Presentation: Using the PI System to Support Prediction and Advanced Control of Reel to Reel Paper Quality

PI Server data is used to support Multivariate (MV) methods for characterizing process variations and monitoring statistical process control (SPC). These modeling methods can also be used for predictive purposes to estimate future trajectories of important process parameters or final conditions of batch type processes. Control of batch type systems is often performed at two levels consisting of maintaining important process parameters along a desired trajectory and a higher level of supervisory control to determine the best trajectory for these variables in order to optimize the final batch quality. Paper machines are run as a continuous process yet quality is determined for each reel. Considering each reel as a batch, batch modeling methods can be applied. In this session a hierarchical approach using latent variable methods (PCA/PLS) is presented to provide these two levels of control and applied to a continuously operated paper machine. The opportunity for using contemporary PI Clients to parse data into event frames will be discussed.