Real-time monitoring of the drying of extruded granules in a fluid-bed dryer using audible acoustic emission chemometrics

Abstract

The purpose of this study was an attempt to adapt the audible acoustic emission (AAE) sound measurement method for the on-line monitoring of the fluid-bed drying progress of pharmaceutical granules. The granules were prepared by extrusion-granulation based on a formulation of 6.7 : 2 : 1 lactose–starch–crystalline cellulose. After the granulation process, the drying process was performed in a fluid-bed dryer at 27 or 42 °C, and AAE sound was measured using a digital voice recorder. The recorded signals were transformed into frequency spectra by using the fast Fourier transformation function. Samples were collected every 60 seconds to determine the moisture content of the granules. The calibration models to predict the moisture content of the granules were constructed based on AAE frequency spectra by using the partial least squares regression method after area normalized function. In order to test the robustness of the calibration model obtained under different dry operating conditions (air temperature) with various acoustic environments (noise), the moisture content of the granules was predicted based on AAE frequency spectra containing noise. The external validation results suggested that the calibration model could be applied to any data set. The regression vector indicated that the sound in the low frequency range might have been caused by the contact of the granules upon over-hydration at the initial stage of the drying process. In contrast, the sound at high frequencies might have been caused by friction of the dried granules later in the drying process.