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Related Experiment Videos

Enhancing bioprocess operability with generic software sensors.

G A Montague1, A J Morris, M T Tham

  • 1Department of Chemical and Process Engineering, University of Newcastle, UK.

Journal of Biotechnology
|August 1, 1992
PubMed
Summary
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Software sensors improve industrial bioprocess operations. This study compares adaptive linear models and artificial neural networks, demonstrating significant operability enhancements through software sensor development in bioprocess applications.

Area of Science:

  • Bioprocess Engineering
  • Software Engineering
  • Control Systems

Background:

  • Industrial bioprocesses require real-time monitoring for optimal performance.
  • Existing monitoring methods face operability challenges.
  • The development of advanced software sensing is crucial for addressing these challenges.

Purpose of the Study:

  • To explore the concept of generic model-based software sensors for bioprocess applications.
  • To evaluate the effectiveness of different software sensor methodologies in industrial settings.
  • To highlight the operability improvements achievable through software sensor development.

Main Methods:

  • Consideration of alternative formulation philosophies for software sensors.
  • Presentation and comparison of an adaptive linear model-based method and an artificial neural network-based method.

Related Experiment Videos

  • Application and performance analysis of these methods on two industrial bioprocess demonstrator systems.

    • Main Results:

    • Demonstration of operability problems in industrial bioprocess systems necessitating software sensor development.
    • Comparative performance analysis of adaptive linear models and artificial neural networks in bioprocess applications.
    • Quantification of operability improvements achieved by implementing developed software sensors.

    Conclusions:

    • Generic model-based software sensors offer significant potential for enhancing bioprocess operations.
    • Both adaptive linear models and artificial neural networks show promise, with performance varying based on application.
    • Software sensor development is a key strategy for improving the efficiency and reliability of industrial bioprocesses.