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BioProcess performance monitoring using multiway interval partial least squares

Lookup NU author(s): Shallon Stubbs, Dr Jie Zhang

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Abstract

© 2018 Elsevier B.V. The method of interval Partial Least Squares (iPLS) is combined with multiway partial least squares (MPLS) to allow the building of enhanced statistical process performance-monitoring models. A novel algorithm is proposed for segmenting batch duration, or spectral data, in applications employing spectroscopy data, into several subintervals for which independent PLS models can be constructed. The approach deviates from the method of using subintervals of equal length and the practice of choosing only a subset of these subintervals for prediction and/or monitoring. The proposed approach provides dramatic reduction in the number of subintervals required and subsequently the number of PLS models required to give improved prediction and monitoring performance. The proposed method is applied to the well-known benchmark fed-batch penicillin production simulator, Pensim, for quality variable prediction and fault detection.


Publication metadata

Author(s): Stubbs S, Zhang J, Morris J

Publication type: Book Chapter

Publication status: Published

Book Title: Computer Aided Chemical Engineering

Year: 2018

Volume: 41

Pages: 243-259

Online publication date: 16/03/2018

Acceptance date: 02/04/2016

Publisher: Elsevier BV

URL: https://doi.org/10.1016/B978-0-444-63963-9.00010-5

DOI: 10.1016/B978-0-444-63963-9.00010-5

Library holdings: Search Newcastle University Library for this item

ISBN: 9780444639639


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