The research behind Process Chemometrics Lab @ GEPSI –CIEPQPF



Integration of Engineering Process Control and Statistical Process Control

Process monitoring methodologies are centred on improving the sensitivity to process upsets, but lack an adequate approach on how to handle the corrective actions when special events are signalled. It turns out that in many instances there are means available to do much more for assisting processes operators than just sending an alarm to the control room about a potential faulty operation state, namely, suggesting lines of action on how to handle it properly. However, for such to be achieved, statistical process control (SPC) monitoring and engineering process control (EPC), traditionally considered rather separate and isolated tasks, have to be coherently combined. We address the proper integration of advanced multivariate monitoring approaches, such as MS-MSPC, with advanced multivariate optimal control schemes, such as Model Predictive Control (MPC). MPC is the state-of-the-art approach for conducting higher level control activities, when a model is available about the process. It has been applied with success to many processes of both operational and economical importance (Qin & Badgwell, 2003), and therefore, is a serious candidate to consider in this situation. Several integration structures are under study.