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While CAE methods allow improving nominal product design using virtual prototypes, uncertainty and variability in properties and manufacturing processes lead to scatter in actual performances. Uncertainty must hence be incorporated in the CAE process to guarantee the robustness and reliability of the design. This paper presents an overview of uncertainty-based design in automotive and aerospace engineering. Fuzzy methods take uncertainty into account, whereas reliability analysis and a reliability-based design optimization framework can deal with variability. Key enabling technologies to alleviate the computational burden, such as workflow automation, substructuring and design of experiments, are discussed, and industrial applications are presented.