DEM–compartment–population balance model for particle coating in a horizontal rotating drum

Kumar, Rahul; Freireich, Ben; Wassgren, Carl

doi:10.1016/j.ces.2014.06.046

Cited by 37 publications

(27 citation statements)

References 22 publications

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“…The initial trends shown in Figures and are similar to those reported previously, with the CoV inter exhibiting initial fluctuations due to the limited particle mixing during the initial stages of coating. The large kinks in Figure near one drum revolution correspond to when the bed has “turned over” once in the drum . After a sufficiently large number of drum revolutions, the CoV inter trend is expected to decrease with the square root of the number of drum revolutions, i.e., have a −1/2 slope using the log‐log axes shown in the figures (refer to Eq.…”

Section: Resultsmentioning

confidence: 99%

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Scaling inter‐tablet coating variability in a horizontal rotating drum

et al. 2017

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This study investigates how the drum‐to‐particle diameter ratio (D/d) affects the surface speed and interparticle coating variability in geometrically similar coaters. Discrete element method simulations were used to model particle movement in different‐sized, cylindrical drums with identical particle diameters, Froude numbers, fill volume fractions, and spray characteristics. The dimensionless streamwise surface speed profiles become increasingly symmetric as D/d increases, with the maximum speed increasing with D/d. The relationship between the maximum dimensionless speed and D/d is fit well with a power‐law expression. Interparticle coating variability decreases with the square root of the number of drum revolutions after a sufficiently large number of drum revolutions. Increasing D/d increases, in a logarithmic manner, the number of drum revolutions required to reach a given degree of coating variability. A similar logarithmic coating variability trend was observed in simulations using almond‐shaped pharmaceutical tablets, suggesting that the trend is independent of tablet shape. © 2017 American Institute of Chemical Engineers AIChE J, 63: 3743–3755, 2017

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Section: Resultsmentioning

confidence: 99%

“…The parameter p i is the cumulative number of exposed pixels for particle i and N is the total number of particles . The standard deviation in the coating mass, σ , is

σ = \sqrt{\frac{1}{N} {(p_{i} - μ)}^{2}}

…”

Section: Model Descriptionmentioning

confidence: 99%

Scaling inter‐tablet coating variability in a horizontal rotating drum

et al. 2017

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“…Kumar et al [129] coupled DEM to a compartment based PBM to model particle coating in horizontal rotating drum, creating a multi-scale model that is much faster than DEM alone and can predict the inter-particle coating variability with accuracy.…”

Section: Tablet Coatingmentioning

confidence: 99%

Discrete Element Modeling of Solid Dosage Manufacturing Processes

Barrasso

Ramachandran

2016

Methods in Pharmacology and Toxicology

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Solid dosage manufacturing primarily involves powder process operations, such as mixing, granulation, and compaction. A model-based approach can be used to develop a better scientific understanding of these processes and implement Quality by Design. These models must predict the critical quality attributes of the product based on process parameters, equipment geometry, and material properties. Discrete element modeling (DEM) is often used to capture mechanistic, particle-scale information, such as velocity and force profiles. In this chapter, recent literature studies that use the DEM to model solid dosage manufacturing processes will be presented and discussed.

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“…Two of the papers in this special issue are fundamental studies of unit processes that build and control the solids dosage forms from the primary particles (Sayin et al, 2015;Kumar et al, 2015). Wet granulation is an example of a process where the equipment for continuous pharmaceutical manufacture is very different from the batch.…”

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confidence: 99%

“…This paper uses a multi-scale modeling approach where DEM simulations are linked to a macroscopic population balance through a compartment model approach. This multi-scale approach is a powerful and necessary approach for developing predictive design models through linking particle scale simulation of important physics (Pei et al, 2015;Huang et al, 2015) with unit process models and experiments (Deng et al, 2015;Sayin et al, 2015;Kumar et al, 2015).…”

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confidence: 99%