The concept of robust design involves identification of design settings that make the product performance less sensitive to the effects of seasonal and environmental variations. Batch processes are more flexible compared to continuous processes and are frequently used in these situations. Stochastic optimization methods provide a general approach to robust/parameter design as compared to conventional techniques. However, the computational burden of these approaches can be extreme and depends on the sample size used for characterizing the parametric variations and uncertainties. In this paper, we present a novel sampling technique. The example of robust batch distillation column design illustrates that the new sampling technique offers significant computational savings and better accuracy.