Multivariate statistical process control charts for batch monitoring of transesterification reactions for biodiesel production based on near-infrared spectroscopy

[Display omitted] •Transesterification reactions monitored using in-line NIR spectroscopy.•Multivariate control charts for batch monitoring developed using spectroscopy data.•Control charts constructed based on two techniques: NM and WKFH.•Monitoring schemes applied for off- and on-line fault detect...

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Bibliographic Details
Published in:Computers & chemical engineering 2016-11, Vol.94, p.343-353
Main Authors: Sales, Rafaella Figueiredo, Vitale, Raffaele, de Lima, Suzana Moreira, Pimentel, Maria Fernanda, Stragevitch, Luiz, Ferrer, Alberto
Format: Article
Language:English
Subjects:
Arrays
Batch process monitoring
Biodiesel
Failure
Monitoring
Monitors
Multivariate statistical process control (MSPC)
Near infrared radiation
Near infrared spectroscopy (NIRS)
Soybean oil methanolysis
Spectra
Statistical process control
Transesterification
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Summary:[Display omitted] •Transesterification reactions monitored using in-line NIR spectroscopy.•Multivariate control charts for batch monitoring developed using spectroscopy data.•Control charts constructed based on two techniques: NM and WKFH.•Monitoring schemes applied for off- and on-line fault detection. This work describes an application of Multivariate Statistical Process Control to monitor soybean oil transesterification. For the development of multivariate control charts, near infrared spectra were acquired in-line during the evolution of ten batches under Normal Operating Conditions. They were then organized in a three-way array (batchíspectral variableítime). This structure was analysed by the two most commonly used approaches to develop batch monitoring schemes for handling such kind of data, referred to as Nomikos-MacGregor (NM) and Wold-Kettaneh-Friden-Holmberg (WKFH), respectively. To assess the performance of the approaches, eight test batches, during which specific interferences were induced, were manufactured. When applied for off-line monitoring, both NM and WKFH correctly pointed out such intentionally produced failures. On the other hand, concerning on-line monitoring, NM exhibited a better fault detection capability than WKFH. Contribution plots were found to highlight the spectral region mostly affected by the disturbances regardless of the modelling strategy resorted to.
ISSN:0098-1354
1873-4375
DOI:10.1016/j.compchemeng.2016.08.013