Development of a Virtual Sensor for Real-Time Prediction of Granule Flow Properties.

Area of Science:

• Chemical Engineering
• Process Analytical Technology (PAT)

Background:

• Real-time process monitoring is crucial for efficient granulation lines.
• Traditional flowability measurements are time-consuming off-line methods.
• Granule properties significantly impact processability and product quality.

Purpose of the Study:

• To develop a virtual sensor for real-time prediction of granule flowability.
• To enable faster decision-making in granulation process control.
• To overcome limitations of conventional, time-intensive flowability tests.

Main Methods:

• Utilizing camera imaging to capture granule size and shape distribution.
• Applying statistical methods to correlate imaging data with established flowability metrics.
• Developing a real-time measurement system for granule characterization.

Main Results:

• Demonstrated correlation between granule size/shape and flowability parameters.
• Established the foundation for a virtual sensor capable of rapid flowability assessment.
• Identified key image-derived features predictive of flowability.

Conclusions:

• The virtual sensor offers a faster alternative to traditional flowability testing.
• Real-time flowability prediction enhances process control and supply chain management.
• This technology supports the implementation of advanced process analytical technology in granulation.