PDF Handbook of Industry 4.0 and SMART Systems 1st Edition Diego Galar Pascual (Author) Download
PDF Handbook of Industry 4.0 and SMART Systems 1st Edition Diego Galar Pascual (Author) Download
PDF Handbook of Industry 4.0 and SMART Systems 1st Edition Diego Galar Pascual (Author) Download
com
https://textbookfull.com/product/handbook-of-
industry-4-0-and-smart-systems-1st-edition-
diego-galar-pascual-author/
textbookfull
More products digital (pdf, epub, mobi) instant
download maybe you interests ...
https://textbookfull.com/product/maintenance-costs-and-life-
cycle-cost-analysis-1st-edition-diego-galar/
https://textbookfull.com/product/robots-drones-uavs-and-ugvs-for-
operation-and-maintenance-1st-edition-diego-galar-author/
https://textbookfull.com/product/digital-manufacturing-and-
assembly-systems-in-industry-4-0-1st-edition-kaushik-kumar-
editor/
https://textbookfull.com/product/a-roadmap-to-industry-4-0-smart-
production-sharp-business-and-sustainable-development-anand-
nayyar/
Advances in Mathematics for Industry 4.0 1st Edition
Deepti Aggrawal
https://textbookfull.com/product/advances-in-mathematics-for-
industry-4-0-1st-edition-deepti-aggrawal/
https://textbookfull.com/product/enabling-technologies-for-the-
successful-deployment-of-industry-4-0-1st-edition-antonio-sartal-
editor/
https://textbookfull.com/product/industry-4-0-challenges-trends-
and-solutions-in-management-and-engineering-1st-edition-carolina-
machado-editor/
https://textbookfull.com/product/information-systems-for-
managers-with-cases-edition-4-0-gabriele-piccoli/
https://textbookfull.com/product/implementing-industry-4-0-the-
model-factory-as-the-key-enabler-for-the-future-of-
manufacturing-1st-edition-carlos-toro/
Handbook of Industry 4.0
and SMART Systems
Handbook of Industry 4.0
and SMART Systems
This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been made
to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all
materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all
material reproduced in this publication and apologize 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.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, 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.
For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://www.
copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-
8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For organizations that
have been granted a photocopy license by the CCC, a separate system of payment has been arranged.
Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for
identification and explanation without intent to infringe.
Visit the Taylor & Francis Web site at
http://www.taylorandfrancis.com
Preface...................................................................................................................................................... vii
Authors....................................................................................................................................................... xi
Index....................................................................................................................................................... 365
v
Preface
Modern market becomes more global and less national or local. Developed world market is reflected in
the wide range of new products, the rapid obsolescence of products, and the emergence of new products,
high quality standards, short delivery, and decreasing costs. Such conditions are very difficult for the
classical industrial production we have today, and thanks to the 29 progress of modern technological
achievements, such as communication networks and the Internet, that force us to develop and introduce
a new modern era of industrial production based on communicational informational linking of manufac-
turers and customers. This transformative shift in production and manufacturing paradigm is popularly
termed as Industry 4.0. Industry 4.0 has elicited much interest from both industry and academia. A recent
literature survey identified the basic concept, perspectives, key technologies, and industrial applications
of Industry 4.0 and examined its challenges and future trends [1,2] . However, no work has established
a systematic framework of smart manufacturing systems for Industry 4.0 that guides academic research
and industrial implementation until now. To fill the gap, this study proposes a conceptual framework for
Industry 4.0 and Smart Systems.
Actually many disruptive technologies, such as Cloud Computing, Internet of Things (IoT), big data
analytics, and artificial intelligence, have emerged. These technologies are permeating the manufacturing
industry and make it smart and capable of addressing current challenges, such as increasing customized
requirements, improved quality, and reduced time to market. An increasing number of sensors are being
used in equipment (e.g., machine tools) to enable them to self-sense, self-act, and communicate with one
another. Through these technologies, real-time production data can be obtained and shared to facilitate
rapid and accurate decision making. The connection of physical manufacturing equipment and devices
over the Internet together with big data analytics in the digital world (e.g., the cloud) has resulted in the
emergence of a revolutionary means of production, namely, Cyber Physical Production Systems (CPPS).
CPPS are a materialization of the general concept CPS in the manufacturing environment. The intercon-
nection and interoperability of CPS entities in manufacturing shop floors together with analytics and
knowledge learning methodology provide an intelligent decision support system. The widespread appli-
cation of CPS (or CPPS) has ushered in the fourth stage of industrial production, namely, Industry 4.0.
CPPS consist of autonomous and cooperative elements and subsystems, connecting communications
and interactions in different situations, at all levels of production, machines, processes to manufacturing,
and logistics networks. Their operational modeling and forecasting allows the implementation of a series
of basic applied oriented research tasks, and above all controlled systems at any level. The basic assump-
tion in terms of CPPS is reflected in the research and defining relations through the prism of autonomy,
cooperation, optimization and response to the assigned tasks. By integrating analytic and simulation-
based approaches, this prediction may be described in greater detail than ever before. Such systems must
confront a series of new challenges in terms of operational sensor networks, smart actuators, databases
and many others, above all, communication protocols.
CPPS will enable and support the communication between humans, machines, and products alike.
The elements of a CPPS are able to acquire and process data, and can self-control certain tasks and
interact with humans via interfaces.
Although extensive effort continues to be exerted to make systems smart, smart systems do not have a
widely accepted definition. In Industry 4.0, CPPS can be regarded as smart manufacturing systems. CPPS
comprise smart machines, warehousing systems, and production facilities that have been developed digi-
tally and feature end-to-end Information and Communication Technology (ICT)-based integration from
inbound logistics to production, marketing, outbound logistics, and service. Smart manufacturing sys-
tems can generally be defined as fully integrated and collaborative manufacturing systems that respond
in real time to meet the changing demands and conditions in factories and supply networks and satisfy
vii
viii Preface
varying customer needs. Key enabling technologies for smart manufacturing systems include CPS, IoT,
Internet of Services (IoS), cloud-based solutions, Artificial Intelligence (AI), and Big Data Analytics.
Today we are on the threshold of a new industrial revolution, the revolution by which digital networks
are related to operating values in the intelligent factory, and that includes everything from the initial
idea, through design, development, and manufacture, to maintenance, service, and recycling. Industries
4.0 include horizontal integration of data flow between partners, suppliers, and customers, as well as
vertical integration within the organization’s frames – from development to final product. It merges the
virtual and the real world. The result is a system in which all processes are fully integrated – system in
information in real-time frame. The speed and rate of changes in consumer trends will be a significant
driver of Industry 4.0.
Since the products are configured to respond to the preferences of individual users, production must
be more flexible and must be shorter.
The point is to create value for customers, and that means to involve them in the process from the
beginning. Of course, the companies that use the highly efficient mass production to achieve economies
of scale are in benefit, while at the same time they have the opportunity to offer a high level of adaptation.
The industries in developed countries in Europe and North America are based on the exploitation of
CPS through technology based on the integration of wireless systems, wireless control system, machine
learning, and production-based sensors. Such industries are developing a national platform for new pro-
duction systems and new age of Industry4.0-based access to the Internet and CPS.
CPS are a new generation of systems that integrate computer and physical abilities. With the combi-
nation of cyber systems and physical systems, user semantic laws can be traced and thus communicate
with people. Cybernetic systems are a summation of logic and sensor unit, while the physical systems
are a summation of actuator units. Through the ability to interact and expand capabilities of the physical
world using computing power, communication technologies and control mechanisms, CPS allow feed-
back loops, improving production processes and optimum support of people in their decision-making
processes. By using the corresponding sensor technology, CPS are able to receive direct physical data
and convert them into digital signals. They can share this information and access the available data that
connect it to digital networks, thereby forming an IOT.
On the other hand, production of new generation should be adjusted to changeable conditions and
issues put before it. Optimization of plant operations will be implemented by improving and speeding
up communications. Starting points are the solutions offered by a vision of “smart environment” for
production.
In order to create a large-scale smart system, smart devices are used. The term “smart” (often used
to mark intelligence) seems to be applicable in different contexts, because its meaning with respect to
objects is not yet clearly defined.
Smart, in some contexts, refers to an independent device, which usually consists of the sensor, and/or
to activate the microprocessor and transceiver. However, adjective smart is used to characterize and that
contributes to the implementation of additional meanings, which introduced multi-platform communi-
cation and increase of its computing capacity. Intelligence is revealed through cooperation in networks
with other smart devices, which have the possibility to check the system updates and decide whether to
act on them or not. Such a network is called smart grid. They may find a reference to smart objects as
objects that have the ability to connect the stored data, as well as offer access to it for human or machine’s
needs. There are so much smart products that are equipped with memory options so that they can be
understood as a kind of living product.
This era, which is which sensors and chips identify and locate products, and in which products know
their history and current status. This network of machines, storage systems, and manufacturing plants
that will exchange inevitably ahead of us is by the scientific circles of developed European countries
cooled new industrial revolution or Industry 4.0.
The modern process of globalization is characterized by its essential dimensions. First, it marks the
objective planetary processes:
Preface ix
• The essence of technological evolution; compression of time and space, reducing the distance
and time required for more branched, global communication.
• Close connection and interdependence of societies; everything is in a wider range of activities
that have become transnational, and cannot be managed solely within the individual states.
Globalization means the spread of identical form (industrialism and then post-industrialism,
market economy and multi-party political system) to almost the entire social world space.
The book covers a wide range of topics, including Fundamentals and Architecture of Industry 4.0, Cyber
Physical Systems (CPS), Smartness and Pervasive Computing, Cloud Computing, Big Data Analytics,
Cybersecurity and Risks, and finally Industry 4.0 across the sectors. A number of demonstrative sce-
narios are presented, and current challenges and future research directions are discussed.
We expect that the book will be useful for the beginners as well as for the researchers working in the
field of Industry 4.0 and smart systems
Authors
Diego Galar Pascual is a Professor of Condition Monitoring in the Division of Operation and
Maintenance Engineering at Luleå University of Technology (LTU), where he is coordinating several
H2020 projects related to different aspects of cyber-physical systems, Industry 4.0, IoT, or industrial Big
Data. He was also involved in the SKF UTC center located in Lulea focusing on SMART bearings and
also actively involved in national projects with the Swedish industry or funded by Swedish national agen-
cies such as Vinnova. He has been involved in the raw materials business of Scandinavia, especially with
mining and oil and gas for Sweden and Norway, respectively. Indeed, LKAB, Boliden or STATOIL have
been partners or funders of projects in the CBM field for specific equipment such as loaders, dumpers,
rotating equipment, linear assets, and so on.
He is also the principal researcher in Tecnalia (Spain), heading the Maintenance and Reliability
research group within the Division of Industry and Transport.
He has authored more than 500 journal and conference papers, books, and technical reports in the
field of maintenance, working also as a member of editorial boards, scientific committees, and chairing
international journals and conferences and actively participating in national and international commit-
tees for standardization and R&D in the topics of reliability and maintenance.
In the international arena, he has been a Visiting Professor at the Polytechnic of Braganza (Portugal),
University of Valencia, NIU (USA) and the Universidad Pontificia Católica de Chile. Currently, he is
Visiting Professor at the University of Sunderland (UK), University of Maryland (USA), University of
Stavanger (NOR), and Chongqing University (China).
Pasquale Daponte was born in Minori (SA), Italy, on March 7, 1957. He obtained his bachelor’s degree
and master’s degree “cum laude” in Electrical Engineering in 1981 from the University of Naples, Italy.
He is a Full Professor of Electronic Measurements at the University of Sannio—Benevento.
From 2016, he is the Chair of the Italian Association on Electrical and Electronic Measurements. He is
Past President of IMEKO.
He is a member of I2MTC Board, Working Group of the IEEE Instrumentation and Measurement
Technical Committee N°10 Subcommittee of the Waveform Measurements and Analysis Committee,
IMEKO Technical Committee TC-4 “Measurements of Electrical Quantities,” Editorial Board
of Measurement Journal, Acta IMEKO and of Sensors. He is an Associate Editor of IET Science
Measurement & Technology journal.
He has organized some national or international meetings in the field of Electronic Measurements and
European cooperation, and he was the General Chairman of the IEEE Instrumentation and Measurement
Technical Conference for 2006, and Technical Programme Co-Chair for I2MTC 2015.
He was a co-founder of the IEEE Symposium on Measurement for Medical Applications MeMeA; now,
he is the Chair of the MeMeA Steering Committee (memea2018.ieee-ims.org). He is the co-founder of the
IEEE Workshop on Metrology for AeroSpace (www.metroaerospace.org), IEEE Workshop on Metrology
for Archaeology and Cultural Heritage (www.metroarcheo.com), IMEKO Workshop on Metrology for
Geotechnics (www.metrogeotechnics.org), IEEE Workshop on Metrology for the Sea (www.metrosea.org),
and IEEE Workshop on Metrology for Industry 4.0 and IoT (www.metroind40iot.org).
He is involved in some European projects. He has published more than 300 scientific papers in journals
and presented papers at national and international conferences on the following subjects: Measurements
and Drones, ADC and DAC Modelling and Testing, Digital Signal Processing, and Distributed
Measurement Systems.
He received the award for the research on the digital signal processing of the ultrasounds in echo-
ophthalmology in 1987 from the Italian Society of Ophthalmology, the IEEE Fellowship in 2009, the
Laurea Honoris Causa in Electrical Engineering from Technical University “Gheorghe Asachi” of
xi
xii Authors
Iasi (Romania) in 2009, “The Ludwik Finkelstein Medal 2014” from the Institute of Measurement and
Control of United Kingdom, and the “Career Excellence Award” from the IEEE Instrumentation and
Measurement Society “For a lifelong career and outstanding leadership in research and education on
instrumentation and measurement, and a passionate and continuous service, international in scope, to the
profession” in May 2018, and IMEKO Distinguished Service Award in September 2018.
Uday Kumar is Chair Professor of Operation and Maintenance Engineering, Director of Research and
Innovation (Sustainable Transport), and Director of Luleå Railway Research Center at Luleå University
of Technology, Luleå, Sweden.
His teaching, research, and consulting interests are equipment maintenance, reliability and maintain-
ability analysis, product support, life cycle costing (LCC), risk analysis, system analysis, eMaintenance,
and asset management.
He is a Visiting Faculty at the Center of Intelligent Maintenance System (IMS) – a center sponsored by
National Science Foundation, Cincinnati, USA, since 2011; External Examiner and Program Reviewer
for Reliability and Asset Management Program of the University of Manchester; Distinguished Visiting
Professor at Tsinghua University, Beijing; honorary professor at Beijing Jiao Tong University, Beijing; etc.
Earlier, he has been a Visiting Faculty at Imperial College London; Helsinki University of Technology,
Helsinki; University of Stavanger, Norway; etc.
He has more than 30 years of experience in consulting and finding solutions to industrial problems,
directly or indirectly related to maintenance of engineering asserts. He has published more than 300
papers in international journals and conference proceedings dealing with various aspects of maintenance
of engineering systems, and has coauthored four books on Maintenance Engineering and contributed to
World Encyclopaedia on Risk Management.
He is an elected member of Royal Swedish Academy of Engineering Sciences.
1
Fundamentals of Industry 4.0
CONTENTS
1.1 Introduction....................................................................................................................................... 3
1.2 Industry 4.0....................................................................................................................................... 4
1.2.1 Definition of Industry 4.0.................................................................................................... 5
1.2.2 What Is Industry 4.0?.......................................................................................................... 5
1.2.2.1 Industry 4.0—What Is It?................................................................................... 5
1.2.2.2 Talking about a Revolution: What Is New in Industry 4.0?............................... 6
1.2.2.3 On the Path to Industry 4.0: What Needs to Be Done?..................................... 6
1.2.3 Key Paradigm of Industry 4.0............................................................................................. 6
1.2.4 Industry 4.0 Conception...................................................................................................... 7
1.2.4.1 Five Main Components of Networked Production............................................ 7
1.2.5 Framework of Industry 4.0: Conception and Technologies................................................ 8
1.2.6 Nine Pillars of Technological Advancement...................................................................... 8
1.2.6.1 Big Data and Analytics...................................................................................... 9
1.2.6.2 Autonomous Robots..........................................................................................11
1.2.6.3 Simulation.........................................................................................................11
1.2.6.4 Horizontal and Vertical System Integration.....................................................11
1.2.6.5 Industrial IoT.....................................................................................................11
1.2.6.6 Cybersecurity................................................................................................... 12
1.2.6.7 The Cloud......................................................................................................... 12
1.2.6.8 Additive Manufacturing................................................................................... 12
1.2.6.9 Augmented Reality........................................................................................... 12
1.2.7 Macro Perspective of Industry 4.0.................................................................................... 12
1.2.8 Micro Perspective of Industry 4.0......................................................................................14
1.2.9 Industry 4.0 Components.................................................................................................. 15
1.2.9.1 Cyber-Physical Systems (CPS)......................................................................... 15
1.2.9.2 Internet of Things............................................................................................. 15
1.2.9.3 Internet of Services...........................................................................................16
1.2.9.4 Smart Factories.................................................................................................17
1.2.10 Industry 4.0: Design Principles..........................................................................................17
1.2.10.1 Interoperability..................................................................................................17
1.2.10.2 Virtualization....................................................................................................18
1.2.10.3 Decentralization................................................................................................18
1.2.10.4 Real-Time Capability........................................................................................18
1.2.10.5 Service Orientation...........................................................................................18
1.2.10.6 Modularity.........................................................................................................18
1.2.11 Impact of Industry 4.0........................................................................................................18
1.2.11.1 Quantifying the Impact: Germany as an Example...........................................18
1.2.11.2 Producers: Transforming Production Processes and Systems......................... 19
1.2.11.3 Manufacturing-System Suppliers: Meeting New Demands and Defining
New Standards................................................................................................. 21
1
2 Handbook of Industry 4.0 and SMART Systems
LIST OF FIGURES
LIST OF TABLES
1.1 Introduction
Industry 4.0 is one of the most frequently discussed topics among practitioners and academics today.
For example, the German federal government announced Industry 4.0 as one of the key initiatives of its
high-tech strategy in 2011 (Kagermann et al., 2013). Since then, numerous academic publications, practi-
cal articles and conferences have focused on the topic (Hermann et al., 2015).
The fascination for Industry 4.0 is twofold. First, for the first time, an industrial revolution has been
predicted a priori, not observed ex-post (Drath, 2014). This provides opportunities for companies and
research institutes to actively shape the future. Second, the economic impact of this industrial revolu-
tion is supposed to be huge, as Industry 4.0 promises substantially increased operational effectiveness
as well as the development of entirely new business models, services and products (Kagermann et al.,
2013; Kagermann et al., 2014; Kempf et al., 2014). A recent study has estimated that these benefits will
have contributed as much as 78 billion euros to the German GDP by the year 2025 (Bauer et al., 2014).
Germany will not be the sole country to profit; similar benefits are expected throughout the world.
With Industry 4.0 becoming a top priority for many research centers, universities and companies within
the past three years, the manifold contributions from academics and practitioners have made the mean-
ing of the term more blurry than concrete (Bauernhansl et al., 2014). Even the key promoters of the idea,
the “Industry 4.0 Working Group” and the “Plattform Industry 4.0,” only describe the vision, the basic
technologies the idea aims at and selected scenarios (Kagermann et al., 2013). They do not provide a
clear definition. As a result, a generally accepted definition of Industry 4.0 has not been published to date
(Bauer et al., 2014).
According to Jasperneite et al. (2012), scientific research is always impeded if clear definitions are
lacking, as any theoretical study requires a sound conceptual and terminological foundation. Companies
also face difficulties when trying to develop ideas or take action, but are not sure what exactly for. “Even
though Industry 4.0 is one of the most frequently discussed topics these days, I could not explain to
my son what it really means,” a production site manager with automotive manufacturer Audi puts it.
This comment reflects the finding of a recent study that “most companies in Germany do not have a
clear understanding of what Industry 4.0 is and what it will look like” (eco—Verband der deutschen
Internetwirschaft, 2014).
4 Handbook of Industry 4.0 and SMART Systems
As the term is unclear, companies are struggling when it comes to identifying and implementing
Industry 4.0 scenarios. Design principles explicitly address this issue by providing a “systemization of
knowledge” (Gregor et al., 2009) and describing the constituents of a phenomenon. In this way, design
principles support practitioners by developing appropriate solutions. From an academic perspective,
design principles are the foundation of design theory (Gregor et al., 2002). However, we could not find
any explicit Industry 4.0 design principles during our search of the literature (Hermann et al., 2015).
This chapter aims to fill this gap in the research. Based on a literature review, it provides a definition
of Industry 4.0 and identifies six design principles that companies should consider when implementing
Industry 4.0 solutions (Hermann et al., 2015).
Horizontal integration across the entire value creation network includes cross-company and internal
company intelligent cross-linking and digitalization of value creation modules throughout the value
chain of a product life cycle and between value chains of adjoining product life cycles.
End-to-end engineering across the entire product life cycle refers to intelligent cross-linking and digi-
talization throughout all phases of a product life cycle, from the raw material acquisition to manufactur-
ing, product use, and product end of life.
Vertical integration and networked manufacturing systems include the intelligent cross-linking and
digitalization within the different aggregation and hierarchical levels of a value creation module from
manufacturing stations via manufacturing cells, lines and factories, also integrating the associated value
chain activities, such as marketing and sales or technology development (Acatech, 2015).
Intelligent cross-linking and digitalization covers the application of an end-to-end solution using infor-
mation and communication technologies (ICTs) embedded in the cloud (Stock and Seliger, 2016).
In a manufacturing system, intelligent cross-linking is realized by the application of CPS operating in
a self-organized and decentralized manner (Acatech, 2015; Gausemeier et al., 2015; Spath et al., 2013).
They are based on embedded mechatronic components, i.e., applied sensor systems for collecting data,
as well as actuator systems for influencing physical processes (Gausemeier et al., 2015). Cyber-physical
systems are intelligently linked with each other and are continuously interchanging data via virtual
networks such as the cloud in real-time. The cloud itself is implemented in the Internet of Things (IoT)
and services (Acatech, 2015). As part of a sociotechnical system, CPS use human–machine interfaces to
interact with operators (Hirsch-Kreinsen and Weyer, 2014).
that are already being delivered and in use can send data to the manufacturer. By using these
data, the manufacturer can improve his or her products and offer the customer novel services.
• Optimized logistics: Algorithms can calculate ideal delivery routes; machines indepen-
dently report when they need new material—smart networking enables an optimal flow
of goods.
• Use of data: Data on the production process and the condition of a product can be combined and
analyzed. Data analysis will provide guidance on how to make a product more efficiently. More
importantly, there is a foundation for completely new business models and services. For exam-
ple, lift manufacturers can offer their customers “predictive maintenance”: elevators equipped
with sensors that continuously send data about their condition. Product wear can be detected
and corrected before it leads to an elevator system failure.
• Resource-efficient circular economy: The entire life cycle of a product can be considered with
the support of data. The design phase will be able to determine which materials can be recycled
(Plattform Industrie 4.0).
adapt to challenging work environments (Schmitt et al., 2013). As the most flexible entity in production
systems, workers will be faced with a variety of jobs, ranging from specification and monitoring to ver-
ification of production strategies. By the same token, they will manually intervene in the autonomously
organized production system, if required. Optimum support can be provided by mobile, context-
sensitive user interfaces and user-focused assistance systems (Gorecky et al., 2014). Established inter-
action technologies offer forward-looking solutions, including some from the consumer goods market
(e.g., tablets, smart glasses and smart watches). Of course the latter need to be adapted to industrial
conditions. Through technological support, workers can realize their full potential, thereby becoming
strategic decision-makers and fl exible problem solvers capable to handle the steadily rising technical
complexity (Weyer et al., 2015).
• Digital workpieces
Each workpiece knows the dimensions, quality requirements and order of its own processing.
• Intelligent machines
Intelligent machines communicate simultaneously with the production control system and the
workpiece being processed, so that the machine coordinates, controls and optimizes itself.
• Vertical network connections
After processing the customer’s unique specifications for the product to be manufactured, the
production control system forward automated rules to the equipment. Essentially, the products
control their own manufacturing process, as they communicate with the equipment, devices
and other workpieces on the conditions of production.
• Horizontal network connections
Communication is realized not only within one factory, but throughout the whole supply chain,
between the suppliers, manufacturers and service providers. The main purpose is to enhance
the efficiency of production and to utilize the resources in a more economical way.
• Smart workpieces
The product to be manufactured senses the production environment with internal sensors and
controls and monitors its own production process to meet the production standards; it can do
so because it can communicate with the equipment, as well as with the components already
incorporated or about to be incorporated.
8 Handbook of Industry 4.0 and SMART Systems
Industry 4.0 is not a future technology. In July 2015, the Changing Precision Technology Company
(in Dongguan, China) became the first factory where only robots work. Each labor process is exe-
cuted by machines: production is done by computer-operated robots and transport is implemented
by self-driven vehicles; even the storage process is completely automatic (Gubán and Kovás, 2017).
Autonomous
Robots
System
Cybersecurity
integraon
Cloud Addive
compung manufacturing
FIGURE 1.1 Main technologies of Industry 4.0. (From Rübmann, M. et al., Industry 4.0: The Future of Productivity and
Growth in Manufacturing Industries, The Boston Consulting Group (BCG), 2015.)
Fundamentals of Industry 4.0 9
Autonomous
Big data and Robots
analy cs
Simula on
INDUSTRY 4.0
FIGURE 1.2 Nine advances transforming industrial production. (From Rübmann, M. et al., Industry 4.0: The Future of
Productivity and Growth in Manufacturing Industries, The Boston Consulting Group (BCG), 2015.)
technology: big data and analytics; autonomous robots, simulation, horizontal and vertical system inte-
gration, the Industrial IoT, cybersecurity, the cloud, additive manufacturing and augmented reality (see
Figure 1.2). In this transformation, sensors, machines, workpieces and IT systems are connected along
the value chain beyond a single enterprise. These connected systems (also called CPS) can interact with
one another using standard Internet-based protocols. They can analyze data to predict failure, config-
ure themselves and adapt to changes. Industry 4.0 will make it possible to gather and analyze data across
machines, enabling faster, more flexible and more efficient processes to produce high-quality goods at
reduced costs. This, in turn, will increase manufacturing productivity, shift economics, foster industrial
growth and modify the profile of the workforce, ultimately changing the competitiveness of companies
and regions (Rübmann et al., 2015).
Many of the nine advances in technology are already used in manufacturing, but with Industry 4.0,
they will totally transform production: isolated, optimized cells will come together as a fully integrated,
automated and optimized production flow, leading to greater efficiency and changing traditional produc-
tion relationships among suppliers, producers and customers, as well as between human and machine
(see Figure 1.3) (Rübmann et al., 2015).
Automated
Automated
Automated
Automated Automated
FIGURE 1.3 Industry 4.0 is changing traditional manufacturing relationships. (From Rübmann, M. et al., Industry 4.0: The Future of Productivity and Growth in Manufacturing
Industries, The Boston Consulting Group (BCG), 2015.)
Handbook of Industry 4.0 and SMART Systems
Fundamentals of Industry 4.0 11
1.2.6.3 Simulation
In the engineering phase of production, three-dimensional (3-D) simulations of products, materials and
production processes are already used, but in the future, simulations will be used more extensively in
plant operations as well. These simulations will leverage real-time data to mirror the physical world in
a virtual model, which can include machines, products and humans. This will allow operators to test
and optimize the machine settings for the next product in line in the virtual world before the physical
changeover, thereby reducing machine setup times and increasing quality.
For example, Siemens and a German machine-tool vendor developed a virtual machine that can simu-
late the machining of parts using data from the physical machine. This lowers the setup time for the
actual machining process by as much as 80% (Rübmann et al., 2015).
1.2.6.6 Cybersecurity
Many companies still rely on unconnected or closed management and production systems. With the
increased connectivity and the use of the standard communications protocols accompanying Industry
4.0, the need to protect critical industrial systems and manufacturing lines from cybersecurity threats
increases dramatically. As a result, secure, reliable communications, as well as sophisticated identity and
access management of machines and users, are essential.
Several industrial-equipment vendors have joined forces with cybersecurity companies through part-
nerships or acquisitions (Rübmann et al., 2015).
Smart Logis cs
Smart Factory
Manufacturing
Mining
Consumer
Renewable Energies
FIGURE 1.4 Macro perspective of Industry 4.0. (From Stock, T. and Seliger, G., Opportunities of Sustainable
Manufacturing in Industry 4.0. 13th Global Conference on Sustainable Manufacturing—Decoupling Growth from
Resource Use, Institute of Machine Tools and Factory Management, Technische Universität Berlin, 10587 Berlin, Germany.
2212–8271© 2016 The Authors. Published by Elsevier B.V, 2016.)
From the macro perspective, horizontal integration is characterized by a network of value cre-
ation modules. Value creation modules are defined as the interplay of different value creation factors,
i.e., equipment, human, organization, process and product (Seliger et al., 2007). The value creation
modules, represented in their highest level of aggregation by factories, are cross-linked throughout
the complete value chain of a product life cycle, as well as with the value creation modules in value
chains of adjoining product life cycles. This linkage results in an intelligent network of value creation
modules covering the value chains of different product life cycles. This intelligent network provides
an environment for new and innovative business models and is thus leading to a change in business
models.
As shown in Figure 1.4, end-to-end engineering from the macro perspective is the cross-linking of
stakeholders, products and equipment along the product life cycle, beginning with the raw material acqui-
sition phase and ending with the end-of-life phase. The products, the various stakeholders such as cus-
tomers, workers or suppliers, and the manufacturing equipment are embedded in a virtual network and
are interchanging data in and between the phases of a product life cycle. This life cycle consists of the
raw material acquisition phase, the manufacturing phase—containing the product development, the engi-
neering of the related manufacturing system and the manufacturing of the product—the use and service
phase, the end-of-life phase—containing reuse, remanufacturing, recycling, recovery and disposal—and
the transport between all phases.
These value creation modules, i.e., factories embedded in this ubiquitous flow of smart data, will
evolve to become smart factories. Smart factories are already manufacturing smart products and are
being supplied with energy from smart grids and with water from freshwater reservoirs. The material
flow along the product life cycle and between adjoining product life cycles will be accomplished by
smart logistics. The stream of smart data between the various elements of the value creation networks is
interchanged via the cloud (Stock and Seliger, 2016).
Smart data are created by expediently structuring information from big data; smart data can be used
for knowledge advances and decision-making throughout the product life cycle (Smart Data Innovation
14 Handbook of Industry 4.0 and SMART Systems
Lab., 2015). When smart factories use embedded CPS for value creation, the smart product can self-
organize its required manufacturing processes and its flow throughout the factory in a decentralized
manner by interchanging smart data with the CPS (Kletti et al., 2015).
A smart product contains information on its requirements for the manufacturing processes and manu-
facturing equipment. Smart logistics use CPS to support the material flow within the factory and between
factories, customers and other stakeholders. They are controlled in a decentralized manner according to
the requirements of the product. A smart grid using renewable energies dynamically matches the energy
generation of suppliers with the energy demand of consumers, e.g., smart factories or smart homes, by
using short-term energy storages for buffering. Within a smart grid, energy consumers and suppliers can
be the same (Stock and Seliger, 2016).
Smart Factory
Consumer
Smart Grid
Outbound
Logiscs
Renewable Final
Water Energies Product
Reservoir
Cloud Service
Procurement
Technology Human
Development
Human Resource
Management
Infrastructure
FIGURE 1.5 Micro perspective of Industry 4.0. (From Stock, T., and Seliger G., Opportunities of Sustainable
Manufacturing in Industry 4.0. 13th Global Conference on Sustainable Manufacturing—Decoupling Growth from
Resource Use, Institute of Machine Tools and Factory Management, Technische Universität Berlin, 10587 Berlin, Germany.
2212–8271© 2016 The Authors. Published by Elsevier B.V, 2016.)
Fundamentals of Industry 4.0 15
From the micro perspective, horizontal integration is characterized by cross-linked value creation
modules along the material flow of the smart factory and smart logistics. The in- and outbound
logistics to and from factories will be characterized by transport equipment able to agilely react
to unforeseen events, such as a change in traffic or weather, and to autonomously operate between
the starting point and the destination. The autonomously operating transport equipment such as
automated guided vehicles (AGVs) will be used for in-house transport along the material flow. All
transport equipment will interchange smart data with the value creation modules to achieve the
decentralized coordination of supplies and products with the transport systems. For this purpose,
the supplies and products will contain identification systems, e.g., radio-frequency identification
(RFID) chips or QR codes, to enable a wireless identification and localization of all materials in the
value chain (Stock and Seliger, 2016).
From the macro perspective, vertical integration requires the intelligent cross-linking of value creation
factors, including products, equipment and humans, along the various aggregation levels of the value
creation modules, from manufacturing stations via manufacturing cells, to manufacturing lines, up to the
level of the smart factory. This networking throughout the aggregation levels includes the cross-linking
of the value creation modules with the different value chain activities, e.g., marketing and sales, service,
procurement and so on. (Porter 2015).
The value creation module in a factory refers to an embedded CPS. The manufacturing equipment,
e.g., machine tools or assembly tools, use sensor systems to identify and localize the value creation fac-
tors, such as the products or the humans, and to monitor the manufacturing processes, e.g., the cutting,
assembly or transport processes. Depending on the monitored smart data, the applied actuators in the
manufacturing equipment can react in real time on specific changes in products, humans or processes.
The communication and the exchange of the smart data between the value creation factors, between the
value creation module and the transport equipment and between the different levels of aggregation and
value chain activities are executed via the cloud.
Table 1.1 provides an overview of the main trends and expected development in the value creation fac-
tors of Industry 4.0 (Stock and Seliger, 2016).
TABLE 1.1
Trends and Expected Developments in Value Creation Factors
Equipment Manufacturing equipment will be characterized by the application of highly automated machine
tools and robots. The equipment will be able to flexibly adapt to changes in the other value
creation factors; for example, robots will work together collaboratively with human workers
on joint tasks (Kagermann et al., 2015).
Human Jobs in manufacturing sectors are likely to become automated (Frey and Osborne, 2013). The numbers
of workers will thus decrease. The remaining manufacturing jobs will contain more knowledge work
and more short-term and hard-to-plan tasks (Spath et al., 2013). Workers increasingly have to monitor
automated equipment, are being integrated in decentralized decision-making, and are participating in
engineering activities as part of the end-to-end engineering.
Organization The increasing organizational complexity in the manufacturing system cannot be managed centrally
from a certain point. Decision-making will thus become decentralized. Decision-making will
autonomously incorporate local information (Kletti et al., 2015). The decision itself will be made
by the workers or by the equipment using methods from artificial intelligence.
Process Additive manufacturing technologies, also known as 3-D printing, will be increasingly deployed in
value creation processes, as the costs of additive manufacturing are rapidly dropping and speed and
precision are simultaneously increasing (Hagel III et al., 2015). This allows designing more
complex, stronger, and more lightweight geometries and the application of additive manufacturing
to higher quantities and larger scales of the product (Hagel III et al., 2015).
Product Products will be manufactured in a batch size according to the individual requirements of the
customer (Acatech 2015). This mass customization of the product integrates the customer as
early as possible in the value chain. The physical product will also be combined with new
services offering functionality and access rather than product ownership to the customer as
part of new business models (Hagel III et al., 2015).
Source: Stock, T. and Seliger, G., Opportunities of Sustainable Manufacturing in Industry 4.0, 13th Global Conference on
Sustainable Manufacturing—Decoupling Growth from Resource Use, Institute of Machine Tools and Factory
Management, Technische Universität Berlin, 10587 Berlin, Germany. 2212–8271© 2016 The Authors. Published
by Elsevier B.V, 2016.
Therefore, the IoT can be defined as a network in which CPS cooperate with each other through unique
addressing schemas. Application examples of the IoT include smart factories, smart homes, and smart
grids (Bauernhansl et al., 2014).
FOOTNOTES:
[119] The Spirit of Laws, book v, chap. 6.
[120] Henry D. Lloyd, Man the Social Creator, 255.
[121] Idem, 246. Lloyd was rather a prophet than a man of
science, but there is a shrewd sense of fact back of his visions.
[122] Such a one
“He lets every one remain just what he is, but takes care that
he shall always be it in the right place: thus he knows how to
make all men’s power his own.” Schiller, Wallenstein’s Lager, I, 4.
CHAPTER XXIV
ON THE ASCENDENCY OF A CAPITALIST CLASS—
Continued
FOOTNOTES:
[123] The American Commonwealth, Chapter 94.
[124] Andrew Carnegie.
[125] T. W. Higginson, Book and Heart, 145.
CHAPTER XXV
THE ORGANIZATION OF THE ILL-PAID CLASSES
and loses faith in himself, in life and in God. The union makes him
feel that he is part of a whole, one of a fellowship, that there are
those who will stand by him in trouble, that he counts for something
in the great life. He gets from it that thrill of broader sentiment, the
same in kind that men get in fighting for their country; his self is
enlarged and enriched and his imagination fed with objects,
comparatively, “immense and eternal.”
Moreover, the life of labor unions and other class associations,
through the training which it gives in democratic organization and
discipline, is perhaps the chief guaranty of the healthy political
development of the hand-working class—especially those imported
from non-democratic civilizations—and the surest barrier against
recklessness and disorder. That their members get this training will
be evident to anyone who studies their working, and it is not
apparent that they would get it in any other way. Men learn most in
acting for purposes which they understand and are interested in, and
this is more certain to be the case with economic aims than with any
other.
Thus, if unions should never raise wages or shorten hours, they
would yet be invaluable to the manhood of their members. At worst,
they ensure the joy of an open fight and of companionship in defeat.
Self-assertion through voluntary organization is of the essence of
democracy, and if any part of the people proves incapable of it it is a
bad sign for the country. On this ground alone it would seem that
patriots should desire to see organization of this sort extend
throughout the industrial population.
The danger of these associations is that which besets human
nature everywhere—the selfish use of power. It is feared with reason
that if they have too much their own way they will monopolize
opportunity by restricting apprenticeship and limiting the number of
their members; that they will seek their ends through intimidation and
violence; that they will be made the instruments of corrupt leaders.
These and similar wrongs have from time to time been brought home
to them, and, unless their members are superior to the common run
of men, they are such as must be expected. But it would be a
mistake to regard these or any other kinds of injustice as a part of
the essential policy of unions. They are feeling their way in a human,
fallible manner, and their eventual policy will be determined by what,
in the way of class advancement, they find by experience to be
practicable. In so far as they attempt things that are unjust we may
expect them, in the long run, to fail, through the resistance of others
and through the awakening of their own consciences. It is the part of
other people to check their excesses and cherish their benefits.
In general no sort of persons mean better than hand-laboring men.
They are simple, honest people, as a rule, with that bent toward
integrity which is fostered by working in wood and iron and often lost
in the subtleties of business. Moreover, their experience is such as to
develop a sense of the brotherhood of man and a desire to realize it
in institutions. Not having enjoyed the artificial support of
accumulated property, they have the more reason to know the
dependence of each on his fellows. Nor have they any great hopes