著者
Keita Yaginuma Shuichi Tanabe Manabu Kano
出版者
The Pharmaceutical Society of Japan
雑誌
Chemical and Pharmaceutical Bulletin (ISSN:00092363)
巻号頁・発行日
vol.70, no.1, pp.74-81, 2022-01-01 (Released:2022-01-01)
参考文献数
23

Soft sensors are powerful tools for the implementation of process analytical technology (PAT). They are categorized into white-box (first-principle), black-box (statistical), and gray-box models. Gray-box models integrate white-box and black-box models to address each drawback, i.e., prediction accuracy and intuitiveness. Although they have been applied to various industrial processes, their applicability to water content monitoring in fluidized bed granulation has not been reported. In this study, we evaluated three types of gray-box models, i.e., parallel, serial, and combined gray-box models, in terms of prediction accuracy using real operating data on a commercial scale with two formulations. The gray-box models were constructed by integrating the heat and mass balance model (white-box model) and locally weighted partial least squares regression (LW-PLSR) model (black-box model). LW-PLSR was utilized to cope with collinearity and nonlinearity. In the serial gray-box models, LW-PLSR models adjusted the fitting parameters of the white-box model depending on the process parameters for each query. In the parallel gray-box or combined gray-box models, LW-PLSR models compensated for the output error of the white-box or serial gray-box models, respectively. The results demonstrated that all three types of gray-box models improved the prediction accuracy of the white-box models regardless of the formulation. Besides, we proposed the assessment method based on Hotelling’s T2 and Q residual for gray-box models using LW-PLSR, which contributes decision support to select gray-box or white-box model. The accurate and descriptive gray-box models are expected to enhance process understanding and precise quality control in fluidized bed granulation.

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他には、物理モデルと統計モデルを組み合わせたグレイボックスモデルによる品質特性予測。流動層造粒プロセスが対象で、第一三共の成果。 https://t.co/QSnmxbz9AU
博士課程学生(社会人)の論文が公開された.医薬品製造時の品質予測にグレイボックスモデル(物理モデル+統計モデル)を使うという内容だが,Featured articleに選ばれた.素晴らしい. Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation https://t.co/SSYvxwbqQi https://t.co/BmjhyWvaap

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