(searched for: (10.5155/eurjchem.8.3.265-272.1608))
European Journal of Chemistry, Volume 8, pp 265-272; doi:10.5155/eurjchem.8.3.265-272.1608
The fluid bed granulation (FBG) is a wet granulation technique for producing granules. It is a complex process because many process variables can influence the granule properties. Therefore, an understanding of the influence of the granulation process variables is necessary for controlling the process. The moisture content of granule also plays a critical role in determining the outcome of the batch. The purpose of this work was to apply Plackett-Burman design for screening of process variables in FBG, study the influence of the process variables on granules properties and the use of NIR spectroscopy and partial least squares (PLS) regression to predict the moisture content of the granules. In order to study the influence of the process variables on the granules properties, Plackett-Burman design with six factors, two levels and three replicates at the center point (15 runs) was used. The results revealed that the atomizing pressure and the airflow rate are the process variables that have strong influence on the granules properties. The NIR spectroscopy in conjunction with PLS was used to determine the moisture content of granule in the FBG. The proposed PLS model was fitted and its predictive performance was evaluated by traditional chemometric criteria. The root mean square error of prediction (RMSEP) was 4.15% with 2 latent variables (LVs). The proposed NIR method was validated and the results obtained were compared with those of the reference LOD method using a paired t-test.