Table Of ContentIndustry 4.0 Vision for the Supply of Energy and Materials
Industry 4.0 Vision for the Supply of Energy
and Materials
Enabling Technologies and Emerging Applications
Edited by
Mahdi Sharifzadeh
Sharif University of Technology
Tehran, Iran
This edition first published 2022
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Library of Congress Cataloging-in-Publication Data
Names: Sharifzadeh, Mahdi, editor.
Title: Industry 4.0 vision for the supply of energy and materials: enabling technologies and
emerging applications / edited by Mahdi Sharifzadeh.
Other titles: Industry four point zero vision for energy and materials
Description: First edition. | Hoboken, NJ, USA : John Wiley & Sons, Inc., 2022. |
Includes bibliographical references and index.
Identifiers: LCCN 2021061622 (print) | LCCN 2021061623 (ebook) | ISBN 9781119695936
(hardback) | ISBN 9781119695967 (pdf) | ISBN 9781119695950 (epub) | ISBN 9781119695868 (ebook)
Subjects: LCSH: Industry 4.0. | Automation--Case studies. | Telecommunication--Case studies.
Classification: LCC T59.6 .I48 2022 (print) | LCC T59.6 (ebook) |
DDC 658.4/038028563--dc23/eng/20220224
LC record available at https://lccn.loc.gov/2021061622
LC ebook record available at https://lccn.loc.gov/2021061623
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Cover design by Wiley
Set in 9.5/12.5pt STIXTwoText by Integra Software Services Pvt. Ltd, Pondicherry, India
10 9 8 7 6 5 4 3 2 1
v
Contents
Preface vii
Part I Industry 4.0 Drivers 1
1 Connectivity through Wireless Communications and Sensors 3
2 Blockchain and Smart Contracts 59
3 Robotics: A Key Driver of Industry 4.0 73
4 Cloud Computing and Its Impact on Industry 4.0: An Overview 99
5 Applications of Artificial Intelligence and Big Data in Industry 4.0
Technologies 121
Part II Industry 4.0 Technologies 159
6 Multi-Vector Internet of Energy (IoE): A Key Enabler for the Integration of
Conventional and Renewable Power Generation 161
7 The Economic Implication of Integrating Investment Planning and Generation
Scheduling: The Application of Big Data Analytics and Machine Learning 189
8 A Systematic Method for Wireless Sensor Placement: A Fault-Tolerant
Communi cation Solution for Monitoring Water Distribution Networks 221
9 An Overview of the Evolution of Oil and Gas 4.0 241
10 Electrification of Transportation: Transition Toward Energy Sustainability 269
11 C omputer-Aided Molecular Design: Accelerating the Commercialization Cycle 297
vi Contents
12 Pharmaceutical Industry: Challenges and Opportunities for Establishing
Pharma 4.0 313
13 Additive Manufacturing: A Game-Changing Paradigm in Manufacturing and
Supply Chains 339
Glossary 359
Index 371
vii
Preface
The Fourth Industrial Revolution, also known as Industry 4.0 or I4.0, refers to the
recent accelerated uptake of a portfolio of technologies that enable a high degree of
automation, integration, transparency, decentralization, and at the same time inter-
connectedness in the industrial sector, as well as other sectors such as health, educa-
tion, and agriculture, enabling optimal and evidence-based decision-making. The
emergence of Industry 4.0 is the result of dramatic advances and convergence in mul-
tiple disciplines. These include a sharp increase in the capabilities for artificial intelli-
gence, wireless communication (e.g., Internet of things), cloud-based computations,
smart transactions (blockchains), and robotics. Such capabilities have manifested
themselves in the form of novel paradigms such as smart manufacturing, the Internet
of things, predictive maintenance, and additive manufacturing.
The present contribution reports the collective endeavors of a multidisciplinary
group of researchers to explore the emerging trends inspired by the aforementioned
evolutions, especially with the focus on the flow of energy and materials in supply
chains. The book has two main parts. In the first part, the key drivers of Industry 4.0,
namely, artificial intelligence, wireless communication, blockchains and smart con-
tracts, cloud computing, and robotics, are discussed. The second part explores the
application of such advancements in the fields of energy networks, additive manufac-
turing, pharmaceutical industry, water distribution, renewable power generation,
petroleum and gas industries, as discussed in the following.
Chapter 1 explores recent advancements in sensor and communication technologies
and their contribution to the realization and commercial viability of industrial/
Internet of things (I/IoTs), smart manufacturing, and other Industry 4.0 paradigms. It
also discusses the applications of communication technologies in Industry 4.0 and the
required criteria. Other features of interest include the relevant standards and proto-
cols, cellular and mobile technologies, the design of wireless systems for IIoT applica-
tions and relevant protocols, and smart sensors and their enabling role in Industry 4.0.
The chapter concludes with predicting future trends in wireless communication for
Industry 4.0.
Chapter 2 explores the concepts and methods that have enabled distributed and
smart transaction systems such as blockchains. The features of interest include the
blockchain taxonomy, desirable attributes, architecture, and most importantly the
emerging applications in different sectors.
Chapter 3 is concerned with the application of robotics in Industry 4.0. First, a com-
prehensive survey of various classes of robots is presented. The classification is pre-
sented with respect to robots’ geometry, actuator and control strategies, and kinematics,
viii Preface
as well as more advanced features such as the number of agents and fabrication mate-
rials. Then the applications of various robotic systems are presented in different areas.
Chapter 4 focuses on the utilization of cloud computing in Industry 4.0. The main
characteristics of cloud computing, as well as developed architectures and types of ser-
vices, the model of cloud deployment, and the corresponding pros and cons are exten-
sively discussed in this chapter. The last part of this chapter explores emerging
paradigms such as edge computing and fog computing and elucidate their differences
compared with traditional cloud and grid computing.
Chapter 5 provides a comprehensive review of artificial intelligence (AI) methods.
The reviewed algorithms are categorized into supervised and unsupervised methods.
In the supervised methods, two major groups of classification and regression methods
are discussed. In the classification methods, the key features of decision trees (DT), the
(naive) Bayesian classifier, K-nearest neighbors (KNNs), linear discriminant analysis
(LDA), support vector machines (SVM) and kernel methods, relevance vector
machines (RVMs), ensemble methods, and logistic regression are reviewed. In the
regression methods, ordinary least squares (OLS) regression, ridge and lasso regres-
sion, support vector regression (SVR), Gaussian process regression (GPR), and thin
plate spline (TPS) are discussed. A separate section is devoted to neural networks and
deep learning, especially to recent developments in convolutional neural networks
(CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM), trans-
formers, graph neural networks (GNNs), generative adversarial networks (GAN),
autoencoders, and self-organizing maps (SOMs). Among unsupervised learning algo-
rithms, special attention is paid to clustering methods such as k-means clustering and
hierarchical clustering, DBSCAN, as well as linear and nonlinear dimensionality
reduction methods (e.g., principal component analysis [PCA], linear discriminant
analysis, manifold learning, Laplacian eigenmaps method). This chapter also provides
a brief overview of semi-supervised and active Learning, bio-inspired methods, as well
as reinforcement learning (RL).
The second part of the book begins with Chapter 6, in which the concept of the
Internet of energy (IoE) is introduced. The discussion starts with the description of
conventional energy grids, exposure of their limitations, and elucidation of the poten-
tials that have become available through the incorporation of the Industry 4.0 technol-
ogies. It continues by reviewing the structure of IoE, with particular emphasis on
energy routers, energy hubs, and software-defined networks (SDNs). The utilization of
other I4.0 technologies such as big-data analytics and blockchains are also discussed
with a special focus on energy trading and transactive IoE.
In Chapter 7, a more specific problem relevant to the Internet of energy is evaluated,
which is concerned with the evolving nature of energy infrastructures. Considering
the depleting fossil sources and their negative environmental impact, significant
efforts are devoted to commercial utilization of renewable energies such as wind and
solar power generation. However, the high penetration of renewable energies in the
electricity grid also poses a significant challenge due to the intermittent and stochastic
nature of wind and solar energies. The conventional approach to tackle such com-
plexity is either through costly energy storage or provision of standby power plant
capacity that is usually driven by fossil fuels. However, a paradigm shift has emerged
using advanced control and communication systems that would deploy predictive
analytics for real-time optimization, eliminating the need for expensive solutions such
Preface ix
as energy storage and power plant extra capacity. The chapter explores the economic
benefits of utilizing such intelligent systems, through the integration of artificial intel-
ligence in the form time-series prediction, and optimization programming for
electricity expansion planning and real-time dispatch.
Chapter 8 explores another specific utilization of Industry 4.0 technologies in the
water distribution networks. Water pipelines are prone to operational issues such as
aging, leakage, water theft, and sabotage attacks. The utilization of smart sensors
quipped with wireless and cellular communication technologies opens up new ave-
nues for monitoring and fault detection. Nonetheless, there is always a trade-off bet-
ween the number of utilized sensors and selected technology (as well as associated
costs) and the observability and possibility of fault detection. In this chapter, a
systematic method based on multi-objective optimization is presented that, while min-
imizing the costs, ensures a certain degree of observability for the network, even in the
case of multiple sensor failures.
Chapter 9 is focused on the evolution of oil and gas industries utilizing Industry 4.0
technologies. The discussions include the introduction of recent trends such as data
acquisition and processing systems, smart and soft sensors, and digital twins, as well
as challenges that need to be addressed for their commercial implementation. More
attention is paid to the architecture that allows the fusion of Industry 4.0 technologies
such as cloud computing, sensor-to-cloud connectivity, 5G, industrial Internet of
things (IIoTs), and AI, with emphasis on standards that enable such integration. The
chapter concludes by exploring potential future developments.
In recent years, the transformation of fossil-driven vehicles using electric engines
has revolutionized the transportation industry. Chapter 10 studies the impact of
Industry 4.0 on transportation electrification. The features of interest include the envi-
ronmental, economic, and societal benefits that are achievable from such transforma-
tion, as well as corresponding barriers and challenges. A deep discussion of the
electrification technologies is provided with special attention to the degree of electrifi-
cation, types of electric motors, required battery and charging technologies, as well as
connectivity of vehicles to grid (V2G), other vehicles (V2V), infrastructure (V2I), build-
ings (V2B), and clouds (V2C) technologies, which can promote energy efficiency as
well as traffic safety. Other integrating Industry 4.0 technologies include blockchains,
artificial intelligence, cyber-security, and robotics are also discussed in this chapter.
Dramatic advances in computational capabilities have also revolutionized the way
that products and services are developed and dramatically have shortened their time
to market. This is the focus of Chapter 11, with emphasis on the role that computer-
aided molecular design (CAMD) plays in reducing the costs of designing new mate-
rials and products in the form of predicting their properties and reducing requirements
for physical experimentation. Different CAMD methods are discussed, and implemen-
tation procedures are presented. This chapter also reviews the emerging and novel
applications of CAMD in the industry.
Chapter 12 evaluates the impact of Industry 4.0 on the pharmaceutical industry. The
discussions include the regulatory considerations in this sector, and the recent trends
in smart manufacturing of pharmaceuticals in the form of continuous processing, ana-
lytical technologies, and digitalization.
The final chapter of the book explores additive manufacturing as a paradigm-shift-
ing technology. Various types of 3D and 4D printing are reviewed and their advantages
