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Abstract:The application of metamodel techniques greatly reduces the computational cost in robust design. However, metamodel is only an approximation of the original model resulting in metamodel uncertainty. In the traditional robust design, only parameter uncertainty is considered rather than metamodel uncertainty, which may induce design error. To address this issue, a method based on Monte Carlo sampling is proposed to quantify the metamodel uncertainty in robust design. With the proposeddoi:10.3901/jme.2014.19.136 fatcat:bjzfkguurffyxowxs465yk33u4