Table Of ContentHybrid Modeling in Process
Industries
Hybrid Modeling in Process
Industries
Edited by
Jarka Glassey
Moritz von Stosch
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Preface ....................................................................................................................vii
Editors ......................................................................................................................ix
Contributors ............................................................................................................xi
1. Benefits and Challenges of Hybrid Modeling in the Process
Industries: An Introduction .........................................................................1
Moritz von Stosch and Jarka Glassey
2. Hybrid Model Structures for Knowledge Integration ..........................13
Moritz von Stosch, Rui M. C. Portela, and Rui Oliveira
3. Hybrid Models and Experimental Design ..............................................37
CRC Press
Moritz von Stosch
Taylor & Francis Group
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Boca Raton, FL 33487-2742 4. Hybrid Model Identification and Discrimination with Practical
© 2018 by Taylor & Francis Group, LLC Examples from the Chemical Industry ....................................................63
CRC Press is an imprint of Taylor & Francis Group, an Informa business Andreas Schuppert and Thomas Mrziglod
No claim to original U.S. Government works
5. Hybrid Modeling of Biochemical Processes ...........................................89
Printed on acid-free paper
Vytautas Galvanauskas, Rimvydas Simutis, and Andreas Lübbert
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6. Hybrid Modeling of Petrochemical Processes .....................................129
This book contains information obtained from authentic and highly regarded sources. Reasonable efforts
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have attempted to trace the copyright holders of all material reproduced in this publication and apologize
7. Implementation of Hybrid Neural Models to Predict the
to copyright holders if permission to publish in this form has not been obtained. If any copyright material
has not been acknowledged please write and let us know so we may rectify in any future reprint. Behavior of Food Transformation and Food-Waste Valorization
Processes .......................................................................................................167
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Stefano Curcio
transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter
invented, including photocopying, microfilming, and recording, or in any information storage or retrieval
system, without written permission from the publishers. 8. Hybrid Modeling of Pharmaceutical Processes and Process
Analytical Technologies ............................................................................191
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Index .....................................................................................................................213
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v
Preface
Hybrid modeling evolved from the field of neural networks and was first
reported in 1992 by Psichogios and Ungar, Johansen and Foss, Kramer et al.,
and Su et al. The central idea of Psichogios and Ungar was to a priori struc-
ture the neural network model through the use of first-principle knowledge.
The result was that when trained with the same amount of available process
data, the hybrid model was capable of predicting the process states better,
was able to interpolate and extrapolate (mostly) more accurately, and was
easier to interpret than pure neural networks.
In 1994 Thompson and Kramer introduced the terminology of parametric
and nonparametric modeling structures to the hybrid modeling field. The
parametric part of the hybrid model is a priori determined on the basis of
knowledge about the system, whereas the nonparametric model parts are
determined exclusively from data. The utilization of the term hybrid semi-
parametric modeling evolved from this classification to designate the type of
hybrid models covered in this book, clearly distinguishing this approach
from other modeling approaches that could be named hybrid, such as hybrid
systems (continuous discrete), gray-box modeling, multi-scale modeling,
block models, and others.
In the past 20 or so years, hybrid modeling has become a mature modeling
methodology, with 5 to 20 articles per year being published in many different
international peer-reviewed journals. In more than 200 articles on this topic,
the key advantages have repeatedly been highlighted. They include better
estimation/prediction performance, better inter- and extrapolation proper-
ties, less requirements on process data, and increased interpretability among
other, more application-specific advantages reported in individual contribu-
tions. These key advantages are widely acknowledged among researchers in
academia but also across process industries. Indeed, many of the modeling
advantages give rise to an improved process operation performance, but the
complexity of hybrid models—and limited education in this area and partial
knowledge—appears to hinder the routine utilization of hybrid modeling
methodology.
In an attempt to promote the adoption of this approach in the industries,
the first hybrid modeling summer school was held at Lisbon, Portugal, in
2013, followed by a European expert meeting on “Hybrid Modeling for PAT
in Biopharma: Status, Perspectives & Objectives,” the outcomes of which
were published in a position paper (von Stosch et al. 2014). The resulting
initiatives indicated that a standard book on hybrid modeling that intro-
duces the underlying theory/fundamentals and demonstrates practical
applications in several process industries is currently missing. This book is
our contribution to support the adoption and evolution of hybrid modeling
vii
viii Preface
methods in the process industries, allowing the exploitation of underused
potential, enhancing current process operation, and improving design in an
efficient way.
This book is based on contributions of leading experts in the field, and
it covers both hybrid modeling fundamentals and their application. Chapters 2
to 4 cover issues such as how to develop a hybrid model, how to represent
and identify unknown parts, how to enhance the model quality by design of
experiments, and how to compare different hybrid models, together with tips
and good practice for the efficient development of high-quality hybrid models.
Chapters 5 to 8 cover the utilization of hybrid modeling for typical process
operation and design applications in industries such as chemical, petrochemi-
cal, biochemical, food, and pharmaceutical process engineering. This book
should therefore be of interest to researchers investigating the fundamental
aspects of this modeling approach and those looking for more effective pro-
cess modeling for monitoring, process development, and optimization within
their fields.
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Editors
Dr. Jarka Glassey currently works as a Professor of Chemical engineering
education in the School of Engineering, Newcastle University, United
Kingdom. She gained her academic qualifications in chemical engineering
at the STU Bratislava, Slovakia, and PhD in biochemical process modeling at
Newcastle University, United Kingdom. She is a Chartered Engineer, Fellow
of the Institution of Chemical Engineers (IChemE), Rugby, UK, and currently
serves on the IChemE Council. She is the Executive Vice President of the
European Society of Biochemical Engineering Sciences (ESBES), and she
is also the vice chair (immediate past chair) of the Modelling, Monitoring,
Measurement & Control (M3C) Section of ESBES. Her research interests are
particularly in the areas of bioprocess modeling, monitoring, whole process
development, and optimization. She has published extensively in this area
and over the years collaborated with a wide range of industrial partners in
real-life bioprocess development and modeling applications. Currently she
is coordinating a large European academic and industrial consortium carry-
ing out research and training early career researchers in the use of the QbD,
PAT and hybrid modeling approaches within biopharma industry in order to
speed up the process development and reduce the lead times from discovery
to full scale manufacture.
Dr. Moritz von Stosch joined the Technical Research and Development
Department of GSK Vaccines in the beginning of 2017. Until then, he had
worked as a Lecturer in Chemical Engineering at the School of Chemical
Engineering and Advanced Materials, Newcastle University, Newcastle upon
Tyne, UK, and he also was the team leader of HybPAT, a spin-off initiative
with the aim of providing hybrid modeling solutions for an efficient imple-
mentation of PAT. In 2011 he earned his PhD at the Faculty of Engineering
of the University of Porto, Porto, Portugal. He was awarded his diploma in
engineering from the RWTH-Aachen University in Germany. Moritz von
Stosch is a leading expert on hybrid modeling methods and their application
to bioprocess problems. He is, for example, the author of more than ten publi-
cations on hybrid modeling and coauthor of several others. In the past years,
he co-organized an expert meeting on “Hybrid Modeling for QbD and PAT
in Biopharma,” which was integrated into the ESBES M3C panel series, and
he also co-organized all three bi-annually hold hybrid modeling summer
schools. In addition, he gave a number of invited talks on “Hybrid modeling
for QbD and PAT” across Europe and the United States.
ix
