A PLS-based multirate dynamic modeling is proposed for quality prediction at a faster rate for multivariable processes with di6erent sampling rates between the process and quality variables. Depending on the nature of the process and quality variables, two model representations are proposed, one-block form for the process with closed-loop quality control, and two-block form for the process without the closed-loop quality control. The applications of the proposed models are compared with respect to two processes, a three-stage absorber and the TE process. The ability of the proposed model to predict quality at a faster rate is demonstrated with the complex TE process.

A stage-based quality control scheme, which combines an online adjustment strategy with the authors’ previous works on stage partial least squares(PLS) modeling and quality prediction, is developed for within-batch control of end-product quality for batch processes. Considering the inherent time-specific nature of process trajectories to the end-product quality, a critical-to-quality-control stage is introduced for quality control and stability improvement, together with guidelines on the manipulating variable selection and no-control region. The effectiveness and feasibility of the proposed scheme are illustrated on an injection molding process.

This paper extends the stage-based sub-PCA modeling method originally proposed by the authors to the monitoring of batch processes with durations of uneven lengths. Two models for each stage are developed, one for the stage division and the other for process monitoring. The purposes of the stage division are two-fold, to enhance process understanding and to provide stage-division information necessary for the development of PCA monitoring models. With the proposed method, batch processes with durations of uneven lengths can be effectively monitored for fault detection and diagnosis.