Purpose

Continuous wet granulation and drying require an adequate process control strategy to ensure the product quality. The most important critical quality attributes of dried granules are the granule size distribution and moisture content. Process analytical technologies (PATs) are available for real-time monitoring of moisture content by, e.g., near-infrared spectroscopy (NIRS), which requires additional installation and complex multivariate validation. Thus, a mass and energy balance (MEB) was derived for a vibrated fluidised bed dryer, which is part of the QbCon^® 1 intended for continuous wet granulation and drying.

Method

Process parameters that are frequently logged were used for the derivation of a MEB. The predicted MEB was compared with the measured loss-on-drying (LOD) for two different formulations.

Results

The model-derived data were in good agreement with the observed LOD, leading to RMSE values of 0.12–0.45.

Conclusion

The implemented MEB can predict the LOD over time and thus might be suitable as a soft sensor without the installation of additional sensors. The obtained energy flux gives insight into the heat transfer, and the derived energy balance might be used to determine the required energy under certain drying conditions.

中文翻译：

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通过质量和能量平衡预测振动流化床干燥机的干燥失重

目的

连续湿法制粒和干燥需要适当的过程控制策略以确保产品质量。干燥颗粒最重要的关键质量属性是颗粒尺寸分布和水分含量。过程分析技术 (PAT) 可通过近红外光谱 (NIRS) 等方式实时监测水分含量，这需要额外的安装和复杂的多变量验证。因此，我们得出了振动流化床干燥机的质量与能量平衡（MEB），该干燥机是 用于连续湿法制粒和干燥的QbCon ^{® 1 的一部分。}

方法

经常记录的过程参数用于导出 MEB。将两种不同配方的预测 MEB 与测量的干燥失重 (LOD) 进行比较。

结果

模型导出的数据与观察到的 LOD 非常一致，导致 RMSE 值为 0.12-0.45。

结论

实施的 MEB 可以预测随时间变化的 LOD，因此可能适合作为软传感器，而无需安装额外的传感器。获得的能量通量可以深入了解热传递，并且导出的能量平衡可用于确定某些干燥条件下所需的能量。