Investigating screw-agitator speed ratio impact on feeding performance in pharmaceutical manufacturing using discrete element method.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
11 Sep 2024
Historique:
received: 24 05 2024
accepted: 05 09 2024
medline: 12 9 2024
pubmed: 12 9 2024
entrez: 11 9 2024
Statut: epublish

Résumé

In continuous powder handling processes, precise and consistent feeding is crucial for ensuring the quality of the final product. The intermixing effect caused by agitators, which alters the powder's bulk density, flow rate, and flow patterns, plays a significant role in this process, yet it is often overlooked. This study combines discrete element method (DEM) modeling and experiments using a commercial-scale feeder to propose a Digital Twin (DT) framework. The DEM model accurately captures key flow features, such as bypass trajectories, stagnant zones, and preferential flow patterns, while providing quantitative predictions for the feed factor and zones prone to material accumulation. Scenario analysis is performed to identify the most favorable operating ranges of the screw-agitator ratio and screw speed, considering the cohesive properties of the powder. The study demonstrates that powders with poor flow characteristics require tighter operational constraints, as the screw-agitator ratio is susceptible to variations in mass feed rate. This contribution highlights the importance of selecting an appropriate screw-agitator ratio instead of maintaining a fixed value. Properly choosing this ratio helps determine an optimal operation window, which aims to achieve a minimum agitation level needed to induce unhindered flow and reduce variability in the mass flow rate.

Identifiants

pubmed: 39261620
doi: 10.1038/s41598-024-72288-0
pii: 10.1038/s41598-024-72288-0
doi:

Substances chimiques

Powders 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

21234

Subventions

Organisme : Bijzonder Onderzoeksfonds UGent
ID : BOF.STG.2020.0049.01

Informations de copyright

© 2024. The Author(s).

Références

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Auteurs

Luz Nadiezda Naranjo Gómez (LN)

Pharmaceutical Engineering Research Group (PharmaEng), Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.
Laboratory of Pharmaceutical Process Analytical Technology (LPPAT), Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.

Kensaku Matsunami (K)

Pharmaceutical Engineering Research Group (PharmaEng), Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.

Paul Van Liedekerke (P)

Department of Data Analysis and Mathematical modeling, Ghent University, Coupure Links 653, 9000, Ghent, Belgium.

Thomas De Beer (T)

Laboratory of Pharmaceutical Process Analytical Technology (LPPAT), Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium.

Ashish Kumar (A)

Pharmaceutical Engineering Research Group (PharmaEng), Department of Pharmaceutical Analysis, Ghent University, Ottergemsesteenweg 460, 9000, Ghent, Belgium. ashish.kumar@ugent.be.

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