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This article describes the results of three case studies conducted consecutively, in order to develop a process control strategy for a top-spray fluid bed granulation process. The use of several real-time particle size (i.e., spatial filter velocimetry and focused beam reflectance measurement) and moisture (i.e., near infrared (NIR) and Lighthouse near infrared spectroscopy) analyzers was examined. A feedforward process control method was developed, where in-line collected granulation information during the process spraying phase was used to determine the optimum drying temperature of the consecutive drying phase. Via real-time monitoring of process (i.e., spraying temperature and spray rate) and product (i.e., granule size distribution and moisture) parameters during the spraying period, the batch bulk density was predicted at the end of the spraying cycle, using a PLS model. When this predicted bulk density was not meeting the desired value, the developed control method allowed the calculation of an adjusted drying temperature leading to the desired batch bulk density at the end of the granulation process. Besides the development of the feed-forward control strategy, a quantitative PLS model for in-line moisture content prediction of the granulated end product was built using the NIR data.

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