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.

脉冲喷雾是流化床制粒中控制粒度的有用工具。为了改善脉冲流化床造粒的质量控制，在线近红外（NIR）光谱和主成分分析相结合被用于开发多元统计过程控制（MSPC）图表。开发了不同类型的MSPC图表，包括主成分评分表，Hotelling的T ²控制图以及到模型X控制图的距离，以监控整个制粒过程中的批次演变。在MSPC建模中，使用相关优化的翘曲作为对齐方法来处理由于制粒机理导致的批次时间变化。本研究中开发的控制图已在正常批次上进行了验证，并在偏离正常处理条件的四个批次上进行了测试，以实现实时故障分析。结果表明，基于NIR光谱的MSPC模型包括构成模型的样本集中的变异性，并且可以承受外部变异性。