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*Business Engineering Institute St. Gallen, Lukasstr. 4, CH-9008 St. Gallen
Working Paper
No. 01 / 2015
Design Principles for Industrie 4.0 Scenarios:
A Literature Review
Hermann, Mario
Pentek, Tobias*
Otto, Boris
Technische Universität Dortmund
Fakultät Maschinenbau
Audi Stiftungslehrstuhl Supply Net Order Management
Abstract: Although Industrie 4.0 is currently a top priority for many companies,
research centers, and universities, a generally accepted definition of the term does
not exist. As a result, discussing the topic on an academic level is difficult, and so
is implementing Industrie 4.0 scenarios. Based on a literature review, the paper
provides a definition of Industrie 4.0 and identifies six design principles for its
implementation: interoperability, virtualization, decentralization, real-time capa-
bility, service orientation, and modularity. Taking into account these principles,
academics may be enabled to further investigate on the topic, while practitioners
may find assistance in implementing appropriate scenarios.
1 Introduction
Industrie 4.0 is currently one of the most frequently discussed topics among prac-
titioners and academics in the German-speaking area (Dais, 2014, p. 625; Drath &
Horch, 2014, p. 56). Since the German federal government announced Industrie
4.0 as one of the key initiatives of its high-tech strategy in 2011 (Kagermann,
Wahlster, & Helbig, 2013, p. 77), numerous academic publications, practical arti-
cles, and conferences have focused on that topic (Bauernhansl, Hompel, & Vogel-
Heuser, 2014, p. V).
The fascination for Industrie 4.0 is twofold. First, for the first time an indus-
trial revolution is predicted a-priori, not observed ex-post (Drath, 2014, p. 2). This
provides various opportunities for companies and research institutes to actively
shape the future. Second, the economic impact of this industrial revolution is sup-
posed to be huge, as Industrie 4.0 promises substantially increased operational ef-
fectiveness as well as the development of entirely new business models, services,
and products (Kagermann et al., 2013, p. 16; Kagermann, 2014, p. 603; Kempf,
2014, p. 5). A recent study estimates that these benefits will have contributed as
much as 78 billion euros to the German GDP by the year 2025 (Bauer, Schlund,
Marrenbach, & Ganschar, 2014, p. 5).
With Industrie 4.0 becoming a top priority for many research centers, univer-
sities, and companies within the past three years, the manifold contributions from
academics and practitioners have made the meaning of the term more blurry than
concrete (Bauernhansl et al., 2014, p. V). Even the key promoters of the idea, the
“Industrie 4.0 Working Group” and the “Plattform Industrie 4.0”, only describe
the vision, the basic technologies the idea aims at, and selected scenarios (compare
Kagermann et al., 2013, p. 5; Plattform Industrie 4.0, 2014), but do not provide a
clear definition. As a result, a generally accepted definition of Industrie 4.0 has not
been published so far (Bauer et al., 2014, p. 18).
According to (Jasperneite, 2012, p. 27), scientific research is always impeded
if clear definitions are lacking, as any theoretical study requires a sound conceptu-
al and terminological foundation. Companies also face difficulties when trying to
develop ideas or take action, but are not sure what exactly for. “Even though In-
dustrie 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 automo-
tive manufacturer Audi puts it. This quote underlines the findings of a recent study
revealing that “most companies in Germany do not have a clear understanding of
what Industrie 4.0 is and what it will look like” (eco, 2014)1.
As the term itself is also unclear, companies are struggling when it comes to
identifying and implementing Industrie 4.0 scenarios. Design principles explicitly
address this issue by providing a “systemization of knowledge” (Gregor, 2009,
p. 7) and describing the constituents of a phenomenon. Therefore, design princi-
ples support practitioners in developing appropriate solutions. From an academic
perspective, design principles are the foundation of design theory (Gregor, 2002,
p. 11). Regarding Industrie 4.0, however, the authors of this paper could not find
any explicitly stated Industrie 4.0 design principles during their literature research.
The paper aims at closing this gap in research. Based on a literature review,
the authors provide a definition of Industrie 4.0 and identify six design principles,
which companies should take into account when implementing Industrie 4.0 solu-
The paper is structured as follows: Chapter 2 gives a short overview of how
the idea of Industrie 4.0 came into being, what its vision and basic goals are, and
what similar concepts can be found in the Anglo-Saxon world. Chapter 3 outlines
the research process and the research method used. Chapter 4 illustrates four com-
ponents which are closely related to the idea of Industrie 4.0, and provides a defi-
nition of Industrie 4.0 on the basis of these four components. Based on that defini-
tion, Chapter 5 introduces six design principles for identifying and implementing
Industrie 4.0 scenarios. Finally, Chapter 6 outlines the contribution of the paper to
both the scientific body of knowledge and the practical world, mentions limita-
tions of the research conducted, and proposes paths for further investigation of the
2 Background
The term “Industrie 4.0” is used for the next industrial revolution - which is about
to take place right now. This industrial revolution has been preceded by three oth-
1 Original source: „Fachleute sind der festen Überzeugung, dass die meisten Unternehmen
in Deutschland keine klare Vorstellung davon haben, was Industrie 4.0 eigentlich ist und wie sie
aussehen wird.“
er industrial revolutions in the history of mankind. The first industrial revolution
was the introduction of mechanical production facilities starting in the second half
of the 18th century and being intensified throughout the entire 19th century. From
the 1870s on, electrification and the division of labor (i.e. Taylorism) led to the
second industrial revolution. The third industrial revolution, also called “the digi-
tal revolution”, set in around the 1970s, when advanced electronics and infor-
mation technology developed further the automation of production processes.
The term “Industrie 4.0” became publicly known in 2011, when an initiative
named “Industrie 4.0” - an association of representatives from business, politics,
and academia - promoted the idea as an approach to strengthening the competi-
tiveness of the German manufacturing industry (Kagermann, Lukas, & Wahlster,
2011). The German federal government supported the idea by announcing that In-
dustrie 4.0 will be an integral part of its “High-Tech Strategy 2020 for Germany
initiative, aiming at technological innovation leadership. The subsequently formed
“Industrie 4.0 Working Group” then developed first recommendations for imple-
mentation, which were published in April 2013 (Kagermann et al., 2013, p. 77). In
this publication, Kagermann et al. (2013) describe their vision of Industrie 4.0 as
“In the future, businesses will establish global networks that incorporate their
machinery, warehousing systems and production facilities in the shape of Cyber-
Physical Systems (CPS). In the manufacturing environment, these Cyber-Physical
Systems comprise smart machines, storage systems and production facilities capa-
ble of autonomously exchanging information, triggering actions and controlling
each other independently. This facilitates fundamental improvements to the indus-
trial processes involved in manufacturing, engineering, material usage and supply
chain and life cycle management. The Smart Factories that are already beginning
to appear employ a completely new approach to production. Smart products are
uniquely identifiable, may be located at all times and know their own history, cur-
rent status and alternative routes to achieving their target state. The embedded
manufacturing systems are vertically networked with business processes within
factories and enterprises and horizontally connected to dispersed value networks
that can be managed in real time – from the moment an order is placed right
through to outbound logistics. In addition, they both enable and require end-to-end
engineering across the entire value chain.” (p. 5)
Based on that vision, the “Plattform Industrie 4.0” developed further recom-
mendations on how to implement the vision (Kagermann et al., 2013, p. 77). It
understands Industrie 4.0 as “a new level of value chain organization and man-
agement across the lifecycle of products” (Plattform Industrie 4.0, 2014).2
As the term “Industrie 4.0” is not well-known outside the German-speaking
area (Lasi, Fettke, Kemper, Feld, & Hoffmann, 2014, p. 261), it is worth to look at
comparable ideas from a global perspective. General Electric promotes a similar
idea under the name Industrial Internet (Bungart, 2014; Evans & Annunziata,
2012). It is defined as “the integration of complex physical machinery and devices
with networked sensors and software, used to predict, control and plan for better
business and societal outcomes” (Industrial Internet Consortium, 2013). The US
government supports research and development activities in the area of the Indus-
trial Internet with a 2 billion dollar fund for Advanced Manufacturing (President’s
Council of Advisors on Science and Technology, 2014, p. 46). Further similar ide-
as can be found under the terms Integrated Industry (Bürger & Tragl, 2014,
p. 560) and Smart Industry or Smart Manufacturing (Dais, 2014, p. 628; Davis,
Edgar, Porter, Bernaden, & Sarli, 2012, p. 145; Wiesmüller, 2014, p. 1).
3 Research Process and Research Method
For the overall research design, the authors of the paper followed the recommen-
dations of vom Brocke et al. (2009). To cover relevant publications in the fields of
engineering, production, and management from both academia and business, the
authors took advantage of five publication databases (CiteSeerX, ACM, AISeL,
EBSCOhost, Emerald Insight) and Google Scholar. The literature review aimed at
identifying central aspects of Industrie 4.0 in order to be able to derive a definition
of this term that is accepted by both researchers and practitioners (Cooper, 1988,
p. 109). To conceptualize Industrie 4.0 and identify key terms, a preliminary lit-
erature review was conducted (vom Brocke et al., 2009, p. 10) by searching for the
terms “Industrie 4.0” and “Industry 4.0” in Google Scholar. The two different no-
tations were applied in order to cover both German and English publications, as
the term is mostly written with “ie” in German and with a “y” in English publica-
tions. The titles, abstracts, and keywords of the first 100 results for each search
term (i.e. 200 publications in total) were analyzed by two researchers independent-
ly of each other, in order to ensure reliability of the review process (Randolph,
2009, p. 6). Each of the two researchers then assigned keywords to each publica-
tion analyzed. For example, Kagermann et al.’s vision of Industrie 4.0 (2013, p.
5), which is quoted in the previous chapter of this paper, received the keywords
2 Original source: “Der Begriff Industrie 4.0 steht für die vierte industrielle Revolution, ei-
ner neuen Stufe der Organisation und Steuerung der gesamten Wertschöpfungskette über den
Lebenszyklus von Produkten.”
CPS, Smart Factory and Smart Product, as these terms are explicitly used in the
text, and Internet of Things, as this term is implicitly mentioned in the phrase “ver-
tically networked with business processes within factories and enterprises and hor-
izontally connected to dispersed value networks”. The two researchers then aggre-
gated the keywords assigned and discussed those cases in which discrepancies had
occurred. The final list included 15 (German and English) keywords (see “Key-
words 2” in Figure 1).
Keyword 1 Keyword 2
Industrie 4.0,
Industry 4.0
Cyber-Physical Systems,
Cyber-Physikalische Systeme,
CPS, Internet of Things,
Internet der Dinge, Internet of
Services, Internet der Dienste,
Smart Factory, intelligente
Fabrik, Smart Product,
intelligentes Produkt, Big
Data, Cloud, M2M, Machine-
Figure 1: Keywords
After that, a search combining the keywords and “Industrie 4.0” or “Industry
4.0” was conducted in the five databases (see Figure 1). As this search resulted in
only a few hits, Google Scholar was included into the search process. Following
the recommendations of Webster and Watson (2002, p. xvi), the results were
complemented by a backward and forward search. Of these results, only the publi-
cations which had a clear reference to “Industrie 4.0” in their title, abstract, or
keywords were considered as relevant. This procedure led to 51 publications
which were analyzed completely by the two researchers and then tagged with the
respective keywords. Again, the results were aggregated and discussed in order to
eliminate discrepancies. The keywords were then ranked according to their fre-
quency of occurrence. The four most relevant keywords are presented as the basic
components of Industrie 4.0 in the following chapter. In accordance with vom
Brocke et al.’s (2009) last step in the literature search process, the paper outlines
further possible research activities based on the literature review’s results in Chap-
ter 6.
Based on the four basic components identified, the authors provide a defini-
tion of “Industrie 4.0”. This definition adheres to Aristotle’s rules of genus proxi-
mum and differentia specifica. While the first rule requires a definition to name the
term’s genus (i.e the superordinate concept or species the term belongs to), the lat-
ter demands a definition to specify the distinct features which distinguish the term
from other terms within the concept or species (Aristotle, 350 BC; Westermann,
In a final step, the authors derive Industrie 4.0 design principles based on the
introduced definitions of the Industrie 4.0 components and the given examples. In
order to ensure the reliability of the process, two researcher derived Industrie 4.0
design principles independently. The design principles found where combined and
grouped. In total, six groups where found. Each group is represented by a generic
term. According to Gregor (2002), these principles guide practitioners and scien-
tists on “how to do” (p. 11) Industrie 4.0.
4 Literature Review Results
The literature review identified four key components of Industrie 4.0: Cyber-
Physical Systems, Internet of Things, Internet of Services, and Smart Factory (see
Table 1). Machine-to-machine (M2M) communication and Smart Products are not
considered as independent Industrie 4.0 components by the authors of the paper,
as M2M is an enabler of the Internet of Things, and Smart Products are a sub-
component of Cyber-Physical Systems (see Chapter 4.1.1 and 4.1.2 for further de-
tails). Likewise, and in line with Kagermann (2014, p. 605-606), the authors of the
paper view big data and cloud computing as data services which utilize the data
generated in Industrie 4.0 implementations, but not as independent Industrie 4.0
In the following, the four basic Industrie 4.0 components will be described
by providing the most often cited definition, explaining each component’s link to
Industrie 4.0, and giving an application example. Afterwards, the authors provide
a new definition of Industrie 4.0, which is based on these components.
Table 1: Industrie 4.0 components (as identified in the 51 publications under analysis)
Search Term (Group) Number of Publications in Which
Search Term (Group) Occured
Cyber-Physical Systems, Cyber-Physikalische Systeme, CPS 46
Internet of Things, Internet der Dinge 36
Smart Factory, intelligente Fabrik 24
Internet of Services, Internet der Dienste 19
Smart Product, intelligentes Produkt 10
M2M, Machine-to-Machine 8
Big Data 7
Cloud 5
4.1 Industrie 4.0 Components
4.1.1 Cyber-Physical Systems (CPS)
An important component of Industrie 4.0 is the fusion of the physical and the vir-
tual world (Kagermann, 2014, p. 603). This fusion is made possible by Cyber-
Physical Systems (CPS). CPS are “integrations of computation and physical pro-
cesses. Embedded computers and networks monitor and control the physical pro-
cesses, usually with feedback loops where physical processes affect computations
and vice versa.” (Lee, 2008, p. 363). The development of CPS is characterized by
three phases. The first generation of CPS includes identification technologies like
RFID tags, which allow unique identification. Storage and analytics have to be
provided as a centralized service. The second generation of CPS are equipped with
sensors and actuators with a limited range of functions. CPS of the third genera-
tion can store and analyze data, are equipped with multiple sensors and actuators,
and are network compatible (Bauernhansl, 2014, pp. 16–17). One example of a
CPS is the intelligent bin (iBin) by Würth. It contains a built-in infrared camera
module for C-parts management, which determines the amount of C-parts within
the iBin. If the quantity falls below the safety stock, the iBin automatically orders
new parts via RFID. This allows consumption based C-parts management in real-
time (Günthner, Klenk, & Tenerowicz-Wirth, 2014, p. 307).
4.1.2 Internet of Things
According to Kagermann, the integration of the Internet of Things (IoT) and the
Internet of Services (IoS) in the manufacturing process has initiated the fourth in-
dustrial revolution (Kagermann et al., 2013, p. 5). The IoT allows “’things’ and
‘objects’, such as RFID, sensors, actuators, mobile phones, which, through unique
addressing schemas, (…) interact with each other and cooperate with their neigh-
boring ‘smart’ components, to reach common goals” (Giusto, Lera, Morabito, &
Atzori, 2010, p. V). Based on the definition of CPS given above, “things” and
“objects” can be understood as CPS. Therefore, the IoT can be defined as a net-
work in which CPS cooperate with each other through unique addressing schemas.
Application examples of the IoT are Smart Factories (see explanation below),
Smart Homes, and Smart Grids (Bauernhansl, 2014, pp. 16–17).
4.1.3 Internet of Services
The Internet of Services (IoS) enables “service vendors to offer their services via
the internet. […] The IoS consists of participants, an infrastructure for services,
business models and the services themselves. Services are offered and combined
into value-added services by various suppliers; they are communicated to users as
well as consumers and are accessed by them via various channels.” (Buxmann,
Hess, & Ruggaber, 2009, p. 341). This development allows a new way of dynamic
variation of the distribution of individual value chain activities (Plattform
Industrie 4.0, 2013, p. 4). It is conceivable that this concept will be transferred
from single factories to entire value added networks in the future. Factories may
go one step further and offer special production technologies instead of just
production types. These production technologies will be offered over the IoS and
can be used to manufacture products or compensate production capacities (Scheer,
2013, p. 2). The idea of the IoS has been implemented in a project named SMART
FACE under the “Autonomics for Industrie 4.0” program initiated by the Federal
Ministry for Economic Affairs and Energy. It develops a new distributed
production control for the automotive industry. The project is based on a service-
oriented architecture. This allows the use of modular assembly stations that can be
flexibly modified or expanded. The transportation between the assembly stations
is ensured by automated guided vehicles. Both, assembly stations and automated
guided vehicles offer their services through the IoS. The vehicle bodies know their
customer specific configuration and can decide autonomously which working
steps are needed. Therefore, they can individually compose the required processes
through the IoS and autonomously navigate through the production (Fraunhofer
IML, 2014).
4.1.4 Smart Factory
“Smart factories constitute a key feature of Industrie 4.0.” (Kagermann et al.,
2013, p. 19). “The Smart Factory is defined as a factory that context-aware assists
people and machines in execution of their tasks. This is achieved by systems
working in background, so-called Calm-systems and context aware means that the
system can take into consideration context information like the position and status
of an object. These systems accomplish their tasks based on information coming
from physical and virtual world. Information of the physical world is e.g. position
or condition of a tool, in contrast to information of the virtual world like electronic
documents, drawings and simulation models. […] Calm systems are referring in
this context to the hardware of a Smart Factory. The main difference between
calm and other types of systems is the ability to communicate and interact with its
environment.” (Lucke, Constantinescu, & Westkämper, 2008, p. 115). Based on
the definitions given for CPS and the IoT, the Smart Factory can be defined as a
factory where CPS communicate over the IoT and assist people and machines in
the execution of their tasks. An example of a Smart Factory is the WITTENSTEIN
bastian’ production facility in Fellbach, Germany, which is organized according
to the principles of lean production. For the implementation of a demand driven
milk run, intelligent work piece carriers are used. They report when a work piece
is ready to be picked up and allow to initiate the milk run only if there is a de-
mand. This helps reduce the number of milk runs and relieve employees from un-
necessary work (Schlick, Stephan, Loskyll, & Lappe, 2014, p. 66).
4.2 Definition of Industrie 4.0
Based on the findings from the literature review, we define Industrie 4.0 as
follows: Industrie 4.0 is a collective term for technologies and concepts of value
chain organization. Within the modular structured Smart Factories of Industrie
4.0, CPS monitor physical processes, create a virtual copy of the physical world
and make decentralized decisions. Over the IoT, CPS communicate and cooperate
with each other and humans in real time. Via the IoS, both internal and cross-
organizational services are offered and utilized by participants of the value chain.
5 Industrie 4.0 Design Principles
The implications of the above presented results are now used to derive design
principles for Industrie 4.0 scenarios. These design principles support companies
in identifying possible Industrie 4.0 pilots, which then can be implemented. In to-
tal, six design principles can be derived from the Industrie 4.0 components (see
Table 2).
Table 2: Design principles of each Industrie 4.0 component
Internet of
Internet of
Interoperability X X X X
Virtualization X - - X
Decentralization X - - X
Real-Time Capability - - - X
Service Orientation - - X -
Modularity - - X -
The design principles are explained in the following by using the example of the
key finder plant of SmartFactoryKL. SmartFactoryKL is a vendor independent tech-
nology initiative settled at the German Research Center for Artificial Intelligence.
The demonstration plant was built in the course of the RES-COM project. It pro-
cesses parts for key finders and assembles them. The housing of the key finders is
equipped with a RFID tag that provides all production relevant data (Schlick et al.,
2014, pp. 74-75).
5.1 Interoperability
Interoperability is a very important enabler of Industrie 4.0. In Industrie 4.0 com-
panies, CPS and humans are connected over the IoT and the IoS. Standards will be
a key success factor for communication between CPS of various manufacturers.
The German Commission for Electrical, Electronic & Information Technologies
of DIN and VDE has recognized this need and published the “German Standardi-
zation Roadmap” in 2013. In the context of the SmartFactoryKL plant, interopera-
bility means that all CPS within the plant (workpiece carriers, assembly station,
and products) are able to communicate with each other “through open nets and
semantic descriptions” (SmartFactoryKL, 2014).
5.2 Virtualization
Virtualization means that CPS are able to monitor physical processes. These sen-
sor data are linked to virtual plant models and simulation models. Thus, a virtual
copy of the physical world is created. In the SmartFactoryKL plant the virtual mod-
el includes the condition of all CPS. In case of failure a human can be notified. In
addition, all necessary information, like next working steps or safety arrange-
ments, are provided (Gorecky, Schmitt & Loskyll, 2014, p. 535). Hereby, humans
are supported in handling the rising technical complexity (SmartFactoryKL, 2014).
5.3 Decentralization
The rising demand for individual products makes it increasingly difficult to con-
trol systems centrally. Embedded computers enable CPS to make decisions on
their own. Only in cases of failure tasks are delegated to a higher level (ten
Hompel, Otto, 2014, p. 6). Nevertheless, for quality assurance and traceability it is
necessary to keep track of the whole system at any time. In the context of the
SmartFactoryKL plant decentralization means that the RFID tags “tell” machines
which working steps are necessary. Therefore, central planning and controlling is
no longer needed (Schlick et al., 2014, p. 75).
5.4 Real-Time Capability
For organizational tasks it is necessary that data is collected and analyzed in real
time. In the SmartFactoryKL the status of the plant is permanently tracked and ana-
lyzed. Thus, the plant can react to the failure of a machine and reroute products to
another machine (Schlick et al., 2014, p. 75).
5.5 Service Orientation
The services of companies, CPS, and humans are available over the IoS and can
be utilized by other participants. They can be offered both internally and across
company borders. The SmartFactoryKL plant is based on a service oriented archi-
tecture. All CPS offer their functionalities as an encapsulated web service (Smart-
FactoryKL, 2014). As a result, the product specific process operation can be com-
posed based on the customer specific requirements provided by the RFID tag
(Schlick et al., 2014, p. 75).
5.6 Modularity
Modular systems are able to flexibly adapt to changing requirements by replacing
or expanding individual modules. Therefore, modular systems can be easily ad-
justed in case of seasonal fluctuations or changed product characteristics. In the
SmartFactoryKL plant, new modules can be added using the Plug&Play principle.
Based on standardized software and hardware interfaces (Schlick et al., 2014, p.
75), new modules are identified automatically and can be utilized immediately via
the IoS (SmartFactoryKL, 2014).
6 Conclusions
The paper contributes to the ongoing discussion centering around Industrie 4.0
within both the scientific and the practitioners’ community.
By providing a definition of Industrie 4.0, the paper creates a common
understanding of the term, which is needed for a reasonable scientific discussion
on the topic. The design principles derived from four basic Industrie 4.0 compo-
nents support academics in identifying, describing, and selecting Industrie 4.0
scenarios in the context of further investigations.
The paper’s practical contributions are twofold: First, the definition given
for Industrie 4.0 helps clarify the basic understanding of the term “Industrie 4.0”
among practitioners. Second, the six design principles can be used for implement-
ing Industrie 4.0 scenarios in companies. They help identify potential use cases
and offer guidance during implementation.
Limitations of the paper result from its scope and the research method
applied. As the focus is on German and English publications only, relevant contri-
butions in other languages might be left unnoticed. Furthermore, it is possible that
during the initial identification of search terms an important Industrie 4.0 related
topic might have been overlooked, leading to an incomplete list of keywords and,
consequently, to an imperfect definition of Industrie 4.0.
Researchers and practitioners are welcome to test the accuracy and use-
fulness of the definition given. Regarding the six design principles identified, fur-
ther research should challenge their utility by identifying, describing, and selecting
Industrie 4.0 scenarios from an academic or practical perspective. Since Drath and
Horch (2013) underline that “Industrie 4.0 is a phenomenon that will come inevi-
tably, whether we want it or not” (p. 58), both academics and practitioners are in-
vited to further enhance the paper’s contribution in order to make the idea of In-
dustrie 4.0 an integral part of future manufacturing and production processes.
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... • Interoperability enables vertical and horizontal integration [26,27]; • Modularity enables flexibility, agility, and product personalization [24,28,29]; • Vertical integration enables smart factories [30,31]; • Smart manufacturing enables digital end-to-end engineering [32]; • Virtualization of production systems depends on real-time capabilities [24,29]; • Decentralization can be achieved through smart products [29,32,33]. ...
... • Interoperability enables vertical and horizontal integration [26,27]; • Modularity enables flexibility, agility, and product personalization [24,28,29]; • Vertical integration enables smart factories [30,31]; • Smart manufacturing enables digital end-to-end engineering [32]; • Virtualization of production systems depends on real-time capabilities [24,29]; • Decentralization can be achieved through smart products [29,32,33]. ...
... • Interoperability enables vertical and horizontal integration [26,27]; • Modularity enables flexibility, agility, and product personalization [24,28,29]; • Vertical integration enables smart factories [30,31]; • Smart manufacturing enables digital end-to-end engineering [32]; • Virtualization of production systems depends on real-time capabilities [24,29]; • Decentralization can be achieved through smart products [29,32,33]. ...
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Small and medium enterprises (SME) face various challenges in order to remain competitive in a global market. Industry 4.0 (I4.0) is increasingly presented as the new paradigm for improving productivity, ensuring economic growth, and guaranteeing the sustainability of manufacturing companies. However, SMEs are ill equipped and lack resources to undertake this digital shift. This paper presents the digital shift process of an SME in a personalized mass production context. Our work provides a better understanding of the interaction between Lean and I4.0. It contributes to the development of Lean 4.0 implementation strategies that are better adapted to manufacturing SMEs in a personalized mass production context. We also demonstrate the usefulness of simulation as a decision-making assistance tool when implementing I4.0. A practical case is documented to fill a gap in the scientific literature identified by several researchers.
... Industry 4.0 is a term that has been discussed in the last ten years; initially, it refers to the integration between many emerging technologies with manufacturing [20]. Industry 4.0 can be considered as the new generation of industrial environments; it aims to reduce human intervention and efforts and replace them with an intelligent environment. ...
... Implementing these technologies varies from one industrial field to another; certain industries rely on the general product level. Thus they follow the idea of the Cyber-physical system (CPS), which is also called the cyber-physical production system (CPPS) [20]. Other environments are trying to narrow the range of technologies, such as those that integrate the Internet of Things ( IoT); these systems are called the Industrial Internet of Things (IIoT) [10]. ...
... CPS should fulfill many criteria for delivering a smart production system to support Industry 4.0. In the literature, several researchers are seeking to explore ways to combine CPS with Industry 4.0, including the study in [20]. 2) Internet of Things (IoT): IoT uses sensors and networking technologies to detect and relay data in real-time. ...
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Industry 4.0 relates to the digital revolution of manufacturing and other sectors, such as retail, distribution, oil and gas, and infrastructure. Meanwhile, the Industrial Internet of Things (IIoT) is a technological advancement that leads to Industry 4.0 implementation by boosting the manufacturing sector’s productivity and economic impact. IIoT provides the ability to provide global connectivity between components in different locations. The manufacturing sector has had various difficulties implementing IIoT, primarily due to IIoT characteristics. This paper offers an in-depth review of Industry 4.0 and IIoT, where the primary motivation behind this is to introduce the most recent advancements related to Industry 4.0 and IIoT, as well as to address the existing limitations. Firstly, this paper presents a novel taxonomy of IIoT challenges that includes aspects of each challenge, such as the terminology and approaches utilized to solve these challenges. Besides IIoT challenges, this survey provides an in-depth demonstration of the many concepts related to IIoT, such as architecture and use cases. Secondly, this paper provides a comprehensive review of the state-of-the-art of Industry 4.0 in terms of concepts, requirements, and supporting technology. In addition, the correlation between enabling technology and technical requirements is discussed in detail. Finally, this paper highlights deep learning, edge computing, and big data as key techniques for the future directions of IIoT. Furthermore, the presented techniques are thoroughly examined to present an alternative method for future adoption. In addition to the showcased techniques, a new architecture for the future of IIoT based on these three primary techniques is also proposed.
... He also introduces the fourth industrial revolution as Internet technologies that are integrated into various branches of industrial production. Hermann, Pentek and Otto (2015) point to the need for interconnection through information from both worlds, virtual and physical. The concept of digitization is a striking part of Industry 4.0, and it is used for horizontally integrated processes, which are indicated within values and their flow. ...
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The main purpose of the paper is the identification of Industry 4.0 (I4) in a selected sector of the Slovak economy with emphasis on a single case study in the company PSA, which is a key player in the market in the analysed automotive sector.. In the paper, three research questions are determined together with the methods through which the analysis is carried out, mainly the method of exploration, explanation and description using the secondary data, financial and annual reports published by the PSA and Slovak authorities. The crucial finding of the paper is the presentation of opportunities for value-added growth and a specific case study of PSA Group Slovakia and its application of the Industry 4.0 concept as a driving force for value-added growth in car exports. Based on the research outputs, the proposals and recommendations are proposed as a series of steps and recommendations for the Slovak Republic with the intention of becoming an innovative country.
... Implementation of the Industry 4.0 concept requires not only usage of high-tech and artificial intelligence but also well designed network infrastructure, sufficient analytics software and smart controllers to use available data properly. Within Industry 4.0 cyber physical systems communicate efficiently not only within enterprise but also outside it integrating companies with customers and other users [Hermann et al. 2015]. The concept makes use of modern IT tools, being based on flexible, decentralized and intelligent structures of production inspection [Lee et al. 2017]. ...
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Background: The following paper was developed to assess maturity levels in regards to sustainable development goals. Highly unstable business environment and opportunities occurring on the market require effective and quick decision making process. It is a challenge to follow such dynamic changes within and outside organization while maintaining sustainable goals. However authors state that this is possible thanks to modern concepts and available tools-Industry 4.0 concept or Business Intelligence to name only few. Those concept support making business decisions based on well gathered, analyzed data and setting sufficient strategy which promotes sustainable goals and allows organization to mature. Methods: Authors based their own maturity model on identified in literature maturity models and international standard: PN-EN ISO 9004:2000. Results: Authors have defined five maturity levels, each described with several features. On the basis of prepared tables one can define maturity level of organization. Additionally, further steps of development can be indicated and enforced in organizational strategy. Conclusions: Application of sustainable development within organizational maturity can mitigate reaching sustainable targets. It is important to understand relations between maturity level of organization and sustainable development goals. By improving its maturity, organization should in parallel develop further sustainable measures.
... The industrial revolution 4.0, often known as digitalization or the era of technology advancement, is a hot topic of discussion in numerous sectors of society at the moment. Industry 4.0 is now a reality, defined by cyberphysical systems, in which people connect and communicate via the internet (Hermann et al., 2015), (Irianto, 2017), (Harto, 2018). As a result, individuals increasingly rely on technology to meet their daily demands, such as online shopping, e-money, e-banking, and online transportation. ...
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Due to the COVID-19 pandemic, prospective elementary school teachers must be able to teach both online and offline using a blended learning model. The purpose of this study is to examine the fundamental teaching skills of prospective elementary school teachers in the Microteaching course. This study used qualitative descriptive method. The subjects were students of the Primary School Teacher Education Study Program in University of Nahdlatul Ulama Sidoarjo who programmed Microteaching courses. The data were collected using observations with a performance assessment rubric. Observations were conducted in two stages: first, when students practiced online teaching, secondly, when they practiced offline teaching. The results showed that online teaching skills obtained an average score of 84.71, while offline teaching skills obtained an average score of 85,78. Hence, prospective elementary school teacher students in the blended learning model received an overall score of 85,24, meaning that they were categorized as very good category
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Industry 4.0 implies a reconfiguration of work organization and new approaches to human resources management (HRM). This research aims to delve deeper into the impacts of Industry 4.0 on the human resources system (HRS). A literature review identifies the potential links between these two core concepts. Finally, secondary data analysis in the form of a literature review on topical scientific researches will explore the following research question: How does Industry 4.0 impact conventional human resources systems (HRS)?
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Teknolojik değişim, 4. Sanayi Devrimi'ni karakterize eden Bilgi İletişim Teknolojisinin (BİT) veya Dijital Ekonominin (DE) baskın bir rolü olarak hayatımızda yer almaya başlamıştır. Bu değişim özellikle BİT, dijital becerilere erişim ve kullanıma hususunu işgücü piyasalarında daha büyük bir ivme kazanmasına yol açmış ayrıca: yapay zekâ alanındaki gelişmeler; düşük maliyetli BİT fiyatları; artan internet penetrasyon oranları otomasyon potansiyelinin daha belirgin bir şekilde ortaya çıkmasına imkân sağlamıştır. McKinsey Global Institute (MGI) tarafından, otomasyonun işgücünü değiştirmek yerine dönüştürme olasılığı daha yüksek olduğu ifade edilmiştir ve mesleklerin %60'ın da yer alan görevlerin en azından üçte biri otomatikleştirilebilse de mevcut otomasyon teknolojileri ile mesleklerin %3'ünden daha azının tamamen otomatik hale gelebileceği belirtilmiştir ayrıca otomasyonun 2030 yılına kadar dünya ekonomisinin verimlilik düzeyine %0,3-%2,2 arasında katkı sağlayacağı vurgulanmıştır (McKinsey, 2018). Dijital Ekonomi, ticaret ve kalkınma için yeni fırsatlar yaratarak ülkelerdeki işletmelerin ve girişimcilerin, dijital platformlar aracılığıyla küresel pazarlarla daha kolay bağlantı kurmalarına yardımcı olmakta ve işletmelerin kâr marjlarını artırmaları noktasında yeni yollar açmaktadır. İktisadi faaliyetlerde artan dijitalleşme ve otomasyon olgusu, yeni iş ve istihdam türleri oluştururken ayrıca iş gücünün beceri gereksinimlerinin de değişmesine imkân sağlamıştır. Bu bağlamda, ülkelerin ve işletmelerin yeni dijital kaynaklardan yararlanma yetenekleri, rekabet güçlerinin önemli bir belirleyicisi olarak görülmektedir (Öztuna, 2017). Bu kapsamda ele alınan bu çalışmada Türkiye’de dijitalleşme sürecinin iş gücü piyasaları üzerindeki etki boyutunun incelenmesi amaçlanmıştır. Bu doğrultuda öncelikle giriş olarak ifade edilen bu bölümünden sonra dijitalleşme, işgücü piyasalarına yönelik kavramsal çerçeve sunulmuştur ardından söz konusu sürecin Türkiye üzerine yansımaları çözümlenmiştir. Sonuç kısmında ise genel değerlendirmelere yer verilmektedir
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The aim of the study is to identify, map and assess the maturity and impact level of the specific energy-oriented economy and other SMART management concepts and social, technological, finance (economical), environmental, and communication (S.T.F.E.C.) trends which arose from the dynamic development and spread of the Industry 4.0 revolution on processes of effective competitiveness and the creation of modern enterprises. The article presents data and information obtained thanks to an in-depth review of the literature (extensive desk research), as well as that obtained as part of the conducted CAWI pilot study. The authors aim to search for answers to three specific research questions, concluding that recently, special attention is paid to such issues as co-creation and co-production, energy-oriented and circular economy, eco-energy, and sustainability. The findings of this study clearly show that in the SMART WORLD era, there is a growing interest in cooperation, co-creation, co-production issues, and usage of modern technologies and SMART management concepts typical of the Industry 4.0 era. The main reason for this is that enterprises strive to optimize and maximize their efficiency in the processes of competitiveness creation. Researched data allows us to conclude that openness to social, environmental, and technological trends and issues, with an approach based on sustainable and eco-energy-oriented development, play an increasingly important role. However, the level of their importance, implementation level, and maturity differ depending on the type of organization or industry. For example, service and trade companies more often than production companies use and rate the usefulness of social trends higher (reality = mainstream orientation for S&T companies and a future orientation for production companies), while production companies apply a more balanced approach, showing greater commitment to economic technological, environmental and financial trends (reality = mainstream orientation for production companies and a future orientation for trade and services companies). Given that the study shows and describes preliminary research results (pilot studies), the authors plan to undertake further efforts in the in-depth scientific exploration of the issues concerned, including, which is particularly important, conducting full-scale research
A Indústria 4.0 é um dos conceitos que mais cresce em todo o mundo, combinando o mundo físico e digital, que tem modificado não apenas a indústria de manufatura e inovação, mas a todos os setores produtivos e organizações, criando perspectivas e possibilidades.No Brasil, esse processo caminha de forma lenta, principalmente pelas dificuldades encontradas pelas indústrias nacionais em investir em inovação para melhoria de seus processos. No entanto, impulsionada pela competitividade interna e principalmente a global, tem motivado estas indústrias a acelerar este processo por busca de inovação. Com base neste cenário, surgiram algumas iniciativas públicas que também estão sendo implantadas, tais como o Decreto nº 10.534, de 2020 que Institui a Política Nacional de Inovação, a instituição da Câmara de Inovação e a Câmara Brasileira da Indústria 4.0, demonstrando assim, o início de uma implementação de uma política de inovação tecnológica para o Brasil.Neste artigo, analisou-se por meio de pesquisa bibliográfica o conceito da Indústria 4.0, suas tecnologias e sua aplicabilidade na indústria nacional sob este contexto. Buscando identificar os desafios e as oportunidades dentro deste novo cenário.
Organizasyonların amaç ve hedeflerine ulaşmasında liderler ve davranışları hayati öneme sahiptir. Kendi çıkarlarını önceleyen ve ferdi hareket eden liderler birçok olumsuzluğa sebep olabilirken, ortak yaşamın kazanımlarından olan kültürel değerleri benimsemiş ve birlikte hareket etmeyi ilke edinmiş liderler hem kendileri hem de organizasyonları için faydalı çıktılar sunabilmektedir. Buradan hareketle, hayatın tüm alanları için önemli olan değer kavramı, bu kitapta liderlik kavramıyla birlikte araştırılmıştır. Alan yazınında liderlik çalışmalarına sıklıkla rastlanmaktadır fakat değer temelli liderliği konu alan çok az çalışma bulunmaktadır. Kitapta demokratik, hizmetkar, fedakâr, karmaşık, paylaşılan, ruhsal, otantik, etik, bilgi odaklı, babacan, ilham verici, yenilikçi, küresel, mizahi ve sorumlu liderlik kavramları değer temelli olarak ele alınmıştır.
Mit der Vernetzung von Produktionstechnologien und IT-Welt in der Industrie 4.0 steigt die Bedeutung von Software für den Maschinenbau. Am Beispiel der Lösung Open Core Engineering (OCE ) von Bosch Rexroth , werden die Möglichkeiten aufgezeigt, die sich aus der Verschmelzung von SPS-Automatisierung mit den Technologien der IT-Welt ergeben. Durch OCE, bestehend aus Softwaretools , Funktionspaketen und offenen Standards sowie der Schnittstelle Open Core Interface , können modular aufgebaute Produktionslösungen starre Produktionsketten ersetzen und die Effizienz für die Fertigung kleinster Stückzahlen steigern.
Dem Industrie 4.0-Paradigma folgend sind alle Gegenstände der Fabrikwelt mit integrierter Rechenleistung und Kommunikationsfähigkeit ausgestattet. Dies betrifft keineswegs nur die Maschine-zu-Maschine(M2M)-Kommunikation, sondern wird auch weitreichende Folgen für das Zusammenspiel zwischen Mensch und Technik mit sich bringen.
Mit einem Anteil von 22,4 Prozent am Bruttoinlandsprodukt (BIP) ist das produzierende Gewerbe das Rückgrat der deutschen Wirtschaft. (vergl. Bundesministerium für Wirtschaft und Technologie, 2013). Im Vergleich: der Anteil des produzierenden Gewerbes am BIP in den USA liegt bei 11,9 Prozent, in Frankreich und Großbritannien bei 10 Prozent (vergl. Heymann, Vetter, 2013). Jährlich produziert die deutsche Wirtschaft einen enormen Handelsüberschuss. Diese Wettbewerbsfähigkeit der deutschen Industrie war entscheidend, um die Finanz- und Wirtschaftskrisen in der jüngsten Vergangenheit erfolgreich zu bewältigen. Konkurrenzfähiger Industriestandort und führender Fabrikausrüster zu sein, muss jedoch immer wieder aufs Neue erarbeitet werden.
Industrie 4.0 verändert mit der Vernetzung von Produktionstechnologien und ITWelt die Spielregeln. An Stelle proprietärer Schnittstellen treten offene Standards, mit denen Maschinenhersteller neueste IT-Technologien eigenständig in ihre Konzepte einbinden. Der vorliegende Beitrag zeigt auf, wie diese Entwicklung mit Hilfe von Open Core Engineering unterstützt werden kann. Open Core Engineering steht für das komplette Engineering-Angebot von Rexroth, das die bislang getrennten SPS- und IT-Welten in einer durchgängigen Lösung verbindet und das 2013 mit dem HERMES AWARD ausgezeichnet wurde. Es bietet Maschinenherstellern neue Freiheiten, innovative Ideen in Software selbst umzusetzen.
Auf dem Weg zur Industrie 4.0 nahm die Logistik ähnliche Entwicklungsstufen wie die Produktion, welche sich ausgehend vom Neo-Taylorismus über die Lean Production nun im Rahmen der vierten industriellen Revolution dem Ideal der „Smart Factory“ annähert (vgl. Tabelle 1).
Der Begriff „Industrie 4.0“ ist in kürzester Zeit zu einem Buzzword geworden. Obwohl erst im zeitlichen Umfeld der Hannover Messe im April 2013 eingeführt, ist er heute in fast aller Munde.
Die Gedankenwelt um das Thema Industrie 4.0 resultiert originär aus dem Zusammenspiel zweier Trends. Einerseits die herausragende Bedeutung der industriellen Produktion für den Wirtschaftsstandort Deutschland (siehe auch Reinhart und Abele, 2011), andererseits die fortschreitende Miniaturisierung und Integration von Computerchips, die in Folge die Vision des „Ubiquitous Computing“ zur Realität werden lässt (siehe Weiser, 1991). Das Internet der Dinge und Dienste schließt den Medienbruch zwischen dinglicher und virtueller Welt und ermöglicht das Anbieten von Mehrwertdiensten auf der Basis eines aktuellen und umfassenden Abbilds der Realität.