A robust suspension system design optimization, which takes into account the kinematic behaviours influenced by bush compliance uncertainty, is presented. The design variables are the positions of the joints, and the random constant is the bush stiffness with uncertainty. The design goals for these kinematic behaviours are typically represented as deviations over the wheel movements. It can be very difficult to evaluate the analytical design sensitivity because the deviation is defined by using the maximum and minimum values over the parameter interval. To avoid the difficulty, this study introduces a metamodel technique. The sample variances for the design goals are approximated from metamodels. In addition, a sequential approximation optimization technique is used to solve a robust design problem for the suspension system. The robust design problem has 18 design variables and 18 random constants with uncertainty. The proposed approach required only 189 evaluations until it converged. The selected design reduced the maximum deviations in the toe and camber angles by 72 per cent and 50 per cent respectively, and their variances by 90 per cent, while satisfying the constraints of changes in the toe angle, camber angle, and front-to-rear change in the wheel centre.

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