based Optimization and Robust Design for Epistemic Uncertainty
- Creators
- Byeng D Youn - Department of Mechanical Engineering and Engineering Mechanics, Michigan Technological University, Houghton, MI 49931Kyung K Choi - Department of Mechanical & Industrial Engineering, College of Engineering, The University of Iowa, Iowa City, IA 52242Liu Du - Department of Mechanical & Industrial Engineering, College of Engineering, The University of Iowa, Iowa City, IA 52242David Gorsich - AMSTA-TR-N (MS 263), U.S. Army National Automotive Center, Warren, MI 48397
- Resource Type
- Journal article
- Publication Details
- Journal of mechanical design (1990), Vol.129(8), pp.876-882
- Publisher
- ASME
- DOI
- 10.1115/1.2717232
- ISSN
- 1050-0472
- eISSN
- 1528-9001
- Language
- English
- Date published
- 08/01/2007
- Academic Unit
- Mechanical Engineering
- Record Identifier
- 9984064592602771
Metrics
15 Record Views