Batch/semi-batch quality control has attracted much attention from chemical engineering researchers recently. In this work, a novel empirical model based quality control approach for batch processes is developed. The model implemented is based on independent nonlinear principal components obtained by means of principal surface analysis- a very hot topic in the area of statistical modeling. The partial initial conditions and intermediate measurements obtained from each batch are analyzed using this approach to extract the independent nonlinear principal components. An empirical model with the nonlinear principal components as inputs is built to predict product quality. Correcting actions based on the initial conditions and intermediate measurements are taken based on the predictions obtained using the empirical model. In this work, the problem formulation and solution method are presented. The illustrative examples include a simulation example and an experimental study on the batch reactive distillation process. The simulation and experimental results show that the proposed approach is highly promising.