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INDUSTRIAL COMMUNICATIONFOR FACTORIES
BUILDING BLOCKS FOR A SECURE REAL-TIME COMMUNICATION AND COMPUTING INFRASTRUCTURE FOR INDUSTRY 4.0
WHITE PAPER
32
IMPRINT
“Building Blocks for a Secure Real-Time Communication and Computing Infrastructure for Industry 4.0” White Paper
Version 1.0 (April 2018)
“Industrial Communication for Factories” (IC4F).
Published by the partners of the projectIndustrial Communication for Factories (IC4F).
Internet: www.ic4f.deE-mail: [email protected]
EDITORIAL TEAM:
Erich Zielinski, Fraunhofer Heinrich Hertz Institute, Berlin, GermanyFelix Beierle, Technische Universität Berlin, GermanyHans-Werner Bitzer, Deutsche Telekom AG, Bonn, GermanyKnut Drachsler, GPS Gesellschaft für Produktionssysteme GmbH, Stuttgart, GermanyBernd Holfeld, Fraunhofer Heinrich Hertz Institute, Berlin, GermanyHarald Klaus, Deutsche Telekom AG, Bonn, GermanyMathias Mormul, Universität Stuttgart, GermanyAndreas Müller, Robert Bosch GmbH, Renningen, GermanyKaroline Saatkamp, Universität Stuttgart, GermanyChristian Schellenberger, Technische Universität Kaiserslautern, GermanyJulius Schulz-Zander, Fraunhofer Heinrich Hertz Institute, Berlin, GermanySlawomir Stanczak, Fraunhofer Heinrich Hertz Institute, Berlin, GermanyEdwin Sutedjo, Nokia Solutions and Networks, Munich, GermanyMatthias Wieland, Universität Stuttgart, GermanyAlexander Willner, Technische Universität Berlin, GermanyFlorian Zeiger, Siemens AG, Munich, GermanyMarc Zimmermann, Technische Universität Kaiserslautern, Germany
CONTACT:
Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute, HHI, Einsteinufer 37, 10587 Berlin, Germany
Layout: LoeschHundLiepold Kommunikation GmbH
PICTURE CREDITS:
Nico ElNino – iStock (Title) pressmaster– Fotolia (p. 11) scandinaviastock – Fotolia (p. 12) sdecoret – Fotolia (p. 16) vectorfusionart – Fotolia (p. 19) PhonlamaiPhoto – iStock (p. 27)
EXECUTIVE SUMMARY
The flagship project “Industrial Communication for Factories”
(IC4F) is working on a secure communication and computing
infrastructure with real-time capabilities for Industry 4.0. The
project is part of the PAiCE program of the German Federal
Ministry for Economic Affairs and Energy (BMWi).
The IC4F project develops a RAMI 4.0-compliant reference
architecture for industrial communication. Specifically, on a
high abstraction level, IC4F considers two layers:
• The ICT infrastructure layer provides wireless or wired
access to all kinds of objects on the shop floor and con-
nects them with cloud resources in the different network
domains.
• The application and data layer includes factory applica-
tions, data models, data management, data analytics and
data visualizations, as well as artificial intelligence and
machine learning algorithms.
Moreover, an overarching security framework protects both
layers.
The IC4F project proposes building blocks, which allow
implementing Industry 4.0 use cases in an efficient and
flexible manner and to realize use case patterns with similar
requirements. These building blocks define packages of
functionalities to meet business needs. The building blocks
are described by templates, which include a description
of the functionality and context, exposed public interfaces,
interoperability, service parameters, and possible implemen-
tations. An Industry 4.0 ICT architecture can be built up from
a collection of interoperating building blocks.
In order to define building blocks, available and upcom-
ing technologies in the field of ICT, applications, and data
must be analyzed. This includes technology domains such
as cloud computing in an industrial environment, virtual-
ization and industrial edge computing, 5G radio and 5G
core network, big and fast data analytics, as well as artificial
intelligence and machine learning algorithms. The analysis
includes mechanisms for secure and reliable connectivity in
production, secure wireless communication and processes,
massive sensor data analysis, and (virtual) network elements
like secure gateways.
This whitepaper briefly outlines the following four specific
use cases and describes how they can be implemented
based on the technologies and the building block approach
developed by IC4F:
• Remote machine access
• Automated Guided Vehicles (AGVs)
• Massive wireless sensor networks
• Mobile operation & control with ultra-reliable machine
communication
During the project, the IC4F consortium will present a proof-
of-concept implementation in real-world industrial environ-
ments for relevant use cases, including the four use cases
mentioned above.
54
1. INTRODUCTIONCONTENTS
German politics and leading industry associations togeth-
er with research and development from companies and
academia provide the foundation for concerted action in
digitizing the industrial production process. Combining the
organizational assets of all stakeholders will accelerate the
speed at which the goal of fully connected factories of the
future can be reached.
In addition to its global goal, the project was also devised
with Germany’s competitiveness in mind. Germany has a
unique landscape of small and medium-sized enterprises
(SMEs) that account for about 95 % of the entrepreneurial
forces. German companies are internationally recognized
for their innovative products and for their efficient use and
production of both tools and technologies for industrial pro-
duction worldwide. Accordingly, continuously improving and
enhancing Germany’s leading position in smart production
and cutting-edge products as well as the return of produc-
tion facilities from foreign sites are goals pursued by the
Industry 4.0 initiative that is governed by public and private
research projects.
Implementing the vision of Industry 4.0 requires a holistic
view of the underlying infrastructure – a type of industrial
Internet/Intranet – taking into account technical possibilities
adapted to industrial requirements. This new industrial com-
munication infrastructure that enables platforms and applica-
tions will become an important economic factor.
Just recently, the telecom industry radically transformed itself
by merging communication with information technologies.
Communication technology performance has increased
significantly over time, virtualization is reducing costs, and
the fifth generation of mobile networks (5G) is expected to
generate even more momentum.
The use of ICT technologies in the automation and manufac-
turing domain, including the required adaptations to industry
requirements, will bring tremendous benefits:
• Boost performance of production facilities thanks to tight
monitoring and configuration of equipment, e.g. condition
monitoring, predictive maintenance, digital twin of the
factory in real-time.
• Close alignment of production and business processes,
e.g., product customization and “hyper-personalization”
through flexible (re-)configuration of production facilities.
• Connectivity of all objects in a heterogeneous environment
and supporting both standardized and proprietary inter-
faces (interworking based on standards).
• Improved collaboration and increased confidence between
business partners along the value chain (e.g., suppliers,
distributors, tier-x) by quality-assured, secure and in-time
connectivity inside factories within and across factory
boundaries.
Convergence between Operational Technology (OT), Infor-
mation Technology (IT), and Communication Technologies
(CT) seems to be the way to reach the goals set for the
digitization of industrial production, and several initiatives
Executive Summary 3
1. Introduction 5
2. Analysis of Use Cases 8
3. Challenges and Requirements for the Building Block Approach 10
4. New Technologies and Functionalities for the Smart Factory 134.1. Cloud – Computing and Virtualization 134.2. 5G – The Communication Network for the Cloud Era 144.3. Data – Driving the Smart Factory 16 4.4. Security – Protecting the Smart Factory 18
5. Reference Architecture and Building Block Approach 205.1. The IC4F Reference Architecture 205.2. The IC4F Building Block Approach 23
6. Application of Building Blocks in Demo Scenarios 276.1. Remote Machine Access 286.2. Automated Guided Vehicles 286.3. Massive Wireless Sensor Networks 306.4. Mobile Cooperation and Control with Ultra-Reliable Machine Communication 31
7. About the IC4F Project 32
References, Abbreviations 34
76
worldwide have started to work towards this goal, e.g., the
Industrial Internet Consortium (IIC) or the Plattform Industrie 4.0.
The flagship project “Industrial Communication for Factories”
(IC4F), as part of the PAiCE program of the German Federal
Ministry for Economic Affairs and Energy (BMWi), is working
on a RAMI 4.0-compliant reference architecture for industrial
communication systems and is creating building blocks for
industrial communication systems that can be used in facto-
ries. The proposed building block approach addresses SMEs
as well as large enterprises, providing them with a basis to
develop tailor-made solutions for future Industry 4.0 use cas-
es. IC4F applies the proposed approach and validates tech-
nologies, along with interworking and integration in different
and representative demonstrators. Figure 1.1. visualizes the
focus and the goal of the IC4F project, i.e., the convergence
of OT, IT and CT.
The IC4F approach is based on a thorough analysis of in-
dustrial use cases from three main sources: the IC4F project
partners, the Industry 4.0 platform, and the workshops
conducted together with industrial application partners of
IC4F’s user forum. Use cases of interest are identified on the
basis of criteria such as “demanding industrial requirements”,
“clear request for new technologies”, and “enabling of new
business opportunities”.
As a result, the ICT and compute infrastructure have to meet
challenges and requirements along the following lines:
• Every object on the shop floor gets connected
• Objects become mobile – the shop floor goes wireless
• Artificial Intelligence (AI) in production
• Fast and reliable communication for machine and process
control – digital twin of the factory in real-time
• Automated deployment and operations
• Comprehensive and scalable secure communication and
data handling in industrial domains and processes
To implement use cases in these domains, we analyze avail-
able and upcoming technologies in the field of ICT, applica-
tions and data. In particular, cloud computing in an industrial
environment, virtualization and industrial edge computing,
5G (radio access and core network), analytics with big and
fast data, and AI technologies are investigated. Functionali-
ties, performance parameters and interfaces that enable new
use cases are emphasized.
The analysis also includes existing and innovative mecha-
nisms for secure connectivity in production, secure wireless
communication and secure processes as well as massive
sensor data analysis. In doing so, we take into account new
functionalities (e.g., role dependent and task-dependent
data handling, scalable security services) and dedicated (vir-
tual) network elements like security gateways and industrial
edge clouds.
Our aim is to establish an architecture that is able to de-
scribe the overall ICT and compute infrastructure for specific
use cases. To this end, we link the functionalities described
above to different levels of the architecture so that use case
patterns with similar requirements can be addressed. The
functionalities are viewed as building blocks on different ar-
chitectural levels and this is referred to as the IC4F building
block approach. The highest level (reference architecture) is
very similar to generally accepted approaches like RAMI 4.0
and IIRA. However, the building block approach enables the
step-by-step implementation of specific use cases.
Finally, we will present four examples of uses cases based on
the technologies and the building block approach assessed
by IC4F:
• Remote machine access
• Automated guided vehicles
• Massive wireless sensor networks
• Mobile operation & control with ultra-reliable machine
communication
The IC4F consortium is planning to implement a proof-of-
concept in an industrial environment for relevant use cases
including the four described above.
The overall picture of the addressed domains of industrial
communication is highlighted in Figure 1.2.
FIGURE 1.2.: HIGH-LEVEL REPRESENTATION OF THE COMMUNICATION DOMAINS ADDRESSED BY IC4F.
I C 4 FP R O J E C T
C T
MobilityCollaboration
SecurityPerformance,e.g., Real-Time
5G, TSN, Virtualization,...
I T
FlexibilityCost Reduction
SecurityFast Data, auto. Deployment
Mobile Edge Cloud
O T
EfficiencyConsistency, Continuity
SafetyDigital Twin in Real-Time
Industrial Edge Cloud
FIGURE 1.1.: FOCUS OF THE IC4F PROJECT.
I N T E R N E T
P U B L I C C L O U D
E N D - T O - E N D ( E 2 E )I N D U S T R I A L S L I C E Q o S V I A P U B L I C I N F R A S T R U C T U R E
M U LT I - O P E R AT O R E N V I R O N M E N T
FA C T O RY A
FA C T O RY B
R E M O T E O P E R AT I O N S C E N T E R
E N T E R P R I S E C L O U D
P U B L I C / P R I VAT E H Y B R I D C L O U D
FA C T O RY
M O B I L E D E V I C E S
E D G E C L O U D
N E W I I o T AUTHENTICATION M E C H A N I S M S
A P P L I C AT I O N P R O G R A M M I N G I N T E R FA C E ( E R P / M E S / P M / C I M / C A X )
A U T O M AT I O N G AT E WAY( O P E R AT I O N A L T E C H N O L O G Y )
P R I VAT E 4 G / 5 G B A S E S TAT I O N W I T H A L O C A L G AT E WAY, I N T E G R AT E D PA A S , I I o T P L AT F O R M A N D A N A LY T I C S
R E A L - T I M E R E M O T E M A I N T E N A N C E A N D C O N T R O L
P R I VAT E 4 G / 5 G L O C A L W I R E L E S S A C C E S S P O I N T
U N L I C E N S E D A N D S U B L I C E N S E D S P E C T R U M
I N T E G R AT E D H I G H A C C U R A C Y I N D O O R P O S I T I O N I N G ( H A I P )
P U B L I C 4 G / 5 G N E T W O R K C E RT I F I C AT E A U T H O R I T Y F O R I N D U S T R I A L C O M M U N I C AT I O N
98
2. ANALYSIS OF USE CASES
A major objective of the IC4F project is to help enterpris-
es to implement the industrial use cases enabled by new
technologies. Many definitions for the term industrial use
case can be found in literature. We prefer the definition put
forward by Cockburn [1]: “A use case captures a contract
between the stakeholders of a system about its behavior and
describes the system’s behavior under various conditions as
it responds to a request from one of the stakeholder.”
We used the following sources as a basis for analyzing indus-
trial use cases:
• Use cases from the IC4F application partners and
associated partners.
• The IC4F User Forum, which includes more than 30 mem-
bers from academia and industry, for discussing Industry
4.0 use cases and future solutions.
• The Plattform Industrie 4.0 [2], which includes hundreds of
use cases that were filtered for analysis according to the
field of production and logistics.
For our use case analysis, we especially considered new,
innovative use cases representing a trend in the field of
Industry 4.0. We also included use cases with demanding
industrial requirements to communication technologies
beyond the state-of-the-art in our investigations. Based on
the key priorities mentioned by EFFRA [3], IC4F defined four
use case clusters in order to structure the use cases to be
analyzed (shown in Figure 2.1.):
• The “Value Chain Integration” cluster which includes
optimized processes and new business models along the
industrial value chain.
• The “Production Information Transparency” cluster which
focuses on the digital twin of processes and conditions in
the factory for improving productivity and efficiency.
• The “Versatile Production” cluster which deals with pro-
duction for user-specific products (e.g., lot size of one) and
products with a short lifecycle.
• The “Augmented Worker” cluster which supports humans
as actors in the field of production through assistance
systems.
As a result of the discussion with industrial users especially,
the use cases listed below that combine several charac-
teristics are expected to increase their performance in this
context or will only then be enabled:
• Use cases that include mobile smart objects which need
to exchange data with other objects and which cannot be
wired easily (e.g., transport vehicles, mobile robots, rotat-
ing machine components).
• Use cases that need real-time transfer of high data vol-
umes (e.g., acoustic or video data or data from a swarm of
numerous sensors) between different locations/companies.
• Use cases that need ultra-high reliable wireless data (safety
and low latency requirements).
• Use cases where wireless exchange of data at a high secu-
rity level plays an important role.
The analysis within IC4F provides a clear picture of the
concerns of stakeholders in future Industry 4.0 use cases
and alignes the results of IC4F’s work on architecture with
the relevant audience at SMEs and large enterprises. The
stakeholder concerns recorded also allow the IC4F project
to derive and prioritize requirements, directly influencing
the design of the IC4F implementations. Project results also
include prototypes showing the proof-of-concept in repre-
sentative real-world demonstrators. The IC4F demonstrators
focus on the clusters “Value Chain Integration”, “Production
Information Transparency”, and “Versatile Production” with
FIGURE 2.1.: FOUR USE CASE CLUSTERS WITH RELEVANCE TO NEW INDUSTRIAL COMMUNICATION TECHNOLOGIES.
clear mapping (cf. Section 6 for a more detailed description
of IC4F demonstrators):
• “Value Chain Integration” is represented by the
“Automated Guided Vehicles” use case.
• “Production Information Transparency” is represented by
the “Remote Machine Access” use case and the “Massive
Wireless Sensor Networks” use case.
• “Versatile Production” is represented by the “Mobile
Cooperation & Control with Ultra-Reliable Machine
Communication” use case.
VA L U E C H A I N I N T E G R AT I O N
V E R S AT I L E P R O D U C T I O N
P R O D U C T I O N I N F O R M AT I O N T R A N S PA R E N C Y
A U G M E N T E D W O R K E R
1110
3. CHALLENGES AND REQUIRE-MENTS FOR THE BUILDING BLOCK APPROACH
From the previous discussion of the use cases, it becomes
obvious that use cases come in different shapes and siz-
es. Likewise, there are also many different ways to tackle
underlying communication requirements. In this section, the
use cases will be revisited to identify common denominators
and a set of generic requirements that will drive technology
selection and architecture for industrial networks.
Everything becomes Connected
An essential property Industry 4.0 will be a new communica-
tion pattern. While a high degree of automation is already
state of the art in factories, Industry 4.0 adds the ability to
seamlessly exchange data between the factory network
and the rest of the enterprise. Ubiquitous connectivity and
easy data exchange and access will be established between
the internet, the intranet, and the shop floor. This will pave
the way for tighter integration between factory control and
business processes.
The Shop Floor goes Wireless
A close interlock between business and factory only makes
sense when the factory can adapt to different business
needs – also in the physical world. If, for instance, a new
product is to be launched, production will be executed by
flexible robots, creating a new production island on demand
rather than restructuring the entire static factory line.
To exploit the possibilities of seamless communication
between machine control and business processes, physical
flexibility on the shop floor is needed in order to allow for
the free flow of production equipment and material. From a
communication point of view, wireless connections should
be used to avoid the spatial constraints of fixed cabling.
High Bandwidth for Video
Outside the industrial context, the main performance charac-
teristic typically associated with a wireless network is band-
width, i.e., the amount of data transferred per time. While
use cases with high bandwidth requirements, such as video
surveillance, may also exist in a factory, bandwidth as such is
not expected to be a main driver in industrial networks.
High Device Density for Sensor Networks
One goal of the industrial factory network is the ability to
obtain deep insights into production processes by gather-
ing and analyzing data from many sensors. The number of
sensors that can be connected simultaneously is an impor-
tant performance parameter. The energy consumed by the
wireless connection should be minimized in order to enable
a long battery lifetime. This is where truly wireless sensors
without a wired power supply become feasible.
Fast and Reliable Communication for Machine Control
In factory automation, the amount of data to be transferred is
typically low, but the time between sending a message and
reception of the message (referred as latency) is of uttermost
importance. Predictability of latency allowing constant cycle
times within a production network is even more important
than low absolute latency. With higher, but predictable laten-
cy, a production process can still operate at a lower speed.
In the case of unpredictable latency, the entire production
could be disrupted resulting, for instance, in the need for a
machine safety stop. Low and predictable latency is addressed
by ultra-reliable low-latency communication. Besides factory
automation, tools that use Augmented Reality (AR) depend
heavily on low latency in order to achieve the targeted level
of usability and experience.
Hierarchical Infrastructure to Support Different Use Cases
In addition to wireless transmission, the timing requirements
of a use case must also include data processing. If a use case
requires low latency between event and action, process-
ing will have to be executed as close to wireless access as
possible. Collocation of access node and compute resource
is referred to as edge computing. It is used for communica-
tion and processing needs of objects connected to the same
edge computing instance, i.e., for a rather limited spatial
area only, such as a shop floor. Use cases that utilize data
from objects distributed over a larger spatial area require
can benefit from processing hierarchical cloud infrastructures.
In some use cases, both requirements may even co-exist.
Sensor data is utilized in edge computing to enable shop
floor automation, and the same data can be used together
with data from other shop floors, e.g., for analytics-based
process optimization in a central cloud. This means that a
factory network will consist of a hierarchy of compute re-
sources that are located so that the different needs in terms
of speed and spatial requirements can be covered.
Sharing Infrastructure between Use Cases and Tenants
In a real factory setup, several use cases owned and operat-
ed by different business entities and with different communi-
cation requirements will run on the same physical infrastruc-
ture. The difficulty in these multi-tenant scenarios is how to
optimize two contradicting properties. On the one hand, re-
sources should be pooled (“shared”) between different use
cases and tenants to enable the best-possible utilization of
resources. On the other hand, resources should be isolated
and dedicated to allow use case-specific optimizations and
ensure that resources are available when needed. The con-
cept of network slicing allows the virtual network embedding
in a common physical network.
Automated Deployment and Operation
Factory networks are complex. A manifold of use cases re-
sulting in different requirements, a rich choice of technology
options, and various possibilities for deploying these on a vir-
tualized hierarchical infrastructure will have to be considered.
Furthermore, an industrial network is not static.
1312
All of the above factors change over time and factory
networks need to adapt to these changes. A high degree
of automation is therefore a very important requirement for
the setup and operation of factory networks. The employed
ICT automation framework (not be confused with the
cyber-physical automation taking place on the shop floor)
must comprise deployable (“virtualized”) functions used to
build the factory network, a deployment system that pushes
these functions on the infrastructure, and an orchestration
framework that generates the required communication links
between these functions.
Security
In the context of Industry 4.0, security is becoming even
more important. In the past, automation networks were iso-
lated from the rest of the world, thus offering rather limited
points of attack. With the expansion of the Internet to the
cyber-physical domain, attack scenarios familiar from the In-
ternet are becoming relevant. An intruder does not have to
be inside the factory in order to launch an attack. Instead, a
hacker can launch the attack via a cloud system and corrupt
or even hijack a production environment from there. To pre-
vent scenarios like these, security must be an integral part of
an industrial network where communication only takes place
between verified identities and where end-to-end protection
is used. Furthermore, a fine granular access management
system is needed to limit access to resources to eligible
entities only.
Compatibility with Legacy and Heterogeneous
Environments
Although a consistent and uniform rollout of an industrial
network according to the described ideal requirements is
desirable, the reality is sure to be different. Existing equip-
ment, purchased before the dawn of Industry 4.0, will have
to continue to operate together with “native” Industry 4.0
equipment.
F U N C T I O N A L
C O N N E C T E V E RY T H I N G
W I R E L E S S A C C E S S
D I S T R I B U T I O N F O R L O C A L H I G H - S P E E D
C E N T R A L I Z AT I O N F O R G L O B A L S C A L E
O P E R AT I O N A L
A U T O M AT I O N
M U LT I - T E N A N C Y
S E C U R I T Y
C O M PAT I B I L I T Y
FIGURE 3.1.: MAIN FUNCTIONAL AND OPERATIONAL REQUIREMENTS FOR INDUSTRIAL NETWORKS
4. NEW TECHNOLOGIES AND FUNCTIONALITIES FOR THE SMART FACTORY
The IC4F project analyzes available and upcoming technolo-
gies in the field of ICT, applications, and data.
4.1. Cloud – Computing and Virtualization
Cloud Computing in Industrial Environments
The majority of the Industry 4.0 use cases [2] discussed aim
for flexible production and optimized efficiency through ad-
vanced data analytics, so that these use cases depend heav-
ily on cloud computing capabilities. Today, state-of-the-art
solutions connect machine data sources to industrial cloud
backend systems and much effort goes into establishing
communication solutions that follow standards that comply
with industrial requirements, e.g., OPC UA. Current research
is now exploring the integration of backend and edge-cloud
systems in an industrial context in order to enable seamless
interaction of on-site cloud deployments (e.g., industrial
edge clouds) and industrial backend cloud systems.
Virtualization & Industrial Edge Computing
Edge computing approaches in service provider infrastruc-
tures and IT/communication networks leverage the process-
ing power available at the edge of the network, e.g., by
providing processing power and/or storage close to the
edge of networks.
Mapping existing mobile edge computing approaches to
the industry domain reveals unanswered questions and chal-
lenges since edge computing resources in today’s approach-
es are still located away from production and shop floor
environments (introducing additional constraints with respect
to real-time requirements), or do not support the industrial
communication protocols required in OT.
The concept of an industrial edge cloud introduces a heter-
ogeneous resource pool for processing power and virtual-
ization (NFV, virtual networks, virtual working environments)
on the shop floor. Of course, the resource pool needs to
support key industry requirements, such as stringent QoS
requirements, redundancy concepts, safety features, or
industrial communication protocols. Industrial edge clouds
therefore allow for an efficient use of shared resources in OT
environments with a strong focus on safe, secure and reliable
industrial processes.
Physical resources are available to different stakeholders/
actors who can use their “own” virtual resources according
to the given agreements, but without interfering with other
actors’ resource assignments, and virtualization offers a suit-
able trade-off between resource pooling (shared use of phys-
ical resources) and isolation (stakeholders can use assigned
logical resources independent of each other). Mapping fea-
ture requests from Industry 4.0 use cases to industrial cloud
concepts shows that scenarios also foresee a service setup
across cloud instances, e.g., services, virtual tenant networks
or virtual work spaces connecting resources from industrial
edge clouds to “traditional” enterprise or public clouds.
1514
4.2. 5G – The Communication Network for the Cloud Era
Cellular mobile networks have been driven by the needs
of human communications evolving from voice and data
communication networks provided by 2G and 3G networks
towards the mobile web in LTE. While LTE already includes
some elements, such as narrowband communication, that
target communication between machines, 5G [4] is especial-
ly designed for the Internet of Things and to fulfill the need
of vertical industries. It consists of a 5G New Radio (NR)
interface and enhancements to the core network, needed
5GC. While 5G NR provides the technical basis in terms of
the performance needed for the wireless transmission link,
5GC with its service-based architecture enables the agile
and intent-driven deployment of the network according to
the requirements of specific use cases.
5G Performance
The performance of 5G systems can be summarized as
follows:
• eMBB - enhanced Mobile Broadband: data volumes reach
10 Tbps/km² and peak rates of 10 Gbps
• mMTC - massive Machine Type Communication: high IoT
device density of 1 million/km2 and optimized energy con-
sumption targeted at 10 % of LTE reference
• URLLC - ultra-reliable low-latency communication: one-way
latency below 1 ms, reliability of five 9’s and high mobility
5G New Radio – Design Principles
With regard to the wireless transmission of data, the above
goals for performance are to be achieved with the following
main technical design principles (among others):
• Increase overall wireless link capacity: New spectrum
options from approx. 400 MHz to 100 GHz in licensed
and unlicensed bands will be available and utilized by
ultra-small up to macro cells.
• Decrease latency: Very short packet lengths can be used.
• Increase reliability: The same data is submitted in a
redundant fashion using multiple channels (referred to as
diversity), utilizing, for instance, different frequency bands,
antennas or access points. The latter point is especially im-
portant with a view to reliability when devices are handed
over from one cell to another.
From an architectural point of view, the access points are
split into two components called Remote Unit (RU) and
Central Unit (CU). While the RUs hold the radio interface,
the CUs are responsible for controlling the radio resources
from several RUs. The CUs can be deployed as virtualized
functions on an industrial edge cloud, for instance, and in
this way complements the service-based architecture of the
5GC, which is explained below.
5G Core – Service-Based Architecture
The essence of 5G’s service based architecture (SBA) can be
described by the following three principles:
• Following the paradigm of software-defined networking
(SDN), network elements are completely decoupled into
software and hardware. The software parts are provided
in the form of virtualized network functions (VNFs) as part
of the network function virtualization (NFV) concept. They
are developed following cloud native design patterns
(like micro services or stateless operations) and are thus
well-suited for deployment on edge or central clouds (re-
ferred to as a 5G multi-layer cloud architecture).
• Dynamic interaction between network functions, which
replace the static point-to-point connections between net-
work elements in traditional networks, is achieved through
service-based interfaces that use HTTP 2.0 transport. The
new 5G Network Repository Function (NRF) takes care of
service registration and discovery.
• The network exposure functions offer Application Pro-
gramming Interfaces (APIs) that enable external entities,
like factory operators, to control and monitor network
policies on an individual device basis.
With the help of the above properties, it is possible to in-
stantiate a set of network functions to form a complete net-
work so that the requirements of a predefined use case can
be fulfilled. With this technique, known as network slicing,
different logical networks – extending from device to data
processing – can be deployed on top of one physical infra-
structure, with each slice optimized with respect to different
performance criteria such as latency or bandwidth.
Bridging the gap from use cases with real world require-
ments to a tailored connectivity service is achieved with the
help of Service Level Agreements (SLAs) that describe the
S L I C E # 1( e . g . , U R L L C )
S L I C E # 2( e . g . , e M B B )
S L I C E # N
S E R V I C E L E V E L A G R E E M E N T S
T O P O L O G Y, Q O S , R E L I A B I L I T Y
U S E C A S E S
R E A L W O R L DR E Q U I R E M E N T S
S E R V I C E L E V E L
D E F I N E
R E Q U E S T S V I RT U A L N E T W O R K
N E T W O R K L E V E L
I N S TA N T I AT E S S L I C E
R E S O U R C E L E V E L
O F F E R S R E S O U R C E S A N D F U N C T I O N S
V I RT U A L I Z E D R E S O U R C E S
A N D N E T W O R K F U N C T I O N S
S E R V I C E M A N A G E M E N T
FIGURE 4.1.: GENERATION OF NETWORK SLICES BASED ON USE CASE REQUIREMENTS
requirements of the use case in a formalized way. These
SLAs are passed to a service management entity that selects
appropriate resources from the resource pool and deploys
virtualized network functions. In this way, network slices
optimized for the respective use case can be generated in an
automated fashion (shown in Figure 4.1).
1716
4.3. Data – Driving the Smart Factory
Architecture for Smart Data
One major challenge is the implementation of an architec-
ture for big and fast data that enables all the steps in the
MAPE loop (Monitoring, Analysis, Planning, and Execution)
and that addresses the required latency and volume of data
processing. Furthermore, this architecture must be able to
support the different steps, which are to be executed to a
certain degree in the edge, in order to allow preprocessing.
In addition, the data from different edge environments in a
cloud architecture must be centrally aggregated. There are
existing architectures for centralized big data implementa-
tions, for instance, the Lambda and the Kappa architecture.
However, in the case of Industry 4.0, the focus of interest is
shifting from the notion of big data to the idea of distribut-
ed smart data. Cyber-physical systems typically use sensors
to obtain the situation, condition, and movement data of
artifacts (processes, machines, equipment, and products) on
the shop floor. This data can then be fed into an engine that
not only allows fast, real-time, streaming-based processing
but also stores relevant sensor data to consider the current
and historical digital representation of the given artifact. This
results in a data-driven production with learning capability, in
which observed behavior is used by prediction mechanisms.
Analytics in the Smart Factory
The future shop floor will contain a large range of sensors
ranging from temperature, humidity, audio, or light to video
and location data streams from moving vehicles or robots.
Such massive sensor networks act as enablers for a variety
of specific use cases or applications for controlling machines,
monitoring, anomaly detection, visualization, or long-term
data analysis. Different scenarios pose different requirements
for the building blocks of the system. Training machine
learning models on large amounts of collected sensor data is
a big data scenario, while video stream analysis from moving
robots poses low-latency requirements.
Artificial Intelligence and Machine Learning in the
Smart Factory
Modern communication networks and massively deployed
sensor networks, in particular, collect, generate and pro-
cess a huge amount of data. Reliable and efficient access
to this data in real-time will accelerate the advancement
of AI/ML technologies for use in the context of Industry
4.0. In addition to enabling new industrial applications and
businesses, these technologies will help to cope with the
hugely increased complexity of communication networks, for
instance, they will enhance their efficiency and robustness by
enabling new communication technologies and by making
the vision of self-organizing networks reality. ML technolo-
gies are expected to provide robust predictions that are not
only a basis for industrial applications, such as predictive
maintenance, but are also a key ingredient in the design of
ultra-reliable low-latency communication networks.
Since the importance of wireless communication for indus-
trial applications is constantly increasing, new AI/ML tech-
nologies will have to be developed for big data analytics
in wireless networks. These technologies need to take into
account the limitations of wireless networks (e.g., limited
bandwidth, severe limitations on battery capacity and com-
puting power, etc.) to fully exploit their inherent properties.
The main challenges posed by wireless networks include the
high mobility of mobile devices, which leads to changes in
network topology. In addition, noisy, capacity-limited wire-
less links are generally exposed to interference, making them
error-prone and unreliable.
The limitations of wireless networks together with the fact
that data is distributed at different geographical locations
call for the development of distributed AI/ML methods of
low-complexity for the efficient use of scarce wireless re-
sources. While being amenable to real-time implementation,
the methods envisioned will have to have good tracking ca-
pabilities and provide robust results based on relatively small
data sets and under strict latency constraints. In order to
achieve these goals, and also to meet the stringent require-
ments of many industrial applications, it is essential that the
rich structure of the wireless channel and the propagating
signals are exploited while the context information and ex-
pert knowledge is incorporated by devising hybrid-driven AI/
ML solutions that optimally combine data and model-based
approaches.
Building Blocks for Data Processing in Edge and
Cloud Computing
As a result, generic functionalities bundled as components
are needed for sensor data acquisition, data storage, data
analysis, data visualization, and industrial processing. Exe-
cution components are used to close the loop and feed the
results back to the shop floor. To connect the components,
sensors, and shop floor artifacts, a reliable and fast connec-
tion framework is needed. Based on the design paradigm of
edge computing, for fast communication between co-lo-
cated devices and to support analyses of data streams with
low-latency requirements, the components can be deployed
directly on an edge node. In order to cover the entire
cyber-physical system or for long-term analysis, a cloud com-
puting backend can fulfill the demands for higher disk space
and computing power.
1918
4.4. Security – Protecting the Smart Factory
Increased connectivity and in turn increased data processing
leads to new mobile and modular production methods that
have new security requirements. With these new approaches,
huge amounts of data will be transmitted over a wireless
connection and processed, for example, on the edge cloud.
Traditional security approaches, such as network layering
with firewalls, have to be adapted or completely replaced
with up-to-date security technologies like intrusion detection
and end-to-end encryption. OT security needs to address
requirements, such as real-time processing, long life cycles
and proprietary protocols. Security should no longer be seen
as an on-top option, but considered as soon as new systems
are planned in order to protect data, prevent incidents, and
improve the reliability of Industry 4.0 production processes.
That being said, however, new security approaches will have
to be compatible with old industrial systems. Three general
topics have been identified and will be described in detail:
• Secure Connectivity – end-to-end security in production
• Reliable Wireless Communication – protection for the
new medium
• Monitoring Processes – the use of edge cloud and
data analytics
Secure Connectivity – End-to-End Security in Production
Industry 4.0 production processes are becoming more and
more complex. Production plants are made up of modular
machines that can be rearranged individually and commu-
nicate with each other. Additionally, machines are able to
communicate with other Industry 4.0 assets. Due to these
new communication possibilities, the new security require-
ments mentioned earlier must be taken into consideration.
Secure end-to-end communication is needed for remote
access in order to load updates and read maintenance infor-
mation. A gateway is hence introduced to ensure a secure
connection between devices and remote operators. The
security gateway, which will be placed as a hardware trust
anchor, enables existing production facilities for Industry 4.0
applications. Devices will also require a mechanism so that
they can authenticate each other in order to start trusted
device-to-device communication.
Furthermore, a significant challenge is that most of the
Industrial IoT (IIoT) [5] infrastructure is designed for long
life cycles. This means that the components responsible for
system security must also be safe in the long term so that
facilities have to update or upgrade security mechanisms,
methods, and services in line with industry standards and
production processes.
Cloud-based security services as well as applications on the
gateway provide reliable access management by setting up
a role-based connection with requirement-specific restric-
tions for remote maintenance or control. This bridges differ-
ent wired and wireless network technologies and supports
different industrial application standards, such as OPC-UA
or MQTT. It also creates, manages, and distributes digital
identities by utilizing a public key infrastructure (PKI). Thanks
to digital identities, trusted nodes can be used in a massive
sensor network without any intrusion by malicious devices.
Reliable Wireless Communication – Protection
for the new Medium
In the future, wireless industrial communication could
increase, providing mobility and flexible ad-hoc commu-
nication between the machines themselves and between
machines and the Industry 4.0 product. In order to ensure
reliable and secure wireless communication, additional data
analysis and detection methods will be used.
First and foremost, a comprehensive authentication scheme
for devices and encryption of data ensures that data can-
not be altered or false data injected. However, a growing
number of wireless-enabled devices and wireless transmis-
sions will impact the stability and reliability of a wireless
connection. Simultaneous wireless transmissions especially
can cause interference and, accordingly, degrade transmis-
sion rates or even disrupt connections. To identify the root
cause of a wireless transmission disruption, classification can
be used to determine whether the interference was uninten-
tional or malicious. Classifying the interference allows the
appropriate measures to be selected, e.g., to either identify
a jamming device or perform radio resource management
in order to prevent a disruption or massive loss of perfor-
mance. In order to be able to switch off a malicious interfer-
ing device like a jammer, plant operators have to know the
precise location of the device. The operator can then either
turn the malicious device off or inform the authorities about
its existence and location. This kind of system can be also
used to identify machines and processes that interfere with
the radio channel, e.g., like frequency converters or welding
robots so that appropriate measures, such as EM shielding,
can be taken.
Monitoring Processes and Data Analytics
Massive sensor networks in Industry 4.0 production plants
constantly monitor the environment in order to detect anom-
alies or to identify attrition to support for instance predictive
maintenance. This, accordingly, generates huge amounts
of measured data for data analysis, i.e., making big data
analysis vital if the information is to be processed efficient-
ly. This means that distributed data storage is essential for
storing huge amounts of data. Furthermore, some informa-
tion needs to be processed as close as possible to the origin
to reduce latency, e.g., when near real-time requirements
are paramount. Moreover, in order to protect the data, the
system needs the capabilities for inherent encryption and
user management for access control.
Near real-time industrial data analytics may also rely on new
processing methods, e.g., by leveraging machine learning.
These new methods allow anomalies in production data to
be detected and can indicate machine manipulation or ma-
licious intrusion. Analysis of sensor data can also be used for
predictive maintenance in order to detect a machine failure
before it happens so that preemptive action can be taken.
Audio data, for example, can be used to listen to anomalies
that indicate failure in engines, bearings or shafts. The more
data is acquired, the more computing power will be needed.
Depending on latency and power requirements, the pro-
cessing units can be placed both on the edge of the network
(edge cloud) or centrally. The use of new detection methods
enables the detection of failures in hardware and software
that may be caused by wear and tear or attack. With the
factory now connected to the enterprise network or even the
Internet, new threats must be addressed which are familiar
from the Internet. A hacker could launch an attack from
cloud-based services or could hijack parts of the production
environment. This cannot be prevented if the attacker uses
zero-day or known exploits, but if a breach is detected, the
infected device can be excluded from communication in
order to protect the other devices from infection.
2120
5. REFERENCE ARCHITECTURE AND BUILDING BLOCK APPROACH
This section describes our approach to the IC4F reference
architecture. First of all, the layers of the architecture are de-
scribed. This is followed by how the architecture can be used
to realize real-world implementations (Section 5.1) using our
building block approach (Section 5.2).
5.1. The IC4F Reference Architecture
Industry 4.0 is bringing new business opportunities while
raising new challenges for the underlying ICT infrastructure
in the context of the factory of the future. The IC4F project
is examining the convergence of operational technology,
information technology, and communication technologies
in order to fulfill the requirements of the Industry 4.0 use
cases. To this end, IC4F takes a holistic view of the industrial
ICT infrastructure, applications, and data models. In par-
ticular, this approach goes beyond a pure physical view of
the communication infrastructure (box view), as it considers
higher layers and application frameworks. It also addresses
scenarios like cloud computing on the shop floor, 4G/5G in
the factory, and scalable fast data architectures for massive
sensor networks.
Consequently, the resulting IC4F reference architecture can
be described on a high abstraction level by two layers:
• The ICT infrastructure layer provides wireless or wired con-
nectivity to all objects on the shop floor and may connect
them with cloud resources in different network domains
• The application and data layer includes factory applica-
tions; modeling, management, analytics, and visualization
of data; as well as AI algorithms.
Both layers are complemented by security as well as man-
agement and control functions that are frameworks rather
than functions represented within a single layer.
The placement of the physical systems is especially impor-
tant with a view to security, availability and scalability. The
placement may range from close to the production process
on the shop floor, e.g., sensors that monitor the system state
or wireless URLLC connections for closed loop machine con-
trol, up to external partners along the value chain who may
be connected via public networks. Placement in this case
stems from the requirements of the use case (cf., chapter 3),
e.g., low latency requirements or specific security require-
ments in a certain network domain. Furthermore, use cases
that cover different position ranges may require specific solu-
tions, e.g., an edge cloud for low latency applications or a
security gateway for remote access via the public internet.
Figure 5.1 shows the different perspectives considered in
Industry 4.0 use cases. Based on the use case requirements,
the application and data as well as the underlying ICT infra-
structure can be defined and implemented. One objective of
the IC4F project is to capture architecture knowledge in the
different domains in building blocks that can then be reused
by enterprises to build their own architectures.
B U S I N E S S P R O C E S S E S
A P P L I C AT I O N D O M A I N , D ATA A N A LY T I C S
D ATA , D ATA M O D E L , S E R V I C E S
P L AT F O R M
M A N A G E M E N T & C O N T R O L
RE
QU
IRE
ME
NT
S F
RO
M U
SE
CA
SE
S
I C T I N F R A S T R U C T U R E
E D G E C L O U D
P R I VAT E
P U B L I C C L O U D
P U B L I C
W I R E D
W I R E L E S S
C O M P U T I N G N E T W O R K I N G S T O R A G E
APPLICATION LAYER
SECURITY
COMMUNICATION & COMPUTING INFRASTRUCTURE
ACCESS SUBSYSTEM
PLANT LEVEL
FA C T O RY C O M PA N Y VA L U E C H A I NS E N S O R S A C T U AT O R S
M A C H I N E E Q U I P M E N T
PRODUCTION CELL AND
L INE
B U I L D I N G B L O C K S F O R A S E C U R E R E A L - T I M E C O M M U N I C AT I O N A N D C O M P U T I N G I N F R A S T R U C T U R E I N I N D U S T RY 4 . 0
S E C U R I T Y
INT
ER
FA
CE
S A
T C
OM
PA
NY
BO
UN
DA
RIE
S
E N T E R P R I S E C L O U D ( P R I VAT E / H Y B R I D )
The IC4F approach corresponds clearly with existing frame-
works and reference architectures for communication and
Internet technologies (OSI model), for software architectures
(The Open Group Architectural Framework, TOGAF [6]), and
for the industrial context (RAMI 4.0 [7] and Industrial Internet
Reference Architecture (IIRA) [8]).
In RAMI 4.0, communication is one of the horizontal layers,
which is defined as the mechanism to exchange information
and to form an integrated physical asset. Accordingly, the
IC4F architecture may be viewed as one facet of the RAMI
4.0 cube (hierarchy levels IEC62264 / IEC61512) where
the ICT infrastructure layer corresponds to the RAMI 4.0
communication layer while the application and data layer
corresponds to the information layer. On the other hand,
the Industrial Internet Consortium (IIC) goes one step further
and extends its Industrial Internet Reference Architecture
(IIRA) with an industrial communication framework. In this
framework, communication is further split into several layers.
These layers are inspired by the OSI model. The IIC provides
a framework that can be used to structure Industry 4.0 topics.
The choice of Internet technology and the introduction of an
OSI-like communication model are important steps towards
practical implementations in all of the approaches. However,
RAMI 4.0 and IIRA models still lack important steps before
industrial use cases can be implemented:
• Each of the layers can be implemented using different
technology choices. Thus, the best technology needs to
be selected with regard to the use case requirements.
• The technologies selected need to be finally deployed on
a physical infrastructure to enable efficient implementation
of communication-driven factory applications.
FIGURE 5.1.: IC4F REFERENCE ARCHITECTURE FOR AN INDUSTRIAL ICT INFRASTRUCTURE, APPLICATION AND DATA
2322
Based on the analysis of industrial use cases and existing
technologies, the IC4F project addresses these points and
provides building blocks for solutions in a much finer gran-
ularity. This building block approach should help SMEs to
implement their use cases.
The overall IC4F approach to implement a specific use
case is depicted in Figure 5.2. Predefined building blocks
can be selected to create the architecture for different use
cases. These describe the functionalities required to meet
5.2. The IC4F Building Block Approach
The objective of the IC4F project is to define the reference
architecture and to provide building blocks to implement
Industry 4.0 use cases based on existing enterprise architec-
ture standards.
In conformity with the ISO/IEC/IEEE 42010:2011 stand-
ard, The Open Group Architecture Framework (TOGAF [9])
provides an Architecture Development Method (ADM) and
concepts for defining architectures for different perspectives
and for iteratively refining architecture building blocks to
form solution building blocks in order to implement a specif-
ic enterprise architecture. It is based on an iterative process
model supported by best practices and a reusable set of
existing architecture building blocks [10,11]. The IC4F ap-
proach applies to TOGAF because it addresses the different
architectures required not only for an enterprise architecture
but also for the factory. It also provides a practical and intu-
itive building block approach while the ADM, as a generic
framework, supports the development of a foundation
architecture made up of architecture building blocks that can
be reused in specific use cases. TOGAF therefore provides
methods and concepts that help us to achieve the overall
objective of a reference architecture with generic, reusable
building blocks.
R E F E R E N C EA R C H I T E C T U R E
C O N C E P T U A L A N D A R C H I T E C T U A L P E R S P E C T I V E
SOLUTION AND IMPLEMENTATION P E R S P E C T I V E
R E A LI M P L E M E N TAT I O N
D E S I G N PAT T E R N
B E S T P R A C T I C E S S Y S T E M D E S I G N I M P R O V E M E N T S F I E L D F E E D B A C K
T O B U I L DT O D E S I G NT O A R C H I T E C T
D ATA F L O W V I E W
N E T W O R K V I E W
O T H E R S
C O N D I T I O N M O N I T O R I N G
M O B I L E R O B O T I C S
O T H E R S
• C O M M O N T E R M I N O L O G Y A N D TA X O N O M Y
• F U T U R E T R E N D S
• B E S T P R A C T I C E T E M P L AT E S
• O V E R V I E W O F T E C H N O L O G Y B U I L D I N G B L O C K S
• S E R V I C E PA R A M E T E R S
• T E C H N O L O G Y R O A D M A P A N D M I G R AT I O N S T R AT E G I E S
• D E S I G N A N D I N T E G R AT I O N
• T E S T I N G P L A N
• I M P L E M E N TAT I O N D O C U M E N TAT I O N
INFORMATION SYSTEM(APPLICATION & DATA)
TECHNOLOGY(ICT INFRASTRUCTURE) S
EC
UR
ITY
A B B
A B B
A R C H I T E C T U R E B U I L -D I N G B L O C K S ( A B B s )
I C 4 F D E M O N S T R AT O R 1
I C 4 F D E M O N S T R AT O R 2
I C 4 F D E M O N S T R AT O R …
I C 4 F D E M O N S T R AT O R N
S O L U T I O N B U I L D I N G B L O C K S
FIGURE 5.2.: IC4F’S OVERALL BUILDING BLOCK APPROACH FOR IMPLEMENTING USE CASES
FIGURE 5.3.: USE OF TOGAF ARCHITECTURES TO SPECIFY THE IC4F REFERENCE ARCHITECTURE
The IC4F reference architecture based on TOGAF is de-
scribed below. Figure 5.3 depicts different architectures ad-
dressed by TOGAF and how the domains mainly addressed
by the IC4F project fit into these architectures. Based on the
TOGAF ADM, the business is first developed followed by the
data and application and finally the technology architecture.
These phases of the architecture development method are
used to define reusable architecture building blocks for the
different architectures and serves as a basis for implement-
ing specific use cases.
Architecture Building Blocks (Conceptual View)
Architecture building blocks (ABBs) define packages of func-
tionalities to meet business needs. Furthermore, building
blocks are described by templates which include a descrip-
tion of functionality and context, exposed public interfaces,
interoperability, service parameters, and possible implemen-
tations. and possible implementations. Use cases can be
built up from a collection of interoperating building blocks.
Therefore, interfaces and relations to other building blocks
need to be defined as well. Moreover, ABBs can be defined
at different levels of detail. Accordingly, depending on the
objective of the building block, both generic and refined
ABBs can be defined to facilitate the support of generic as
well as more specific functionalities.
TECHNOLOGY ARCHITECTURE
INFORMATION SYSTEM ARCHITECTURE
BUSINESS ARCHITECTURE
D ATAA P P L I C AT I O N
S E C U R I T Y
I N F R A S T R U C T U R E A N D H A R D WA R E
D E P L O Y M E N T C O M M U N I C AT I O N A N D C O M P U T E
the business needs in a vendor and product-independent
manner. Accordingly, these reusable architectural building
blocks can be used to design the solution for a specific use
case via the solution building blocks. The solution building
blocks implement the functionalities described by the archi-
tectural building blocks. In the IC4F project, demonstrating
specific use cases will be used to validate the IC4F reference
architecture.
2524
The purpose of generic architecture building blocks is to
provide an orientation within the framework and to under-
stand the related concepts for a certain use case. Since the
placement of ICT and application components plays an
important role in Industry 4.0 use cases, this placement con-
sideration must also be taken into account for the generic
architecture building blocks. Possible placement domains
are the machine, factory, enterprise, or public (open world)
level as shown in Figures 5.4. and 5.5. Each domain contains
generic functions, such as compute, storage, networking and
access. This references current operational domains such
as public cloud/networks, IT cloud network and shop floor/
OT networks. Today, these domains usually operate inde-
pendently. The IC4F project plans to investigate the seamless
use across domains, e.g., connectivity and QoS mechanisms
from the shop floor to remote sites, cloud resource access
FIGURE 5.4.: HIGH-LEVEL CONCEPT SHOWING AN EXAMPLE OF BUILDING BLOCKS FOR THE TECHNOLOGY ARCHITECTURE
FIGURE 5.5.: HIGH-LEVEL CONCEPT SHOWING AN EXAMPLE OF BUILDING BLOCKS FOR THE INFORMATION SYSTEM ARCHITECTURE
P U B L I C W I R E L E S S
C O N T R O L U N I T
F I E L D N E T W O R K
C O N T R O L U N I T
W I R E L E S S M O D E M
F I E L D N E T W O R K
I N D U S T R I A L W I R E L E S S
E N T E R P R I S E W I R E L E S S
E N T E R P R I S E N E T W O R K
E N T E R P R I S E C O M P U T E
E N T E R P R I S E S T O R A G E
I N D U S T R I A L N E T W O R K
I N D U S T R I A L C O M P U T E
P U B L I C N E T W O R K
P U B L I C C O M P U T E
T E C H N O L O G Y
INTERNET
OPEN WORLD
ENTERPRISE
FACTORY
WIRELESS CONNECTED MACHINE
WIRED CONNECTED MACHINE
P U B L I C S T O R A G E
P U B L I C W I R E D A C C E S S
LOGICAL COMMUNICATION PATH
from the edge to public nodes. The IC4F building blocks are
continuously advanced throughout the project. In particular,
the framework is extendable to consider future trends and
technologies.
When it comes to flexibility and dynamics in a distributed
end-to-end scenario/use case, two levels can be distin-
guished. On the communication infrastructure level, SDN
and NFV technologies allow for different optimized deploy-
ments for multiple distribution schemes according to chang-
ing needs and topologies. On the service and application
level, similar degrees of freedom and optimization potential
can be achieved with micro-services, modularized applica-
tions, and orchestration frameworks like TOSCA. Building
blocks are, for instance edge computing, Industrial wireless,
and (big) data analytics.
ICT infrastructures have traditionally been separated in vari-
ous physical areas like the field/machine, shop floor/factory,
enterprise and public area. In the past, different technolo-
gies, ecosystems, and business models have evolved along
these separation lines. In the IC4F project, we expect that
that these boundaries are successively breaking down and
that technologies from one area can be adapted and used in
other areas. One example of this, is the virtualization of com-
pute resources. In addition to making resources available for
multiple purposes, these are also interconnected across the
different areas. This means that there is a network of com-
puter resources available, ranging from local, enterprise wide
to public compute resources, that forms a seamless compute
cloud. Figure 5.4. shows how the different areas with various
computing, networking, storage, and wireless functions in
the domains could be interconnected. It provides a view of
the building blocks for more detailed solutions within the
overarching ICT infrastructure.
The application and data domain (see Figure 5.5.) con-
tains generic blocks that depict the logical data flow from
data producers, data distribution between the various user
applications, data management, data processing up to its
visualization. Unlike the ICT Infrastructure, where the focus is
more on the physical and virtual infrastructure, the emphasis
here is on the logical data flow.
There is a generic flow, i.e., data is generated, transport-
ed, processed, analyzed and then visualized somewhere or
further events are caused. Within this pattern, the data may
cross various areas, it may be processed and used at any
place, depending on the specific need. Furthermore, as data
has a tendency to grow along that flow line (i.e., replicating
and generating new data), a new need to manage data
arises in the respective area. This covers functions to store
data at the right place, transform it where needed, and make
it available when permitted. There are also area-specific
I N D U S T R I A L S E R V I C E S , E . G . M E S
B U S I N E S S S E R V I C E S , E . G . E R P
D ATA P R O D U C E R
A P P L I C AT I O N A N D D ATA
OPEN WORLD
ENTERPRISE (CENTRAL CLOUD)
FACTORY (EDGE CLOUD)
CONNECTED MACHINE
LOGICAL COMMUNICATION PATH
C E N T R A L D ATA M A N A G E M E N T
D ATA A N A LY T I C S
E D G E D ATA M A N A G E M E N T
M E S S A G I N G M I D D L E WA R E(PLATFORM SERVICE, NOT PART OF APPLICATION SERVICE)
D ATA V I S U A L I Z AT I O N
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services like Manufacturing Execution System (MES) for the
factory area and Enterprise Resource Planning (ERP) in the
enterprise area that utilize the data flow above. Along the
areas above, there is a correlation between the type of data
and services/applications running on top of a certain type of
ICT infrastructure. In the past, these were hard boundaries.
The IC4F project is investigating what needs to be done in
order to establish communication across these boundaries in
a controlled and defined way.
Refined architecture building blocks can be defined to
meet specific use case requirements, following the generic
building blocks approach. The refinement is based on an
iterative process of selecting appropriate building blocks
for a specific use case. With refined architecture building
blocks, technology choices, interworking, solution integra-
tion/interfacing, and migration strategies can be considered
FIGURE 5.6.: EXAMPLES OF ARCHITECTURE BUILDING BLOCKS AT DIFFERENT LEVELS (MARKED IN BLUE AND ORANGE)
and visualized. Figure 5.6. shows examples of functionalities
(building blocks) which are possible choices for the archi-
tecture of particular use cases. In this figure, blue building
blocks represent generic building blocks and orange blocks
represent the more specific refined building blocks. Inde-
pendent of their refinement level, these building blocks are
vendor and product independent.
Solution Building Blocks (Solution/Instantiation View)
The solution building blocks (SBBs) represent vendor-specific
deployable/executable components related to the archi-
tecture building blocks. The SBBs provide the performance
details required for the implementation of specific use cases.
In the IC4F project, SBBs are generated within the scope of
the selected IC4F demonstrators selected. However, these
are vendor and use-case specific and consequently do not
embody a general view.
T E C H N O L O G Y A R C H I T E C T U R EI N F O R M AT I O N S Y S T E M A R C H I T E C T U R E S E C U R I T Y
D ATA S T O R A G E & M G M T.
D ATA A N A LY T I C S
C L O U D O R C H E S T R AT I O N
W I R E D N E T W O R K
W I R E L E S S C O N N E C T I V I T Y
BIG DATA ANALYTICS/BATCH
PROCESSING
RELATIONAL DATABASE
MGMT. SYSTEM
TOSCA APPLICATION DEPLOYMENT
& MGMT. ENGINE
TOSCA CLOUD SERVICE TEMPLATE
TOSCA APPLICATION &
MODELING TOOL
NOSQL DATABASE
MGMT. SYSTEM
NEWSQL DATABASE
MGMT. SYSTEM
TIME SERIES DATABASE
MGMT. SYSTEM
COMPLEX EVENT PROCESSING
STREAM ANALYTICS
T C O S S M A RT C A R D
R O L E M A N A G E M E N T
C E RT I F I C AT E / K E Y M A N A G E M E N T
P U B L I C K E Y I N F R A S T R U C T U R E
P R O F I N E T
S E R C O S
E T H E R N E T
M P L S
T S ND ATA L A K E
W I R E L E S S H A RT
W L A N
M U LT E F I R E
4 G - LT E
5 G - N E W R A D I O
S E C U R E G AT E WAY
6. APPLICATION OF BUILDING BLOCKS IN DEMO SCENARIOS
In order to validate the reference architecture and building
block approach outlined in the previous section and to show
its practical relevance, it is essential that some real-world
examples are considered along with how this approach can
be used to implement concrete use cases and applications.
To this end, four different use cases, which are outlined in
Section 2, are briefly discussed. Specifically, the four different
use case are a subset of the uses cases which will be shown
through ten advanced demonstrators.
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S E C U R I T Y G W A N A LY T I C S V I S U A L I Z AT I O N
4 G – M O D E M
R E M O T E S E R V I C E C E N T E R
FA C T O RY
M A C H I N E
S E C U R I T Y G W S E N S O R / A C T U AT O R / C O N T R O L L E R
P U B L I C 4 GN E T W O R K
FIGURE 6.1.: BASIC SETUP OF “REMOTE MACHINE ACCESS” USE CASE INCLUDING SELECTED BUILDING BLOCKS FOR IMPLEMENTING SUCH A SCENARIO
FIGURE 6.2.: BASIC SETUP OF THE “AUTOMATED GUIDED VEHICLES” USE CASE INCLUDING SELECTED BUILDING BLOCKS FOR IMPLEMENTING SUCH A SCENARIO
6.2. Automated Guided Vehicles
Automated guided vehicles (AGVs) that take care of the
flow of goods and material in a factory in an autonomous
manner are considered as another relevant example. Due
to their mobility, wireless connectivity is a natural choice for
such devices. In the simplest case, this connection can be
used to transmit new tasks or to retrieve status information.
However, as more and more reliable and powerful wireless
technologies become available, advanced functionalities
may be implemented. One example could be to offload a lot
of the intelligence that is traditionally contained in the AGV
U R L L C - M O D E M
D E V I C E - T O - D E V I C E C O M M U N I C AT I O N
O N B O A R D G W
4 G - M O D E M L O C AT I O N TA G S
A C T U AT O R
S E N S O R
D ATA V I S U A L I Z AT I O N
L O C AT I O N B E A C O N S
Q R C O D E
T O S C A O R - C H E S T R AT I O N
M Q T T B R O K E R
D ATA S T R E A M P R O C E S S I N G
T R A N S P O RT P R O T O C O L S
D ATA M A N A G E M E N T
N E T O R K M A N A G E M E N T
I T D ATA S T O R A G E
L O C AT I O NA N A LY T I C S
V I S U A LA N A LY T I C S
A N O M A LYA N A LY T I C S
T O S C A D E V I C E M O D E L I N G
I N D U S T R I A L E D G E C L O U D
GRAND MASTER CLOCK (PTP)
I T E D G E C L O U D
U R L L C S Y S T E M
4 G S Y S T E M
E N T E R P R I S E N E T W O R K
A C T U AT O R
S E N S O R
4 G - M O D E M
U R L L C - M O D E MO N B O A R D G W
A G V 1
I C T I N F R A S T R U C T U R E
P L AT- F O R M
A P P L I C AT I O N S / S E R V I C E S
FA C T O RY S U P P O RT S Y S T E M
WA R E H O U S E D I G I TA L T W I N
A G V 2
L O C AT I O N TA G S
itself (e.g., video processing for recognizing the environment
or analytics functionality) to an edge cloud. Likewise, AGVs
could communicate directly with each other, e.g., via direct
device-to-device communication, in order to jointly collabo-
rate in a swarm-like manner so that more complex or difficult
tasks can be managed than by a single AGV, such as joint
lifting of heavy goods. Moreover, localization technologies
6.1. Remote Machine Access
In some situations, it may be helpful to remotely connect
to a certain machine or component, for example, in case of
malfunctions or for remote maintenance. As the supplier of
such a machine or component does not necessarily know in
advance where his equipment will ultimately be used and
what communication infrastructure will be available, the eas-
iest and presumably most generic way to implement remote
access is via a cellular 4G network. However, this generally
poses security challenges, because this kind of “bypass” to
a public network infrastructure may vitiate any local security
mechanisms in place and hence lead to a potential security
threat. One possible way to address this challenge is to care-
fully monitor, control, and log the traffic that goes from and
to a remotely connected machine or component, for exam-
ple, via a dedicated security gateway. The principle setup of
such a system, including selected building blocks outlined in
the previous section for implementing this kind of use case,
are depicted in Figure 6.1.
integrated into the wireless infrastructure could be used to
assist in positioning an AGV on the factory floor as well as
to the current destination. A likely architecture, including cer-
tain building blocks that are required to build such a system,
is shown in Figure 6.2.
3130
6.3. Massive Wireless Sensor Networks
A wide variety of different sensors may be deployed in a
factory to implement functions, such as condition monitor-
ing, predictive maintenance or to detect anomalies. In many
cases, it makes sense to connect these sensors wirelessly as
this facilitates easy retrofit solutions, so that existing ma-
chines can also be easily “upgraded” simply by integrating
additional sensors. Moreover, this can reduce maintenance
and installation work and improve usability. In fact, we envi-
sion that in future hundreds or thousands of sensors may be
deployed in a factory, leading to a potentially significant ac-
WIRELESS SENSOR WIRELESS SENSOR
S E N S O R4 G - M O D E M S E N S O R4 G - M O D E M
APPLICATION / SERVICES
ICT INFRASTRUCTURE
FACTORY SUPPORT SYSTEM
B A C K E N D D ATA A G G R E G AT I O N
4 G S Y S T E M
I N D U S T R I A L E D G E C L O U D
I T D ATA C E N T E R C L O U D
E N T E R P R I S E N E T W O R K
I T E D G E C L O U D
L O C A L D ATA A G G R E G AT I O N
A N O M A LY D E T E C T I O N
FIGURE 6.3.: BASIC SETUP OF THE “MASSIVE WIRELESS SENSOR NETWORK” USE CASE INCLUDING SELECTED BUILDING BLOCKS FOR IMPLEMENTING SUCH A SCENARIO
6.4. Mobile Cooperation and Control with Ultra-Reliable Machine Communication
As a last example, we are considering a mobile control panel
that can be used to configure or monitor a machine. Such
control panels typically also have safety-critical functions,
e.g., an emergency stop button. Most panels currently have
wired connections due to the demanding reliability and
latency constraints of the safety-critical functions. However,
FIGURE 6.4.: BASIC SETUP OF USE CASE “MOBILE COOPERATION & CONTROL WITH ULTRA-RELIABLE MACHINE COMMUNICATION” INCLUDING SELECTED BUILDING BLOCKS FOR IMPLEMENTING SUCH A SCENARIO
APPLICATION / SERVICES
ICT INFRASTRUCTURE
S A F E T Y C O N T R O L L E R
I N D U S T R I A L G W5 G - S Y S T E M
USER EQUIPMENT
C O N T R O L PA N E L5 G - M O D E M
FACTORY SUPPORT SYSTEM
cumulated data rate. However, it is not necessary to transmit
every sensor value to the cloud since much of the data may
be redundant or correlated and since adequate actions may
only have to be carried out locally. Therefore, one promising
approach is to have some local pre-processing/pre-aggre-
gation, for example, in an edge cloud, and to forward only
the pre-processed data to an actual backend cloud. One
major challenge in this respect is how distributed processing
with potential instances in the end devices, the edge cloud
and the backend cloud can be properly orchestrated and
deployed. A likely architecture of this use case, including
selected building blocks, is shown in Figure 6.3.
with new wireless technologies, such as 5G with its ultra-reli-
able and low-latency communication, a wireless connection
becomes possible, for example, in combination with appro-
priate safety protocols such as PROFIsafe. To this end, the
mobile control panel must be connected to a 5G network via
a 5G modem and a suitable gateway to communicate with
the machine control unit. Figure 6.4 depicts a possible setup
of such a system using ABBs.
3332
7. ABOUT IC4F
The flagship project “Industrial Communication for Factories”
(IC4F) aims to develop secure, robust, and real-time commu-
nication solutions for the manufacturing industry. Throughout
the project, the IC4F partners develop building blocks for a
trusted industrial communication and computing infrastruc-
ture based on an open cross-domain architecture that allows
modular expansion for new applications and communication
technologies. Key technologies include 5G, multi-access
edge computing, cloud computing, virtualization, and
industrial monitoring and analytics. The building blocks are
designed to enable users to select the appropriate ICT tech-
nologies, according to the new Industry 4.0 requirements
and the specific migration approach.
The IC4F reference architecture will provide a validated
approach for defining Industry 4.0 communication systems
in a variety of factory ecosystems. Accordingly, IC4F involves
relevant stakeholders along the value chain and brings
together the expertise from different specialist disciplines.
The project is supported by the German Federal Ministry of
Economic Affairs and Energy (BMWi).
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REFERENCES, ABBREVIATIONSReferences
[1] Cockburn, Alistair, “Writing effective Use Cases”, Addi-son-Wesley, 2001
[2] Anwendungsbeispiele der Plattform Indutrie 4.0, http://www.plattform-i40.de/I40/Navigation/Karte/SiteGlobals/Forms/Formulare/karte-anwendungsbeispiele-formular.html
[3] EFFRA: Factories 4.0 and Beyond, Recom-mendations for the work programme 18-19-20 of the FoF PPP under Horizon 2020, Version: v30 – Date: 12/09/2016
[4] NGMN Alliance (2014), 5G White Paper -Executive Version[5] Jeschke, S., Brecher, C., Song, H., & Rawat, D. B. (2017), Industrial Internet of Things, Cham: Springer International Publishing, https://doi.org/10.1007/978-3-319-42559-7 (Last retrieved on March 15, 2018)[6] Open Group, TOGAF standard, http://www.opengroup.org/
subjectareas/enterprise/togaf/[7] Deutsches Institut für Normung (2016), Referenzarchitektur-
modell Industrie 4.0 (RAMI4.0)[8] Industrial Internet Consortium (2015),Industrial Internet
Reference Architecture, http://www.iiconsortium.org/IIC_PUB_G1_V1.80_2017-01-31.pdf
[9] http://pubs.opengroup.org/architecture/togaf8-doc/arch/chap32.html
[10] http://pubs.opengroup.org/architecture/togaf9-doc/arch/chap37.html
[11] http://pubs.opengroup.org/architecture/togaf9-doc/arch/chap37.html#tag_37_03
Abbreviations
2G/3G/4G/5G 2nd/3rd/4th/5th Generation Mobile Network3GPP 3rd Generation Partnership Project5GC 5G CoreABB Architecture Building BlockADM Architecture Development MethodAGV Automated Guided VehicleAI Artificial IntelligenceAPI Application Programming InterfaceAR Augmented RealityCT Communication TechnologyCU Central UniteMBB Enhanced Mobile Broadband ERP Enterprise Resource PlanningGW GatewayIC4F Industrial Communication for FactoriesIIC Industrial Internet ConsortiumIIoT Industrial Internet of ThingsIIRA Industrial Internet Reference ArchitectureIoT Internet of ThingsIT Information TechnologyKPI Key Performance IndicatorLTE Long Term EvolutionLTE-A Long Term Evolution-AdvancedMAPE Monitoring, Analysis, Planning, and ExecutionMES Management Execution SystemML Machine LearningMQTT Message Queue Telemetry TransportMTC Machine-Type CommunicationNFV Network Function VirtualizationNR New RadioNRF Network Repository FunctionOSI Open Systems InterconnectionOT Operational TechnologyPKI Public Key Infrastructure PaaS Platform as a ServiceQoS Quality of ServiceRAMI 4.0 Reference Architecture Model Industry 4.0RU Remote UnitSDN Software-defined NetworkTOGAF The Open Group Architectural FrameworkTSN Time Sensitive NetworkURLLC Ultra Reliable Low Latency CommunicationVM Virtual MachineVNF Virtual Network FunctionVR Virtual RealityWLAN Wireless Local Area Network