Abstract
Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example.
Original language | English (US) |
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Pages (from-to) | 145-153 |
Number of pages | 9 |
Journal | Reliability Engineering and System Safety |
Volume | 138 |
DOIs | |
State | Published - Jun 2015 |
Keywords
- Kriging metamodel
- Robust design
- Sequential optimization and reliability assessment Sequential sampling
- optimization
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Industrial and Manufacturing Engineering