Industrial application of heat- and mass balance model for fluid-bed granulation for technology transfer and design space exploration

Ochsenbein, David R.; Billups, Matthew; Hong, Bingbing; Schäfer, Elisabeth; Marchut, Alexander J.; Lyngberg, Olav

doi:10.1016/j.ijpx.2019.100028

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…Özahi 27 described a thermodynamic mode applied to a batch fluidized bed dryer. Ochsenbein also presented a heat–mass balance model of a pharmaceutical industrial continuous fluidized bed drying process 28 . Wang, 10 Beigi, 15 and Srinivas 9 presented heat and mass transfer models to describe the phenomena within the dried particles in a batch fluidized bed dryer.…”

Section: Data Analysis and Case Studymentioning

confidence: 99%

An improved batch fluidized drying experimental design based on digital sensors and a minicomputer

Cui

Peng

et al. 2021

Engineering Reports

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In most undergraduate programs of chemical engineering in Chinese universities, the batch fluidized bed drying (BFBD) experiment is commonly adopted as a part of the experimental course of chemical engineering unit operation. In those BFBD experiments, the students should dry the material in a dryer, repeatedly sample and measure it outside to get its moisture content. In most cases, each sampling and measuring operation needs more than 5 min. The BFBD drying experiment conducted in that manner cannot obtain adequate, accurate data, making it difficult for the student to perform proper calculation and data analysis. In this article, the authors build a small BFBD prototype equipment and mount a set of digital temperature/humidity sensors. Then they use a Raspberry Pi 3, a kind of mini‐computer, to automatically measure and record the process parameters values online. Aided by those modern information process methods, the data accuracy and amount are all enhanced. Based on the gotten big data set, the student can get much more accurate results and do a more thorough analysis. The data analysis based on the old BFBD equipment is too straightforward and simple because it only needs the mass balance calculations. On the contrary, although the new BFBD equipment adopts an indirect way to measure the drying process, it obtains much more accurate results than before. The students must also apply more theories to get the results, such as mass transmission, the thermal balance, which makes the experiment more comprehensive. That is meaningful and helps to achieve the objectives of the chemical engineering experiments.

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Section: Data Analysis and Case Studymentioning

confidence: 99%

An improved batch fluidized drying experimental design based on digital sensors and a minicomputer

Cui

Peng

et al. 2021

Engineering Reports

View full text Add to dashboard Cite

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Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation

2022

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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 T 2 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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Model Based Process Development and Operation of a Fluid Bed Granulation Unit to Manufacture Pharmaceutical Tablets

Mu�oz,

Sen,

Gupta

et al. 2024

Systems and Control Transactions

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A hybrid model for the fluid bed granulation operation was built. The deterministic component focuses on the mass and energy balances representing the water ingress and egress from the powder bed. The empirical one does on granule growth. Estimability techniques were used to determine which parameters to regress from the available data. A partial least squares approach was used to better understand the impact of the model parameters onto key model responses and sensitivity plots were made to aid operational decisions and support pharmaceutical development.

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Industrial application of heat- and mass balance model for fluid-bed granulation for technology transfer and design space exploration

Abstract: Graphical abstract

Cited by 3 publications

References 19 publications

An improved batch fluidized drying experimental design based on digital sensors and a minicomputer

An improved batch fluidized drying experimental design based on digital sensors and a minicomputer

Gray-box Soft Sensor for Water Content Monitoring in Fluidized Bed Granulation

Model Based Process Development and Operation of a Fluid Bed Granulation Unit to Manufacture Pharmaceutical Tablets

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