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Optimizing Energy Efficiency of a Twin-Screw Granulation Process in Real-Time Using a Long Short-Term Memory (LSTM)

Chaitanya Sampat1, Rohit Ramachandran1

  • 1Rutgers-The State University of New Jersey, 98 Brett Road, Piscataway, New Jersey 08854, United States.

ACS Engineering Au
|April 22, 2024
PubMed
Summary

This study optimized twin screw granulation (TSG) energy efficiency using a long-term memory (LSTM) model and optimization algorithms. The process achieved a 27% increase in energy efficiency while maintaining granule yield.

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Area of Science:

  • Pharmaceutical Manufacturing
  • Chemical Engineering
  • Process Optimization

Background:

  • Traditional pharmaceutical manufacturing for solid oral dosage forms is often inefficient, generating significant waste.
  • There is a growing need for energy-efficient manufacturing processes in line with carbon neutrality goals.
  • Maintaining critical quality attributes during process optimization is essential.

Purpose of the Study:

  • To maximize the energy efficiency of the twin screw granulation (TSG) process.
  • To validate the effectiveness of an LSTM model combined with optimization algorithms for TSG.
  • To demonstrate increased energy efficiency without compromising granule yield.

Main Methods:

  • Utilized a long-term memory (LSTM) model trained on time-series process data from TSG runs.
  • Employed a stochastic optimization algorithm to maximize energy efficiency under defined constraints.
  • Conducted experimental runs at optimized parameters to validate the model's predictions.

Main Results:

  • Achieved a maximum increase of 27% in energy efficiency across tested optimization scenarios.
  • Successfully maintained the yield of granules throughout the twin screw granulation process.
  • Demonstrated the capability of the combined LSTM and optimization approach to enhance TSG energy efficiency.

Conclusions:

  • The integration of LSTM models and optimization algorithms offers a powerful strategy for improving pharmaceutical manufacturing energy efficiency.
  • Optimized TSG parameters can significantly reduce energy consumption while preserving product quality.
  • This approach supports the industry's drive towards sustainable and carbon-neutral pharmaceutical production.