Journal of Mechanical Science and Technology

The Korean Society of Mechanical Engineers (대한기계학회)
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A Robust Optimization Using the Statistics Based on Kriging Metamodel

  • Lee Kwon-Hee (Department of Mechanical Engineering, Dong-A University) ;
  • Kang Dong-Heon (Department of Mechanical Engineering, Dong-A University)
  • Published : 2006.08.01
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Abstract

Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

Keywords

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