Volume 53
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Zhao, J., Li, W., Qu, H., Tian, G., & Wei, Y. (2020). Real-time monitoring and fault detection of pulsed-spray fluid-bed granulation using near-infrared spectroscopy and multivariate process trajectories. Particuology, 53, 112-123. https://doi.org/10.1016/j.partic.2020.02.003
Real-time monitoring and fault detection of pulsed-spray fluid-bed granulation using near-infrared spectroscopy and multivariate process trajectories
Jie Zhao a, Wenlong Li a, Haibin Qu a *, Geng Tian b, Yanding Wei b *
a Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China
b Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province, College of Mechanical Engineering, Zhejiang University, Hangzhou 310027, China
10.1016/j.partic.2020.02.003
Volume 53, December 2020, Pages 112-123
Received 25 October 2018, Revised 19 January 2020, Accepted 4 February 2020, Available online 23 April 2020, Version of Record 16 December 2020.
E-mail: quhb@zju.edu.cn; weiyd@zju.edu.cn

Highlights

• Monitoring and fault diagnosis in pulsed-spray fluid bed granulation were studied.

• Multivariate statistical process control (MSPC) was used to monitor granulation.

• Correlation optimized warping synchronized time-varying process batch trajectories.

• Near-infrared (NIR) spectroscopy with MSPC was used as a quality control strategy.

• NIR spectroscopy-based multivariate process trajectories were proposed for granulation.


Abstract

Pulsed spray is a useful tool for granule size control in fluid bed granulation. To improve the quality control of pulsed-spray fluid bed granulation, a combination of in-line near-infrared (NIR) spectroscopy and principal component analysis was used to develop multivariate statistical process control (MSPC) charts. Different types of MSPC charts were developed, including principal component score charts, Hotelling's T2 control charts, and distance to model X control charts, to monitor the batch evolution throughout the granulation process. Correlation optimized warping was used as an alignment method to deal with the time variation in batches caused by the granulation mechanism in MSPC modeling. The control charts developed in this study were validated on normal batches and tested on four batches that deviated from normal processing conditions to achieve real-time fault analysis. The results indicated that the NIR spectroscopy-based MSPC model included the variability in the sample set constituting the model and could withstand external variability. This research demonstrated the application of synchronized NIR spectra in conjunction with multivariate batch modeling as an attractive tool for process monitoring and a fault diagnosis method for effective process control in pulsed-spray fluid bed granulation.

Graphical abstract
Keywords
Pulsed-spray fluid bed granulation; Multivariate statistical process control; Multiway principal component analysis; Near-infrared spectroscopy; Correlation optimized warping