Process Insight

Process insight focuses on extracting meaningful information from process data to understand, optimize, and predict system behavior. Current research emphasizes data-driven approaches, employing machine learning techniques like Gaussian processes, Polynomial Chaos Expansion, and recurrent neural networks, alongside process mining methods to analyze diverse data types, including continuous features and event logs. These advancements enable improved process design, anomaly detection, and predictive modeling across various domains, from manufacturing and chemical engineering to healthcare and cybersecurity, ultimately leading to enhanced efficiency and resource utilization.