The application of dynamic time warping (DTW) to the analysis and moni
toring of batch processes is presented. This dynamic-programming-based
technique has been used in the area of speech recognition for the rec
ognition of isolated and connected words. DTW has the ability to synch
ronize two trajectories by appropriately translating expanding, and co
ntracting localized segments within both trajectories to achieve a min
imum distance between the trajectories. Batch processes often are char
acterized by unsynchronized trajectories, due to the presence of batch
-to-batch disturbances and the existence of physical constraints. To c
ompare these batch histories and apply statistical analysis one needs
to reconcile the timing differences among these trajectories. This can
be achieved using DTW with only a minimal amount of process knowledge
. The combination of DTW and a monitoring method based on Multiway PCA
/PLS is used for both off-line and on-line implementation. Data from a
n industrial polymerization reactor are used to illustrate the impleme
ntation and the performance of this method.