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

作者：Sales Rafaella Figueiredo; Vitale Raffaele; de Lima Suzana Moreira; Pimentel Maria Fernanda^*; Stragevitch Luiz; Ferrer Alberto

来源：Computers & Chemical Engineering, 2016, 94: 343-353.

DOI：10.1016/j.compchemeng.2016.08.013

• Biodiesel
• Batch process monitoring
• Near infrared spectroscopy (NIRS)
• Multivariate statistical process control (MSPC)
• Soybean oil methanolysis

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 x 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.

• 出版日期2016-11-2