In this monograph we have sought to provide an introduction to automatic analysis and interpretation of process operational data both in real time and over the operating history. Methods are developed for designing intelligent, state space based systems for process monitoring, control and diagnosis. Such a system is able to identify known and new operational states, either normal or abnormal and project the operation of the process to a single point of the operational state space by simultaneously considering all measurements and giving causal explanations to operators and plant managers. The techniques have also proved useful in discovering operational states for product design. In developing the methods, we have attempted to address the point that plant operators and supervisors are part of the overall control system responsible for data interpretation and critical decision making, and therefore should be integrated into control systems in a way to provide them with necessary computer based, automatic processing tools.