Multivariate statistical process control charts for batch monitoring of transesterification reactions for biodiesel production based on near-infrared spectroscopy
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Multivariate statistical process control charts for batch monitoring of transesterification reactions for biodiesel production based on near-infrared spectroscopy
Sales Figueiredo, R.; Vitale, R.; Pimentel, MF.; De Lima, SM.; Stragevitch, L.; Ferrer, A. (2016). Multivariate statistical process control charts for batch monitoring of transesterification reactions for biodiesel production based on near-infrared spectroscopy. Computers & Chemical Engineering. 94:343-353. doi:10.1016/j.compchemeng.2016.08.013
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/102085
Multivariate statistical process control charts for batch monitoring of transesterification reactions for biodiesel production based on near-infrared spectroscopy
[EN] 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 ...[+]
[EN] 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 (batch × spectral variable × time). 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.[-]
info:eu-repo/grantAgreement/MINECO//DPI2014-55276-C5-1-R/ES/BIOLOGIA SINTETICA PARA LA MEJORA EN BIOPRODUCCION: DISEÑO, OPTIMIZACION, MONITORIZACION Y CONTROL/
Thanks:
The authors would like to thank FACEPE/NUQAAPE, CNPq/INCTAA science funding programs for partial financial support. Research fellowships granted by the Brazilian agencies ANP/Petrobras and CNPq are also gratefully acknowledged. ...[+]
The authors would like to thank FACEPE/NUQAAPE, CNPq/INCTAA science funding programs for partial financial support. Research fellowships granted by the Brazilian agencies ANP/Petrobras and CNPq are also gratefully acknowledged. This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI2014-55276-C5-1R and Shell Global Solutions International B.V. (Amsterdam, The Netherlands).[-]