The document addresses fault detection and diagnosis in Continuous Stirred Tank Reactors (CSTRs), highlighting the importance of accurately diagnosing faults to maintain product quality in chemical processes. It discusses various methods for fault diagnosis, particularly using Neural Network Predictive Controllers and Fuzzy Logic Controllers to enhance accuracy and efficiency in real-time operations. The research outlines a mathematical framework for modeling CSTR behavior and emphasizes the role of fuzzy decision-making in managing faults and ensuring operational integrity.