A new method is introduced for optimally designing multiproduct batch plants under the single-product campaign (SPC) production mode. Uncertain future product demands are described with normal probability distributions, and more than one processing unit of equal size are allowed per stage. A t the expense of imposing the normality assumption for product demand uncertainty and the SPC production mode, the original two-stage stochastic optimization problem is transformed into a deterministic mixed-integer nonlinear programming problem without relying on implicit or explicit discretization of the uncertain variables. This is accomplished through the explicit solution of the inner problem and the analytical integration overall product demand realizations. This problem representation and solution strategy result in savings of orders of magnitude over existing methods in computational requirements.