Tack, TimTimTackMaier, AlexanderAlexanderMaierNiggemann, OliverOliverNiggemann2022-03-122022-03-122014https://publica.fraunhofer.de/handle/publica/38667210.1007/978-3-319-03500-0_2This chapter introduces methods from the field of visual analytics and machine learning which are able to handle high feature dimensions, timed systems and hybrid systems, i.e. systems comprising both discrete and continuous signals. Further, a three steps tool chain is introduced which guides the operator from the visualization of the normal behavior to the anomaly detection and also to the localization of faulty modules in production plants.enanomaly detectionproduction plantautomation systemVisual analyticsvisualization technique004670conference paper