In some industrial situations, the classical assumption used in the batch process monitoring that all batches have equal durations and are synchronized does not hold. A batch process is carried out in sequential phases and a significant variability generally occurs in the duration of the phases such that events signifying the beginning or the end of a phase are generally misaligned in time within the various batches. The consequence is that the variable trajectories, in the different runs of the same batch process, are unsynchronized. In this case, data analysis from process for performing the multivariate statistical process control can be difficult. In this paper, we propose several innovative methods for the off-line and on-line monitoring of batch processes with varying durations, all based on the Hausdorff distance. These methods have been successfully tested on a simulated example and on an industrial case example. The conclusion is that these methods are able to efficiently discriminate between nominal and non-nominal batches.