Abstract

In this work, a multi objective optimization of batch fluidized drying of two pharmaceutical powders (Group A particles and Group B particles) has been performed using desirability function. Optimization was studied based on non-linear models that take into account particle entrainment and combine dense bed and freeboard sections. Optimization criterion was simultaneously minimizing drying time, dense bed specific energy consumption, and freeboard specific energy consumption. The desired solid final moisture content was considered as a constraint. The control variables were air temperature and air velocity. For the Group B particles, simulation results indicated that desirability increase was monotonic with air temperature increase and air velocity decrease. For the Group A particles, it was shown, the existence of a desirability optimum. By comparing static and dynamic control to the real batch operation, the highest percent reduction of drying time, dense bed specific energy consumption, and freeboard specific energy consumption was obtained for static control with a high value of fixed inlet air temperature. Nevertheless, the risk of product overheating and damaging could be reduced by temperature reduction during the drying process as showed by optimal control trajectories obtained in the case of dynamic control.

摘要

在这项工作中，使用意愿函数对两种药物粉末（A 组颗粒和 B 组颗粒）的批量流化干燥进行了多目标优化。基于非线性模型研究了优化，该模型考虑了颗粒夹带并结合了致密床和干舷部分。优化标准是同时最小化干燥时间、密集床单位能耗和干舷单位能耗。所需的固体最终水分含量被认为是一个约束。控制变量是空气温度和空气速度。对于 B 组粒子，模拟结果表明，随着气温升高和风速降低，合意性增加是单调的。对于 A 组粒子，显示出存在最适合意性。通过将静态和动态控制与实际间歇操作进行比较，对于具有高固定入口空气温度值的静态控制，获得了干燥时间、密床比能耗和干舷比能耗的最高百分比减少。然而，在干燥过程中降低温度可以降低产品过热和损坏的风险，如在动态控制情况下获得的最佳控制轨迹所示。