The goal of robust design optimisation is to improve the quality of a product or process by minimising the deteriorating effects of variable or uncertain parameters. This robustness can be achieved by different approaches using formulations of statistical decision theory which all require many function evaluations throughout the optimisation. In cases where no closed-form descriptions of the objective are available and pointwise solutions are expensive to evaluate, metamodelling techniques based on design of experiments are used to replace the actual numerical analysis codes. In this paper we propose a method to sequentially augment the significance of spatial correlation metamodels for robust design optimisation through additional sampling.     «

The goal of robust design optimisation is to improve the quality of a product or process by minimising the deteriorating effects of variable or uncertain parameters. This robustness can be achieved by different approaches using formulations of statistical decision theory which all require many function evaluations throughout the optimisation. In cases where no closed-form descriptions of the objective are available and pointwise solutions are expensive to evaluate, metamodelling techniques based...     »