Equipment Failure and Anomaly Detection Deep Learning

I've been tasked with creating a Deep Learning Model to take timeseries data and predict X days out in the future when equipment is going to fail/have issues. From my research I found using a Semi-Supervised approach using GANs and BiGANs. Does anyone have any experience doing this or know of research material I can review? I'm worried about equipment configuration changing and having a limited amount of events.

anomaly anomaly detection data datascience deep learning detection equipment experience failure found future gans material research semi-supervised timeseries