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Digital Twins for Bioprocess Control Strategy Development and Realisation

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Digital Twins

Part of the book series: Advances in Biochemical Engineering/Biotechnology ((ABE,volume 177))

Abstract

New innovative Digital Twins can represent complex bioprocesses, including the biological, physico-chemical, and chemical reaction kinetics, as well as the mechanical and physical characteristics of the reactors and the involved peripherals. Digital Twins are an ideal tool for the rapid and cost-effective development, realisation and optimisation of control and automation strategies. They may be utilised for the development and implementation of conventional controllers (e.g. temperature, dissolved oxygen, etc.), as well as for advanced control strategies (e.g. control of substrate or metabolite concentrations, multivariable controls), and the development of complete bioprocess control. This chapter describes the requirements Digital Twins must fulfil to be used for bioprocess control strategy development, and implementation and gives an overview of research projects where Digital Twins or “early-stage” Digital Twins were used in this context. Furthermore, applications of Digital Twins for the academic education of future control and bioprocess engineers as well as for the training of future bioreactor operators will be described. Finally, a case study is presented, in which an “early-stage” Digital Twin was applied for the development of control strategies of the fed-batch cultivation of Saccharomyces cerevisiae.

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Development, realisation and optimisation of control strategies utilising Digital Twins

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Abbreviations

AMBC:

Advanced and model-based control

CHO:

Chinese hamster ovary (mammalian cell)

DCU:

Digital control unit

DLL:

Dynamic link library

DO:

Dissolved oxygen

DoE:

Design of experiment

EtOH:

Ethanol

GUI:

Graphical user Interface

MPC:

Model predictive control

NMPC:

Nonlinear model predictive control

OLFO:

Open-loop-feedback-optimal strategy

OTS:

Operator training simulator

P:

Product (Ethanol)

P:

Proportional (P-controller)

P&ID:

Piping and instrumentation diagram

PCS:

Process control system

PI:

Proportional integral (PI-controller)

PID:

Proportional integral derivate (PID-controller)

RQ:

Respiratory quotient

S:

Substrate (Glucose)

SSF-BC:

Simultaneous saccharification, fermentation, and biocatalysis

STR:

Stirred tank reactor

X:

Dry biomass density (S. cerevisiae)

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Acknowledgements

The authors would like to thank C. Fittkau and S. Dreßler for their excellent laboratory work at Furtwangen University. We gratefully appreciate that parts of the presented work have been funded by the German Federal Ministry of Education and Research, Innovation Alliance prot P.S.I. (FKZ: 031B0405C).

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Authors and Affiliations

  1. Faculty of Medical and Life Sciences, Furtwangen University, Villingen-Schwenningen, Germany

    Christian Appl, André Moser & Volker C. Hass

  2. Department of Biochemical Engineering, University College London, London, UK

    Christian Appl, Frank Baganz & Volker C. Hass

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  1. Christian Appl
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  2. André Moser
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  3. Frank Baganz
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  4. Volker C. Hass
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Correspondence to Volker C. Hass .

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Editors and Affiliations

  1. Institute of Chemical, Environmental and Bioscience Engineering, Vienna University of Technology, Wien, Austria

    Christoph Herwig

  2. Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, Hamburg, Germany

    Ralf Pörtner

  3. Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, Hamburg, Germany

    Johannes Möller

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Appl, C., Moser, A., Baganz, F., Hass, V.C. (2020). Digital Twins for Bioprocess Control Strategy Development and Realisation. In: Herwig, C., Pörtner, R., Möller, J. (eds) Digital Twins. Advances in Biochemical Engineering/Biotechnology, vol 177. Springer, Cham. https://doi.org/10.1007/10_2020_151

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