Development of Advanced Process Monitoring and Fault Detection Techniques for Specialty Chemicals

Thesis Abstract

This project aims to develop advanced process monitoring and fault detection techniques specifically tailored for the production of specialty chemicals. Specialty chemicals often require precise control and monitoring due to their complex synthesis pathways and stringent quality requirements. The project will focus on the application of advanced data analytics, machine learning, and statistical methods to develop real-time monitoring and fault detection systems for specialty chemical processes. The resulting techniques will enable early detection of process deviations, equipment failures, and quality variations, thereby enhancing process reliability and product consistency in the specialty chemical industry.