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Related Experiment Video

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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

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Ensuring tablet quality via model-based control of a continuous direct compaction process.

Martin Kirchengast¹, Selma Celikovic¹, Jakob Rehrl²

¹Institute of Automation and Control, Graz University of Technology, Graz, Austria.

International Journal of Pharmaceutics

|July 1, 2019

Summary

This summary is machine-generated.

Continuous pharmaceutical manufacturing enhances productivity and quality. This study introduces a control strategy for direct compaction, ensuring consistent active pharmaceutical ingredient concentration and tablet press (TP) hopper levels, even during variations.

Keywords:

Continuous manufacturing Direct compaction Model predictive control Process control

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Area of Science:

Chemical Engineering
Pharmaceutical Technology
Process Control

Background:

Continuous manufacturing offers advantages over batch processing in pharmaceuticals, including improved efficiency and consistent product quality.
Direct compaction is a key process in continuous tablet production.

Purpose of the Study:

To present a control strategy for direct compaction in a continuous tablet production line.
To ensure stable active pharmaceutical ingredient (API) concentration and tablet press (TP) hopper levels.

Main Methods:

A data-driven, linear modeling approach was used.
A Smith predictor was developed for API concentration control.
A model predictive controller was implemented for TP hopper level control.

Main Results:

The control strategy effectively managed API concentration variations.
The TP hopper level was maintained consistently.
A system for discarding out-of-specification material before the TP was implemented.

Conclusions:

The developed control strategy is effective for continuous direct compaction.
The approach ensures steady product quality and process efficiency.
Validation through simulations and pilot plant implementation confirms the strategy's robustness.