Control Charts and Machine Learning for Anomaly Detection in Manufacturing

Chapter 1 Introduction to Control Charts and Machine Learning for Anomaly Detection in Manufacturing

Chapter 3 Control Charts for Monitoring Time-Between-Events-and-Amplitude Data

Chapter 4 Monitoring a BAR(1) Process with EWMA and DEWMA Control Charts

Chapter 5 On Approaches for Monitoring Categorical Event Series

Chapter 7 A Review of Tree-Based Approaches for Anomaly Detection

Chapter 8 Joint Use of Skip Connections and Synthetic Corruption for Anomaly Detection with Autoencoders

Chapter 9 A Comparative Study of $$\text {L}_1$$ L 1 and $$\text {L}_2$$ L 2 Norms in Support Vector Data Descriptions

Chapter 10 Feature Engineering and Health Indicator Construction for Fault Detection and Diagnostic