Pre-testing in simulations allows for risk avoidance in scaling up. We offer consulting services. Monthly contracts available.
The spray dryer allows for the consideration of product quality variation control and equipment scale-up (enlargement) by simulating factors that influence particle size control, moisture content control, and particle shape during the manufacturing process. In modeling, the particle size distribution is calculated based on the Population Balance equation, and the drying process of the particles is also taken into account. Additionally, representing adhesion to the walls is an important requirement in the simulation. With the integration of Siemens' STAR-CCM+, it is possible to analyze the actual gas flow in detail, which can be used for considerations of scale-up and operational improvements. This is an optional feature of gPROMS FormulatedProducts. *For more details, please download the catalog or contact us.
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basic information
You can check related videos on YouTube. "Spray Dryer Digital Twin" https://youtu.be/VbjU2HgF-5o https://youtu.be/xHw57Y2qTAk
Price range
Delivery Time
P3
※This is the delivery date after the license agreement. If you have any other questions, please feel free to contact us.
Applications/Examples of results
Spray Drying Process - Spray Dryer Model * Scale-up * Consideration of Operational Improvements
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Company information
Founded in 1997 by the gPROMS development team at Imperial College London, PSE became part of the Siemens Group in 2019 and has been providing products and services in Japan as Siemens Corporation since 2023. gPROMS features a powerful equation-based computation engine that differs from traditional simulators, allowing for seamless handling of both steady-state and dynamic simulations. This enables the effective scaling up of models adjusted with experimental data from batch processing for the design and operational optimization of continuous processing plants. With gPROMS's excellent capabilities in custom modeling, parameter estimation, and optimization, it is possible to quickly build optimal manufacturing processes, resolve issues, and achieve optimization.
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