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http://dx.doi.org/10.3795/KSME-A.2005.29.9.1243

A Global Robust Optimization Using the Kriging Based Approximation Model  

Park Gyung-Jin (한양대학교 공과대학 기계공학과)
Lee Kwon-Hee (동아대학교 공과대학 기계공학과)
Publication Information
Transactions of the Korean Society of Mechanical Engineers A / v.29, no.9, 2005 , pp. 1243-1252 More about this Journal
Abstract
A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.
Keywords
Robust Design; Kriging; Uncertainties; Global Robust Optimization; Simulated Annealing Algorithm; DACE(Design and Analysis of computer Experiments);
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Times Cited By KSCI : 3  (Citation Analysis)
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