This course provides an introduction to general strategies that can be used to monitor the performance of complex processes and their automatic control systems. Process monitoring is concerned with two broad issues (i) Is the current process operation normal or abnormal (fault detection)? (ii) If the performance is considered to be abnormal, what is the root cause (fault diagnosis)? Control system monitoring is concerned with similar issues but different monitoring strategies and methods of analysis are employed. Both model-based and data-driven monitoring strategies are considered. Emphasis is placed on statistically-based techniques that can be used to analyze multivariate time-series data.

This course provides an introduction to general strategies that can be used to monitor the performance of complex processes and their automatic control systems. Process monitoring is concerned with two broad issues (i) Is the current process operation normal or abnormal (fault detection)? (ii) If the performance is considered to be abnormal, what is the root cause (fault diagnosis)? Control system monitoring is concerned with similar issues but different monitoring strategies and methods of analysis are employed. Both model-based and data-driven monitoring strategies are considered. Emphasis is placed on statistically-based techniques that can be used to analyze multivariate time-series data.