Comparative study on the real-time monitoring of a fluid bed drying process of extruded granules using near-infrared spectroscopy and audible acoustic emission.

The process of fluidized bed drying of granules was comparatively evaluated by on-line real-time measurements of granule moisture content (MC) using near-infrared spectroscopy (NIR) and audible acoustic emission (AAE). The extruded granules were prepared by kneading a powder blend containing lactose, starch, crystalline cellulose, and riboflavin, with water. The MC of the granules (while they were dried at 35 °C in a fluidized bed dryer) was monitored simultaneously with NIR and AAE. The prediction accuracy of the NIR and AAE using partial least squares (PLS) was verified by measuring MC of the granules. The best calibration models following NIR and AAE evaluations consisted of five latent variables with correlation coefficients of 1.000 and 0.998 and root mean square error of 0.259 and 0.615, respectively. As a result of external verification, the accuracy of MC analysis by AAE was slightly lower than that of NIR; however, it was still applicable in practice. Furthermore, the end point of fluidized bed drying process was automatically determined using the PLS discriminant analysis. From the above results, it can be concluded that the AAE-mediated granule drying process can be monitored with sufficient accuracy (compared with NIR).