Multivariate monitoring of batch processes using batch-to-batch information
β Scribed by Jesus Flores-Cerrillo; John F. MacGregor
- Publisher
- American Institute of Chemical Engineers
- Year
- 2004
- Tongue
- English
- Weight
- 212 KB
- Volume
- 50
- Category
- Article
- ISSN
- 0001-1541
No coin nor oath required. For personal study only.
β¦ Synopsis
Abstract
Multiway principal component analysis (MPCA) and multiway partialβleast squares (MPLS) are wellβestablished methods for the analysis of historical data from batch processes, and for monitoring the progress of new batches. Direct measurements made on prior batches can also be incorporated into the analysis by monitoring with multiblock methods. An extension of the multiblock MPCA/MPLS approach is introduced to explicitly incorporate batchβtoβbatch trajectory information summarized by the scores of previous batches, while keeping all the advantages and monitoring statistics of the traditional MPCA/MPLS. However, it is shown that the advantages of using information on prior batches for analysis and monitoring are often small. Its main advantage is that it can be useful for detecting problems when monitoring new batches in the early stages of their operation., the approach and benefits are illustrated with condensation polymerization and emulsion polymerization systems, as examples. Β© 2004 American Institute of Chemical Engineers AIChE J, 50: 1219β1228, 2004
π SIMILAR VOLUMES
## Abstract The development of a stateβspace framework for monitoring batch processes that can complement the existing multivariate monitoring methods is presented. A subspace identification method will be used to extract the dynamic and batchβtoβbatch trends of the process and quality variables fr