Fault detection in batch processes through variable selection integrated to multiway principal component analysis

•Limitations of batch process monitoring for high dimensional datasets are analyzed.•An offline fault detection method for batch processes is proposed.•Selected variables are the ones that improve batch classification accuracy.•A real dataset from a chocolate conching batch operation is analyzed.•The proposed PVS-MPCA method promoted a 85% reduction in false alarm rate.