Abstract
To solve the product robust design problems involving a mixture of random and interval factors, a novel approach is proposed which combines an integrated metamodeling method with a percentile-based robust optimization model. The integrated metamodeling method embodies the integration of Response Surface Methodology (RSM) and Support Vector Regression (SVR), which is used to construct the metamodels of product performance efficiently. The percentile-based robust optimization model could bring both the design objective robustness and the feasibility robustness of the design constraint into account, which assures a product’s reliability and quality robustness to the noise. A case study of a diaphragm spring in automobile clutch is described to how the effectiveness and practicability of the proposed approach.
This project is supported by Chinese National Natural High-Tech. R&D Program for CIMS under Grant No. 2002AA413520 and National Fundamental Research Program (973) under Grant No. 2003CB716207.
Chapter PDF
Similar content being viewed by others
Key words
5. References
M. S. Phadke, Quality Engineering Using Robust Design (Prentice Hall, New Jersey, 1989).
W. Chen, J. K. Allen, F. Mistree, and K. L. Tsui, A procedure for robust design, ASME Journal of Mechanical Design 118(4), 478–485 (1996).
X. Du, A. Sudjianto, and B. Huang, Reliability-based design under the mixture of random and interval variables, ASME Journal of Mechanical Design 127(6), 1068–1076 (2005).
R. H. Myers, and D. C. Montgomery, Response Surface Methodology: Process and Product Optimization Using Designed Experiments (John Wiley and Sons, New York, 1995).
N. Cristianni, and J. Shawe-Taylor, An introduction to support vector machines and other kernel-based learning methods (Cambridge University Press, Cambridge, 2000).
M. Zeleny, Compromise programming, in Multiple Criteria Decision Making (University of South Carolina Press, Columbia, 1973).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 International Federation for Information Processing
About this paper
Cite this paper
Liu, C., Lin, Z. (2006). Product Robust Design with a Mixture of Random and Interval Factors. In: Wang, K., Kovacs, G.L., Wozny, M., Fang, M. (eds) Knowledge Enterprise: Intelligent Strategies in Product Design, Manufacturing, and Management. PROLAMAT 2006. IFIP International Federation for Information Processing, vol 207. Springer, Boston, MA . https://doi.org/10.1007/0-387-34403-9_26
Download citation
DOI: https://doi.org/10.1007/0-387-34403-9_26
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-34402-7
Online ISBN: 978-0-387-34403-4
eBook Packages: Computer ScienceComputer Science (R0)