Abstract
Batch processes are commonly characterized by uneven trajectories due to the existence of batch-to-batch variations. The batch end-product quality is usually measured at the end of these uneven trajectories. It is necessary to align the time differences for both the measured trajectories and the batch end-product quality in order to implement statistical process monitoring and control schemes. Apart from synchronizing trajectories with variable lengths using an indicator variable or dynamic time warping, this paper proposes a novel approach to align uneven batch data by identifying short-window PCA&PLS models at first and then applying these identified models to extend shorter trajectories and predict future batch end-product quality. Furthermore, uneven batch data can also be aligned to be a specified batch length using moving window estimation. The proposed approach and its application to the control of batch end-product quality are demonstrated with a simulated example of fed-batch fermentation for penicillin production.
DOI
10.1016/j.isatra.2013.12.020
Publication Date
2014-01-01
Publication Title
ISA Transactions
Volume
53
Publisher
Elsevier BV
ISSN
0019-0578
Embargo Period
2024-11-22
First Page
584 - 590
Last Page
584 - 590
Recommended Citation
Wan, J., Marjanovic, O., & Lennox, B. (2014) 'Uneven batch data alignment with application to the control of batch end-product quality', ISA Transactions, 53, pp. 584 - 590-584 - 590. Elsevier BV: Available at: https://doi.org/10.1016/j.isatra.2013.12.020
Comments
keywords: Variable batch lengths keywords: Variable batch lengths keywords: Variable batch lengths keywords: Variable batch lengths keywords: Variable batch lengths