Batch process monitoring using an assumption-free modeling methodology

An assumption-free model is developed for the monitoring of batch processes. The model is based on variable-wise unfolded multy-way principal component analysis (MPCA) and avoids the problem of batch alignment, which is necessary in the case of a batch-wise unfolded MPCA. The assumption-free model and a model based on batch-wise unfolded MPCA are developed and tested on different batch processes datasets in order to evaluate their performances on process monitoring and fault detection.