Abstract Self-supervised learning has demonstrated state-of-the-art performance on various anomaly detection tasks. Learning effective representations by solving a supervised pretext task with pseudo-labels generated from unlabeled data provides promising concept for industrial downstream tasks such as process monitoring. In this paper, we present SSMSPC novel approach multivariate statistical ...