scholarly journals Digital Twin of Low Dosage Continuous Powder Blending - Artificial Neural Networks and Residence Time Distribution Models

Author(s):  
Áron Kristóf Beke ◽  
Martin Gyürkés ◽  
Zsombor Kristóf Nagy ◽  
György Marosi ◽  
Attila Farkas
Pharmaceutics ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1119
Author(s):  
Martin Gyürkés ◽  
Lajos Madarász ◽  
Ákos Köte ◽  
András Domokos ◽  
Dániel Mészáros ◽  
...  

The present paper reports a thorough continuous powder blending process design of acetylsalicylic acid (ASA) and microcrystalline cellulose (MCC) based on the Process Analytical Technology (PAT) guideline. A NIR-based method was applied using multivariate data analysis to achieve in-line process monitoring. The process dynamics were described with residence time distribution (RTD) models to achieve deep process understanding. The RTD was determined using the active pharmaceutical ingredient (API) as a tracer with multiple designs of experiment (DoE) studies to determine the effect of critical process parameters (CPPs) on the process dynamics. To achieve quality control through material diversion from feeding data, soft sensor-based process control tools were designed using the RTD model. The operation block model of the system was designed to select feasible experimental setups using the RTD model, and feeder characterizations as digital twins, therefore visualizing the output of theoretical setups. The concept significantly reduces the material and instrumental costs of process design and implementation.


2019 ◽  
Vol 344 ◽  
pp. 525-544 ◽  
Author(s):  
M. Sebastian Escotet-Espinoza ◽  
Sara Moghtadernejad ◽  
Sarang Oka ◽  
Zilong Wang ◽  
Yifan Wang ◽  
...  

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