Anomaly Detection for Injection Molding Using Probabilistic Deep Learning

Data collection from industrial devices is becoming more popular with the advent of technologies and trends such as the Industrial Internet of Things (IIoT) and Industry 4.0. We propose a deep learning-based approach to detect anomalies in real-time from multivariate time series data and interpret the detected anomalies' root causes. We apply the method to real-world industrial data collected from...