Abstract
A system for fluidized bed granulator automation with in-line multichannel near infrared (NIR) moisture measurement and a unique air flow rate measurement design was assembled, and the information gained was investigated. The multivariate process data collected was analyzed using principal component analysis (PCA). The test materials (theophylline and microcrystalline cellulose) were granulated and the calibration behavior of the multichannel NIR set-up was evaluated against full Fourier Transform (FT) NIR spectra. Accurate and reliable process air flow rate measurement proved critical in controlling the granulation process. The process data describing the state of the process was projected in two dimensions, and the information from various trend charts was outlined simultaneously. The absorbence of test material at correction wavelengths (NIR region) and the nature of material-water interactions affected the detected in-line NIR water signal. This resulted in different calibration models for the test materials. Development of process analytical methods together with new data visualization algorithms creates new tools for in-process control of the fluidized bed granulation.
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