Status report Industry 4.0 - Sacha Michel, Louis Dalpra, Thomas Wagner, Patrick Llerena, Philipp Nenninger - Upper Rhine 4.0, le réseau de ...
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
Status report Industry 4.0
Sacha Michel, Louis Dalpra, Thomas Wagner, Patrick Llerena, Philipp
Nenninger
Contents
1 Definition 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 History . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2.1 First introduction of Industry 4.0 in Germany . . . . . . . . . . . 1
1.2.2 Introduction in France and Switzerland . . . . . . . . . . . . . . . 2
1.2.3 National goals . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Meaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.1 Internet of Things . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.2 Industry 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Overall strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.1 Vision and Goals . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.2 Measures/investments and areas of activity . . . . . . . . . . . . . 6
1.5 Structure for Industry 4.0 . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.5.1 Reference Architecture Model Industry 4.0 . . . . . . . . . . . . . 8
1.5.2 Industrial Internet Reference Architecture . . . . . . . . . . . . . 9
1.5.3 Industry 4.0-Component . . . . . . . . . . . . . . . . . . . . . . . 11
1.6 Example application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
1.6.1 Fictitious company FiveBike . . . . . . . . . . . . . . . . . . . . . 12
1.6.2 Digitized service . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
1.6.3 Criteria for I4.0-products - Festo service unit combinations . . . . 14
2 Economical & Social Aspects - A Literature Review 17
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2 Implications of Industry 4.0 for firms . . . . . . . . . . . . . . . . . . . . 18
2.2.1 Implementation of Industry 4.0 paradigm in the firm . . . . . . . 19
2.2.2 Geographical environment for Industry 4.0 firms . . . . . . . . . . 24
2.3 Implications of Industry 4.0 for Customers . . . . . . . . . . . . . . . . . 25
2.3.1 Industry 4.0 provides a better comprehension of customers’ demand 25
2.3.2 Customers are the heart of Industry 4.0 . . . . . . . . . . . . . . . 28
2.3.3 Industry 4.0 as a vector of social stability and economic sustainability 31
2.4 Implications of Industry 4.0 for workers . . . . . . . . . . . . . . . . . . . 33
2.5 Implications for central authorities . . . . . . . . . . . . . . . . . . . . . 36
2.5.1 Industrial policy . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.5.2 Educational policy . . . . . . . . . . . . . . . . . . . . . . . . . . 40
2.5.3 Ecological implications . . . . . . . . . . . . . . . . . . . . . . . . 41
ii
2.5.4 Incentives to enter Industry 4.0 . . . . . . . . . . . . . . . . . . . 42
2.6 Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
3 Technical Aspects 47
3.1 MQTT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
3.1.1 Publish/subscribe pattern . . . . . . . . . . . . . . . . . . . . . . 47
3.1.2 Topics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.1.3 Further features and functionalities . . . . . . . . . . . . . . . . . 49
3.1.4 MQTT 5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
3.1.5 Alternatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
1 Definition
1.1 Introduction
Industry 4.0 (I4.0) is a commonly used term, but it is rarely understood uniformly.
In the context of I4.0 a lot of buzzwords like IoT/IIoT, Smart Factories, CPS, Work
4.0, Big Data or Digitization are used, which are just as obscure. Whoever starts to
get familiar with the concept will primarily encounter various programs and initiatives
in research. Some equipment suppliers provide a few solutions as products or services,
but those are rarely seen in actual, non-research, use. There are only a few small or
medium-sized enterpises (SME), which are said to be the main beneficiaries that try to
adapt such products and services in small R&D projects. This approach is only able to
demonstrate very limited aspects of I4.0.
• Is I4.0 just a hype?
• What is the appeal?
• Is a fear of falling behind rational?
• Where to start?
• Shouldn’t there be Industry 3 before I4.0?
This report will try to resolve uncertainties and provide realistic future prospects for
SME.
1.2 History
1.2.1 First introduction of Industry 4.0 in Germany
The term “Industrie 4.0” was first used in 2011 by Henning Kagermann, Wolf-Dieter
Lukas and Wolfgang Wahlster during the Hannover Messe [1]. It was used as a project’s
title, which was part of the German Federal Government’s “Hightech strategy”. The
expression is based on the idea of an upcoming fourth industrial revolution.
• Driven by steam and water power the first industrial revolution occurred around
1750 enabling new mechanized factory systems.
1
1 Definition
Industry 4.0:
today - Digitization
Industry 3:
1960 - Automation
Industry 2:
1870 - Electrification
Industry 1:
1750 - Mechanization
Figure 1.1: Industrial revolution
• The second industrial revolution began with electricity. Electrification enabled
mass productions in 1870.
• New information and communications technology made it possible to automate
industries in 1960 [2].
• The fourth industrial revolution is supposed to use Cyber Physical Systems (CPS)
to digitize industrial enterprises [3].
By using a numbering scheme familiar to the one used to tag software versions, 4.0
instead of just 4, emphasis it put on the computer science based approach and possible
multiple iterations. The project “Industrie 4.0” ended in 2013 when an implementation
strategy was presented by the German research union and Deutschen Akademie der
Technikwissenschaften (acatech) during the Hannover Messer [3].
In 2013 the project was then continued by BITKOM, VDMA and ZVEI. A research
network named “Plattform Industrie 4.0” (figure 1.2(a)) was founded. A few members
of the research group, who were part of the initial project, got part of this network
too [4]. Further the “Allianz Industrie 4.0” was founded to support SME especially in
Baden-Württemberg. Baden-Württemberg has a lot of potential in respect of I4.0 as it
houses big parts of Germany’s automotive and automation industry while also being the
location for various research institutions.
1.2.2 Introduction in France and Switzerland
In 2013 the program “La Nouvelle France Industrielle” came up in France and even-
tually lead to the project “Industrie du futur” in 2015 [5]. This project is the French
2
1 Definition
(a) Plattform Industrie 4.0 (b) Industrie 2025
(c) Alliance Industrie du Futur
Figure 1.2: Industry 4.0 Projects and programs
counterpart to the German “Industrie 4.0”. In parallel to the German Plattform In-
dustrie 4.0 the Alliance Industrie du Futur (AIDF) was founded in France in 2015 [6]
(figure 1.2(c)). The two networks work in cooperation with each other.
Switzerland started an initiative in 2016 to also support future industry development
in respect to the I4.0 topic called “Industrie 2025” (figure 1.2(b)).
1.2.3 National goals
According to the implementation strategy by the German research union main goal
of the fourth industrial revolution should be to reinforce Germany’s position as global
leader in the equipment suppling industry [3]. The suppliers should concentrate on
developing and selling new solutions and products, which enable factory Digitization for
I4.0. Germany’s industry should also use those products in their own productions to
digitize those. Switzerland pursues a similar approach but with the main goal to improve
innovation and development Know-how. It should be used to tap into new markets [7].
New markets will secure jobs and strengthen Switzerland’s global position. The AIDF
in France aims to also improve innovation and development Know-how in the industry
but also support investments in new technology [6].
3
1 Definition
1.3 Meaning
1.3.1 Internet of Things
The Internet of Things (IoT) is what we get when we connect Things, which
are not operated by humans, to the Internet [8].
To break down this cite:
• To connect Things communication protocols and communication patters are needed
that fit the concept of IoT.
• Things relates to all things that could be connected like sensors, actuators, con-
trollers and other types of devices.
• Not operated by humans excludes e.g. smartphones or laptops (which are “already”
connected). It is meant to put emphasis on the autonomy of devices including
provisioning, delegation of trust, automatic decision making and discovery.
• The Internet stands for the network to which most digital devices operated by
humans are already connected. Things connected to the Internet allow access
from anywhere. It also implies scalability, global identity and security.
1.3.2 Industry 4.0
While the technological main driving force of the third revolution were electronics,
computers and automation the main force of I4.0 is the Internet and networking. Most
sources agree; key aspect of I4.0 is the introduction of IoT to the industry.
This exposes the first issue. To be able to embed “things” into the Internet some form
of computer or microcontroller is needed. Some industry sectors are equipped better,
some worse. As the introduction of such electronics was the main driver of the third
industrial revolution, it is a necessary foundation for the fourth. It has to be possible to
connect Machinery and computers to the Internet. Analog processes have to be mapped
to digital, computeraided workflows (see [9]). Some of the steps towards the idea of I4.0
cannot be clearly categorized as part of the third or fourth industrial revolution, but
their necessity is undoubted by all implementation approaches and strategies.
2013’s implementation recommendation [3] explains that machinery, storage systems
and operating equipment have to become CPS to accomplish Digitization for I4.0. Plat-
tform Industrie 4.0’s implementation strategy from 2015 substantiate that [10]. Humans,
objects and systems need to be represented physically and digital. It is only possible to
connect all parts of the value chain if relevant information is available digitally. A fully
digitized and interconnected value chain is able to dynamically organize and optimize
itself. This is the foundation for more complex possibilities and approaches to I4.0. For
example could a dynamic and automated optimization of machinery and storage lead
41 Definition
to cost reduction, high availability and a more environmentally friendly/resource-saving
production. A self-organizing production is also able to achieve smaller lot sizes effi-
ciently. The buzzword here is “lot size 1”; a production that is able to organize itself to
produce individualized products with lot sizes as small as one without losing efficiency.
Those two aspects summarize, according to Plattform Industrie 4.0 and the Industrial
Internet Consortium (IIC), the general idea of I4.0. A foundation of interconnected
CPS in the whole value chains needs to be achieved to then use it to realize ideas like:
optimizing the value chain softwareaided or fully automated and achieve small effective
lot sizes.
“Make things work smartly” [11] A first common goal towards I4.0 is to equip all
elements of the value chain with a digital interface. Today there are already purely
digital components, which offer such an interface by default, but most parts of the
value chain only have a physical representation. Those ones need to be adapted and
outfitted with a digital representation. Physical and digital representations need to be
tied together, CPS, than they can be outfitted with an interface. If this goal is reached,
optimally every component of the value chain will be able to talk to the others and they
will understand each other.
“Make things smartly” [11] In enterprises that have not yet adapted information tech-
nology in a broader spectrum the first step might already offer advantages like shortened
and more unified processes and workflows. Other enterprises might already have adapted
to such digitized workflows before the term Industry 4.0 came up. Those can now start
to think about further benefits and use cases. Commonly known ideas like online dash-
boards to control factory facilities status, predict maintenance by monitoring machinery,
highly computeraided and automated order and human resource management. Compa-
nies that start to adapt I4.0 ideas will find all different kinds of practical uses, which
may be specific for their industry.
1.4 Overall strategy
This chapter will further discuss the direction and strategy of I4.0. It will provide
general approaches and goals.
1.4.1 Vision and Goals
Concrete goals that can be reached today or in the future, are discussed by various
publications. Plattform Industrie 4.0, Industrie 2025 and AIDF each offer examples and
explanations. Apart from that those are also publications to smaller topics and projects
and even a few case studies (see chapter 1.6). As I4.0 spans various industries and
51 Definition
company sizes, examples are mostly quiet specific but can give an inspiration. Despite
the diversity a few common keypoint can be found and summarized.
One, if not the most, mentioned keypoint is the flexibility of production infrastructure.
More flexibility and less need trade-offs enable an optimized decision-making. The vision
also includes the idea of high customizability based on the productions flexibility. A
production that is able to dynamically adapt and produce customized products enables
a company to offer customer-specific products without additional costs. Such a dynamic
production could produce individual products while also being more resource efficient
and environmental friendly.
A digitized company with digitized factories can also develop new business models.
Those could be based on digitized services like automatically notifying service personnel
or offering remote support.
Thanks to new software running on connected digital workspaces employees will be
supported. A modern workplace eases daily tasks and helps automating repetitive tasks.
Unified and softwareaided processes that an employee can use are convenient for him
while also lowering administrative expenses. I4.0 will change what, how, where and how
much we will work. AIDF focuses on such benefits in working environments calling it:
“plants for people”. Plattform Industrie 4.0 describes how to use the potential of a better
Work-Life-Balance and examines a similar field about befits for employees that way.
Concluding this topic it is important to stress again that most ideas, especially more
concrete ones, are quiet specific. Each enterprise has to classify and rank I4.0-visions
and -goals for itself. Support can be found looking for other companies that already have
adapted I4.0 concepts and offer the possibility to use them as a “beacon”. Many external
agents start to offer suitable support too. It can also be beneficial to find employees in
different department that are interested in the I4.0 topic and can offer company- and
department-specific ideas and help to sketch goals.
1.4.2 Measures/investments and areas of activity
In order to let this vision become reality the three initiatives provided thoughts to
activities, investments and fields of research and action. Based on the central points
mentioned by Industrie 2025 the thoughts of all three initiatives will be ordered:
Promote Digitization Prerequisite for interconnected components is a uniform digital
interface. Foundations for autonomous communications are already present in some
form and on some devices while others have to be retrofitted with those technologies [12].
Difficulties will arise if the network infrastructure is lacking the performance and storage
to handle the increasing volume of data [10]. Cloud-Computing will be needed in the
infrastructure of even smaller companies.
61 Definition
Promote linkage in production processes Factories, production lines and workspaces
have to be networked. Interfaces and protocols have to be standardized. The Industrial
Internet of Things has to be introduced in companies, while also Machine-to-Machine
communication (M2M) is needed. Both concepts are quiet similar but extend each other.
Most companies are already using networks to connect workstations, laptops and mobile
phones but mostly only for office workers, sales- and service-workers. The shopfloor is
a blindspot. Interconnected digitized machinery and shopfloor logistics (M2M) expand
a companies network of “things” to a Industrial Internet of Things (IIoT). A decentral-
ized network spanning the whole value chain needs to be established. Difficulties that
may arise due to different requirements like safety, security and realtime operation or
bandwidth/throughput have to be solved [10]. To further expand the network suppliers
and customers or external server centers have to be connected to each other, calling for
an improved broadband infrastructure.
Use collected data The rising amount of data can be collected to gain new insights
about complex processes and systems. Those insights can be used to improve or even
automate decision-making. Statistics and trends can be extracted out of those data
pools. They can be used to plan machine usage and assignments, monitor downtime,
retooling and maintenance. Quiet similar to machinery the data can be used to plan
employee assignments by work hours, vacation and skill. This can improve work organi-
zation and structure. Following those concepts will lead to a more predictable production
that is able to react precisely if conditions change. Plattform Industrie 4.0 has based
their concept of an administration shell on this need for a uniform understanding of
interconnectivity and data [10].
Link all processes, concept stage to final disposal This topic combines a few already
mentioned fields. It should be pointed out that digital connectivity needs to be achieves
in networks not only along one axis. The whole lifecycle needs to be digitized and the
value chain needs to be network along the horizontal and vertical axis. This network is
the base for a dynamic, flexible and resource efficient production. New services can be
provided on that basis using newly developed business models. The already mentioned
concept of an administration shell attempts to formalize communication, interface and
data for each asset in I4.0-communication and -networks. Chapter 1.5.3 further explains
this concept.
A few topics that also need to be discussed and researched but are less often mentioned,
shouldn’t be missing here. They are still crucial for I4.0 and Digitization. Collecting
and sending data, probably even sensitive data containing a companie’s expertise, will
be sent over the Internet. Thinking about security is vital. Security and safety can both
be at stake if machinery could be controller via the Internet by an unauthorized person.
71 Definition
Legal frameworks have to be audited and adapted to protect data but also not to hinder
necessary data exchange. Liability issues could rise if everything is connected.
1.5 Structure for Industry 4.0
The various programs and projects have encountered and described the same problem;
a lack of a consisted structure and vocabulary for I4.0. This lead to the development of
separate abstracts models and architectural descriptions for I4.0.
1.5.1 Reference Architecture Model Industry 4.0
Figure 1.3: RAMI 4.0 (Source: Plattform Industrie 4.0)
Plattform Industrie 4.0’s work group “Reference architecture, standards and norms”
developed, in cooperation with Bosch Rexroth, the Reference Architecture Model In-
dustry 4.0 (RAMI 4.0). It was published in 2015 [13]. This three-dimensional model
(figure 1.3) is supposed to be a tool for classifying products, solutions and use cases in
regards to the overall structure of I4.0.
Along the model’s vertical axis it is split up into “Layer”. Those layers organize
different kinds of informations that describe the I4.0 component from varied viewpoints.
For example, the Business layer might describe a products costs and possible vendors.
A product’s manual would be part of the Functional and, depending on the product,
81 Definition
Integration layer. Looking towards I4.0 there will also be something that describes a
products communication capabilities and something that digitally provides information
about the product. One of the horizontal axes “Life Cycle & Value Stream” presents a
way to classify concepts, ideas or products based on the section of the life cycle they are
useful for. The second horizontal axis “Hierarchy Levels” categorizes hierarchy. Using
all three axes it is now possible to clearly categorize for what a specific idea, concept
or product could/should be used. For example, a tool that provides insight on when
a machine might fail and therefore when it should undergo maintenance. This tool
will have to tap into the communication structure and read information the machine
provides. It will then present business insight on possible downtimes. It will be most
useful during the maintenance/usage phase of one instance, one machine. Looking at
the “Hierarchy Levels” such a tool will be helpful on the “Work Center” level where
maintenance of single machines is be planned.
Just like in this example the RAMI 4.0 can be used, to classify already known norms,
solutions, use cases, products and standards. It provides a basis for clear communication.
Mapping such technologies in the RAMI 4.0 can help to identify spots where technology
is still missing and spots where different solutions overlap. In regions of the model with
a lot of overlapping problems could arise as the /acI40 goal to connect everything cannot
be achieved with incompatible technologies. Common ground has to be found to enable
a fast, effective and lean production with communication across enterprise borders.
1.5.2 Industrial Internet Reference Architecture
In parallel and independent of the development of RAMI 4.0 the IIC has developed
a reference architecture and published it in 2015. The so-called Industrial Internet
Reference Architecture (IIRA) includes an unified vocabulary and the Industrial Internet
Architecture Framework (IIAF). This framework is supposed to standardize viewpoints
and concerns during development, documentation and communication in the context of
I4.0 and the IIRA [14]. An idea quiet similar to the one Plattform Industrie 4.0 based
RAMI 4.0 on. In 2017, a report was published as both cooperating institutions decided
to try to align bith reference architectures [11].
Figure 1.4 shows a graphical representation of the viewpoints considerer in the IIRA.
Comparing that figure to the RAMI 4.0 those viewpoints align to the layers in RAMI 4.0.
While RAMI 4.0’s layers are more split up the IIC’s approach is more universal. The
IIRA additionally marks the direction of guidance and validation between the named
viewpoints. Also the RAMI 4.0’s life cycle axis matches the IIRA’s one. In contrast to
the layers and viewpoints the life cycle axis is more precise in the latter. The third axis
of the IIRA marks the biggest difference to the RAMI 4.0. Along this axis the model is
split up into the different industrial sectors. All those differences mark clearly that the
IIRA is supposed to be used in a broader spectrum of businesses (e.g. energy, medicine
and pharmacy, public services and (public) transportation) while RAMI 4.0 focuses on
producing industries. The RAMI 4.0 could therefore be used as are more detailed subset
91 Definition
Figure 1.4: Viewpoints, Applications Scope and Lifecycle Process of IIRA (Source: IIC)
of the IIRA. This also matches the institutions motivations. Plattform Industrie 4.0
is concerned about the development and guidance of I4.0 while the IIC focuses on the
broader goal of standardizing IoT and IIoT.
In the report, which compares RAMI 4.0 and IIRA, is another figure. Figure 1.5 pro-
vides another good example on how to use RAMI 4.0. OPC UA as a communication
standard that is built for I4.0 and M2M can be classified using RAMI 4.0’s communica-
tion layer. To classify the technology more detailed, the communication layer is further
divided into the layers of the known ISO/OSI model. The figure shows, how the commu-
nication layer is manly based off of commonly known protocols like IP, Ethernet, WiFi
and 4G but will also use new technologies like TSN and 5G. Based on those ISO/OSI
layers OPC-UA is used as protocol in the ISO/OSI layers 5,6 and 7. It is most useful in
production and usage, not so much during the development and prototyping phase of a
product. OPC-UA is also only scalable to the level of a work center and therefore isn’t
suited for communication on enterprise or “Connected World” hierarchy levels.
101 Definition
Figure 1.5: RAMI 4.0 Communication Layer (Source: IIC)
1.5.3 Industry 4.0-Component
Another concept that is a result of the standardizing work of Plattform Industrie 4.0
is the “Industry 4.0-Componen” [15]. To build the networked base for an interconnected
digitized value chain it is crucial that all assets and components can pass information
from and to each other. Previous chapters already mentioned the idea of an adminis-
tration shell. The concept of an administration shell describes the interface, which each
component offers to enable the physical asset to be part of an I4.0 network. A shell itself
contains a digital copy of the physical object. Physical object and administration shell
combined result in a CPS. Assets like drilling machines or tool trolleys can be mapped
to administration shells just like individual employees, fleet vehicles and inventory can.
Using its shell an asset must be able to provide information (static and dynamic) about
itself in the network it is connected to. E.g., a full shell must be able to notify the
network about its need to be emptied. Based on the type of network used, the shells of
the next free forklift truck can react by reserving it and a free logistics employee can be
notified as his shell reacts.
1.6 Example application
Chapter 1.4.1 already touched the critical aspect of there being not “one” Industry
4.0 in different enterprises [16]. Not every company has adapted Digitization to the
same extend and the possibilities to achieve Digitization and profit from it are various.
Original Equipment Manufacturers (OEMs), Start-ups and Digitization champions have
to join the discussion just as latecomers have to. Diverse application fields can be
111 Definition
derived from different industry sectors and therefore challenge a uniform way of I4.0.
This chapter will provide a few fictitious and real examples on how I4.0 can look like in
various situations.
1.6.1 Fictitious company FiveBike [16]
The fictitious digitized company FiveBike produces electric bicycles. Internal systems
record and process all parts of the value chain like construction, assembly planning and
contracts as well as assembly control digitally. This high level of Digitization allows for
optimal internal networking and digital interfaces towards customers, contractors and
suppliers. It is thus possible to achieve a high level of self-organization and automation,
while it is also enables a exchange of order, product and production data between the
parties involved. FiveBike is mainly an assembly company and therefore a reliable
network of suppliers (tires, bearings, screws, spokes, etc.) and contractors (motors,
frames, etc.) is important, to guarantee quick delivery times. Customers can be end
users, which use a web service to order individual configured bicycles. FiveBike also
produces standard models in higher quantities for distributors. A third business model
is about suppling major customers. They can also the web service to order individual
bikes or use traditional sales contacts. Compared to end customers they order in larger
batches (lot size > 10).
Industry 4.0 is mainly adapted by FiveBike through their order-driven production.
In-house, this influences above all:
• The order management automatically accepts orders from customers and places
orders with suppliers and contractors. Contracts must be suitably negotiated and
optimized to support such an automation.
• Development and construction must design bicycles with respect to the mod-
ular customizable aspects. The bicycles also have to be constructed in a way that
supports automation in the assembly process.
• Controlling has to be interconnected with order management to automatically
process cash flows and invoices.
• Intralogistics, represented by the IT department and IT development. In a
non-order-driven production the second would probably not exist, while it is manda-
tory in this example to have experts developing and maintaining complex software
services and applications.
• Operational Control and Planning must adapt to the digital and automated
processes, especially with regards to personnel management (personnel has to be
familiar with digital workflows or has to be trained).
121 Definition
Assembly, sales, purchasing and marketing are not not influenced that much. Shipping,
service and human resources management are also less affected.
A centralized control system is at the heart of operational order management. Trig-
gered by an order, it checks the necessary parts and, accordingly, checks suppliers to
order parts if necessary. The system then creates a schedule based on the estimated
dates of delivery and the amount of available assembly workers. A precise completion
date can then be provided to the customer. This system means that standard orders
don’t have to be managed by an employee anymore. The employee’s task instead is to
elaborate and continuously renegotiate contracts with suppliers and contractors to allow
for such an automatic order management. He is also responsible to monitor the auto-
mated processes while communicating errors or suggestions for improvement to technical
order managers, software developers and assembly workers. Commercial and technical
order managers discuss their respective orders on a daily basis. Software tools support
them, providing a detailed insight using data and statistics from the central control sys-
tem. The digital insight view enables those jobs to be highly flexible. Monitoring and
planning can be done, given the right equipment, from anywhere at any time. FiveBike
distinguishes between standard and special orders. The later need more intervention by
the respective order manager if special parts have to be ordered from new suppliers.
As soon as a new combination gets available, the configurator has to be updated.
Construction and development engineers get assisted by a system that matches config-
urations, frame measurements and positions for various components. The system also
checks requirements for quality characteristics and assembly possibilities. During produc-
tion and assembly of prototypes product developers have to communicate with suppliers
and assembly workers. This communications ensures that any changes to processes, sup-
ply chains and intralogistics can be considered in an early stage. Those responsible in
the IT department and development can then adapt the software tools and systems to
the changes before the new combination is officially unlocked in the online configurator.
Assembly workers do the assembly for individual orders at FiveBike. Assembly is done
in pairs, working in “boxes” that story parts and tools. Electronic working instructions
that show the current configuration to be build on e.g. a smartphone or tablet are pro-
vided to the workers. A self-organized logistics system uses Kanban-cards and selfdriving
transport devices to enable “condensed” labor. A highly automated production line as-
sembles orders that contain larger quantities. This production line is interconnected and
able to reconfigure itself to adapt to the bicycles configuration it has to assemble.
The given example ends in a conclusion that emphasizes that most current core compe-
tences will still be needed in the future, but those core competences will be additionally
extended by the need for new skills like:
• System competence, an understanding for interconnected intelligent systems
• Process knowledge about the cooperation between physical and digital processes
in CPS
131 Definition
• Interdisciplinary work and learning, especially in the area of technical systems
in the fields of IT, electrical engineering and mechanics, is expected of all employees
• Competences for cooperation, communication and organization are just
as important as those in the fields on technical systems. Employees and executives
have to be “connected” to each other in the same way the digital system is.
• Self-responsibility and self-organized work are especially important when
working with intelligent systems
• decentralized processes, which are required by I4.0, call for a new understanding
of leadership
1.6.2 Digitized service [17]
[17] describes the advantages and the implementation of a solution for digitized service
processes. A system is explained that automates and streamlines service processes of
the Bystronic Group based in Switzerland. All available service technicians are known
to the system with their respective qualifications and skills. As soon as a repair request
is received the system can automatically look for an available technician with the needed
skills. He then will be marked as reserved in the system and a notification will be sent
to his smartphone. The system is connected to the companies ERP-system so that
an automated check for available spare parts can be conducted. Missing parts can be
ordered and directly sent to the customer to prevent incorrect delivery. Delivery dates
are then used to determine when the service technician should arrive, knowing all spare
parts will be available for a successful repair job. Lastly, the system makes sure all
necessary tools are available at said date.
During the service visit the technician uses an app on his smartphone or tablet to
report back about his job. All used spare parts, his working hours, used maintenance and
repair protocols and expenses for accommodation and food are recorded digitally. This
procedure unifies the flow of organizational processes during deployment of a technician.
The needed data is easily available for all other departments (Logistics, HR management,
...) and can be archived. Archived data can later be used to draw conclusions about the
customers situation so that the sales department can adapt his strategy.
The digitized process described is also the basis for new business models, e.g. “Pre-
dictive Maintenance”, in the context of I4.0.
1.6.3 Criteria for I4.0-products - Festo service unit
combinations [18] [19]
In [18] Plattform Industrie 4.0 describes a concept for determining the I4.0 suitability
of products. The used criteria are based on concepts from RAMI 4.0 (see 1.5.1). An
141 Definition
example is given that uses the concept to evaluate a real product, a service unit combi-
nation from FESTO; MSE6-E2M [19]. This product combines the typical functions of a
service unit with additional sensors to measure pressure and flow, internal data record-
ing and processing, a stop valve and various communication interfaces (e.g. Ethernet).
The unit can differentiate between different operating states using Machine-Learning or
fixed thresholds. Detecting those states enables the unit to automatically monitor itself
and operate energy efficient as it can close the stop valve if it detects an idle state.
The goal of Plattform Industrie 4.0 is to establish a standardized concepts to back up
labels like “I4.0-read”, “Sensors I4.0” or “IoT Ready”. Seven criteria should be evaluated
two times; once for the early lifecycle phase (RAMI 4.0 - Type) during development
and once for a later lifecycle phase (RAMI 4.0 - Instance). Further, those criteria are
categorized based on their estimated coverage (C). Those categories are: Mandatory
(M), optional/use case specific (O) and not relevant (N).
151 Definition
Criterion Requirements L C Product characteristics 2018 Energy efficiency modul
1. Identification Cross-manufacturer identification of T M For 1) material number 1) Parts number and product
the asset with unique identifier (ID) (electronic) in accordance key of the manufacturer
attached to the product, with ISO 29002-55 or URI (electronically) readable
electronically readable. I M For 2) serial number or 2) DM code of the
Identification in: unique ID manufacturer
1) Development For 3) manufacturer + serial 3) DM code of the
2) Goods transport (logistics), number or unique ID manufacturer
production With 2) and 3) electronically 4) Participant identification
3) Sales, service, marketing readable, for physical via TCP/UDP and IP network
4) Network products via 2D code or RFID
For 4) participant
identification via IP network
2. I4.0 communication Transfer of product data and data T M Manufacturer makes data CAD drawings, EPLAN macros,
files for interpretation or available/accessible online. instructions, device
simulation, for example; product The data should be relevant description etc.
data in standardized form to customers and
available/accessible with the
assistance of identification,
e.g. pdf via http(s) and URI
Product can be addressed via the I M Administration shell of the Yes, sensors and states can be
network, supplies and accepts data, product can be addressed (at read out. Valve can be
Plug & Produce via I4.0-compliant any time) with the assistance controlled for which purpose
of the identification online via
services. TCP/UDP&IP with at least the a control module with OPC-
information model from OPC- UA application is plugged in.
UA
3. I4.0 semantics Standardized data in the form of T M For 2) catalogue data can be Yes, via link of the DM code
features with cross-manufacturer accessed online in an open
unique identification and syntax for: standard
1) Commercial data I M For 2) and 5) catalogue data Yes, via link of the DM code
2) Catalogue data and data on the lifecycle of
3) Technical data: mechanics, the product instance can be
electronics, functionality, location, accessed online
performance
4) Dynamic data
5) Data on the lifecycle of the
product instance
4. Virtual description Virtual representation in I4.0- T M Relevant information for Product description,
compliant semantics Virtual customers can be accessed catalogue, image, technical
representation across the entire digitally based on the type features, data sheet, CAD
lifecycle. Characteristic attributes of identification (product drawings, EPLAN macros,
the actual component, information description, catalogue, image, instructions, device
on relationships between the technical features, data description etc. are available
attributes, production and sheet, security properties online
production process-relevant etc.)
relationships between Industry 4.0
components, formal description of
relevant functions of the actual
component and its processes.
I M Digital contact to service and DM code leads directly to
information for product service and offers
support including spare part information on spare parts
information from the field
possible
5. I4.0 Services and Definition still open (service system) T O Digital description of the Interfaces are described
states device interface available openly
General interface for loadable I O Information such as states, Data at the interface for all
services and for the reporting of error messages, warnings etc. states are open and available
states. Necessary basic services that available via OPC-UA online
an I4.0 product must support. information model in
accordance with an industry
standard
6. Standard functions Basic standardized functions that T N Not defined First diagnosis and condition
run on various products regardless monitoring functions
of manufacturer and provide the
I N Not defined Also monitoring of the
same data in the same functions.
process with diagnosis output
They serve as the foundation for the
functionality on which all
manufacturers can build their own
enhancements.
7. Security Minimum requirements to ensure T M A threat analysis was Documentation shows that
security functionality. conducted. Appropriate no security capabilities exist
security capabilities were
considered and publicly
documented.
I M The existing security Documentation shows that
capabilities are documented. no security capabilities exist
Suitably secure identities
exist.
Figure 1.6: Characteristics of the energy efficiency module
(Source: Plattform Industrie 4.0)
162 Economical & Social Aspects - A
Literature Review
2.1 Introduction
Industry 4.0 can be defined as a new way to organize the production process thanks
to many innovations in internet of things, digitalization, augmented reality, artificial
intelligence, etc. This new revolution in industry is based on the smart factory, charac-
terized by an interconnection of machinery and systems in the production sites, but also
between the production sites, and with external partners such as consumers or suppliers.
Industry 4.0 has then become one of the central strategical projects of Germany which
encourages this shift in industry. France also has many actors involved through the “Al-
liance Industrie du Futur” which mainly gather firms and academics institutions to
promote and accompany French firms into the digitalization and smart factory era. Sim-
ilar initiatives are also taking place in the United States, in Japan or in China.
But this great transformation, seen as a strategic goal for countries and firms that
wish to remain competitive, will not be accomplished without crucial modifications
in the society. The digitization and automation process inside firms will create many
technological and managerial challenges as well as important implications for consumers.
At a state level, many questions also arise about educational or environmental policies.
Finally, one capital matter will involve the labor market, with many low skilled jobs
threatened by automation and new technological advances.
The goal of this report is then to give a broad view of the existing literature regard-
ing these topics. First, we will see what has been studied regarding the implications
of Industry 4.0 for firms. Then how it impacts consumers. The last two parts will be
dedicated to the implications for workers and for central authorities.
It should be noticed that the whole literature on this subject is fairly recent, with
few articles written before 2015. Nevertheless, we notice a lack of quantitative studies
on the subject, whether it is about the evolution of the labor market, or the adoption
of Industry 4.0 defined with clear indicators by firms. The bulk of the literature is
mostly about giving guidelines for entering Industry 4.0 or about predicting its effects
at various levels. The main ideas most authors seem to agree on are: Firms will benefit
from Industry 4.0 with gains in time and costs while the low-skilled workers will lose
172 Economical & Social Aspects - A Literature Review
their jobs due to automation. This issue on the labor market should be addressed with
an evolving educational and training policy.
2.2 Implications of Industry 4.0 for firms
To start this part on the implications for firms, a paper [20] focuses on giving a broad
view of the benefits and challenges of Industry 4.0 through multiple case studies (n =
46), hence by interviewing managers in firms of various sizes and sectors. What appear
to be the most important benefice of Industry 4.0 is Competitiveness, the ability for
a firm to expand and protect market shares, mainly by innovative offerings. Second
most occurring benefits concerns cost reduction and enhanced value creation. Then
managers quote optimization of process and products, novel business models, resource
efficiency and gains of time. As for the challenges, the most recurrent is said to be
about “technical integration” of the Industry 4.0 paradigms. Implementing intra-firm
and inter-firm connection requires a lot of transformations and modernization of the
production facilities. Companies also fear the implementations of immature technologies,
which could harm production. Second most important challenge is the “organizational
transformation” which implies a corporate culture where every agent is convinced of
the need to shift to Industry 4.0 methods and paradigms. Managers also cite a lot of
challenges about data security, competition (increased by Industry 4.0) and cooperation
(with suppliers and customers).
These are the main opportunities and challenges faced by firms regarding Industry
4.0, and we will give more details about them in the next sections.
Additional to the overview of Kiel et al. [20], Herrmann [21] list several risks of smart
factories:
• Standardization. Industry 4.0 can only be efficient if systems intra-firm and inter-
firm are standardized. Failing to do so will harm the benefits of Industry 4.0.
• Information-security. The information security experience in industrial companies
can currently be assessed as rather low. Failing to upgrade could harm the com-
panies.
• Availability of Fast Internet. Most of the paradigms of Industry 4.0 rely on internet
connection. Failing to have powerful internet connection could paralyze the firm
of not allowing to reach full intensity.
• Organizational risks. “The company organization plays an important role espe-
cially at the highest hierarchy level. Management must define a clear strategy and
plan for digitalization and demonstrate an understanding of IT and processes”.
182 Economical & Social Aspects - A Literature Review
Figure 2.1: Humans, organization, and technology model (Source: Oks et al. [23])
2.2.1 Implementation of Industry 4.0 paradigm in the firm
One crucial stake for firms is the implementation, whether technological or organi-
zational, of Industry 4.0 in firms. Veile et al. [22] take interest in the question, and
give insight from the best practices. As schematized by Oks et al. [23], implementation
touches three dimensions: Technological, organizational, and human (figure 2.1).
At the human level, Veile et al. [22] tell us that firms need to adapt the employees’
tasks, as with automation, the work required by them change. Employees will be more
involved in mental activities and decision making. Formations and education will then
be crucial for employees to adapt to this new environment. This recommendations
are also present in several articles : Erol et al. [24] emphasize the need for employees
to have confidence in technologies. They need to have fundamental understanding of
automation technologies and data analysis [24, 25]. Employees also need to be aware
of security implications and data abuse issues [25]. Furthermore Kagermann et al. [26]
state that people in the firm should be aware of the interconnected nature of the system
that are working with, and themselves have interdisciplinary knowledge. Kiel et al. [20]
recommends that firms work closely with school and universities in order to provide the
skills needed for Industry 4.0 environment employees. Trainings, education programs
and e-learning are recommended by many [24, 27, 28]. However, it should be noted
that as technology will develop, intuitive design will probably require less training over
time [22].
Benesova & Tupa [29] provide a detailed list of the qualifications needed by firms to
run an Industry 4.0 factory (figure 2.2).
At the organization level, Veile et al. [22] find that in order to implement Industry 4.0,
firms need to adapt their corporate culture and communication. Management should
serve as a role model, leading towards change, but in an incremental rather than radical
192 Economical & Social Aspects - A Literature Review
Figure 2.2: Qualification and skills (Source: Benesova & Tupa [29])
202 Economical & Social Aspects - A Literature Review
way. The corporate cultural changes required are many: Willingness to learn, promotion
of creativity and innovation and recognition of the customer and its needs.
The organizational structure of the firm should be revised. Industry 4.0 needs an
“agile” organization, which encompass flat and weak defined hierarchies, flexible struc-
tures and processes and decentralized settings. This agile organization will allow bet-
ter Industry 4.0” implementation by enabling faster decision-making and promoting
entrepreneurial spirit. Management should also adapt to the agile organization. Imple-
mentation of Industry 4.0 could go through pilot projects to test and evaluate benefits
and challenges of these new practices. The role of organization in an optimal imple-
mentation of Industry 4.0 is also emphasized by Schuh et al. [25] who state that the
organization structure must be agile and implies that employees might face frequent
changes of tasks as well as affiliations to teams. Employees should also be organized
in communities, matching their ability to work on certain issues for a period of time.
Less formal organizational structures are said to support decentralized and optimized
decision-making in Industry 4.0 factories [30, 31]. It is also important for firms to focus
on their core competencies and so outsource value creation processes, hence cooperate
with partners [32–34].
At the technological level, Veile et al. [22] recognizes a great challenge for firms imple-
menting Industry 4.0 technologies which is about security and safety. Indeed firms will
need to protect themselves from external actors and interferences. External partners and
customers are the main interferences. To protect themselves, firms can apply specific
security systems and so security experts will be needed in the firm to run the security
system.
To prepare new Industry 4.0 technologies adoptions, firms should seek internal and
external knowledge. External sources can be the best practices used by other firms
or academic literature. Internal sources are firms’ own R&D branches and a constant
learning by mistakes. Still according to Veile et al. [22] the key elements of technological
implementation of Industry 4.0 are:
• A proper understanding of new technologies and trends.
• Acquire new hardware components such as radio-frequency identification (RFID),
Network connections, sensors, micro-processors and actuators to collect machine
data and allow analyses.
• Software adaptations in order to digitally connect all processes and systems, and
storing the data in clouds.
• Secure and standardized interfaces to prevent information losses.
• Retrofit of the existing infrastructures and systems.
212 Economical & Social Aspects - A Literature Review
Veile et al. [22] provide a framework of Industry 4.0 implementation in figure 2.3(a).
Furthermore, they give an overview of the existing literature on the key aspects of
implementing Industry 4.0 in firms in the figure 2.3(b).
222 Economical & Social Aspects - A Literature Review
(a) Framework of Industry 4.0 implementation
(b) Literature on the key aspects of implementing Industry 4.0
Figure 2.3: Source: Veile et al. [22]
232 Economical & Social Aspects - A Literature Review
2.2.2 Geographical environment for Industry 4.0 firms
An important aspect for a firm is about the environment it chooses to evolve in.
If the last decades have seen many firms from developed countries offshoring many of
their activities to third-world countries to reduce their costs, the many advantages of
Industry 4.0 could provoke a new trend toward “re-shoring” or “back-shoring”, hence
the return of some or all of the activities of the firms that did offshore before. Arlbjørn
& Mikkelsen [35] have found through a study about firms in Denmark that many jobs
could be maintained in the home country thanks to automation. Foerstl et al. [36] and
Bailey & De Propris [37] also believes Industry 4.0 could be beneficial for reshoring ac-
tivities. Indeed automation and digitalization imply less reliance on labor which was a
key reason for firm to offshore their activities [38,39]. It thus has started an exploration
of the advantages of these technologies to permit back shoring activities [34, 40, 41]. It
should be noted though that a recent study [42] finds a low rate (14%) of backshoring
firms adopting Industry 4.0 technologies.
The second environment-related variable a firm can act on is whether it chooses to
be part of a a geographical cluster or not. Clusters of firms are said to allow building
common language, trustful relations and enhance interactive learning, all beneficial to
innovation and better supply chains. On the other hand, Industry 4.0, which allow
long-distance communication and cooperation might seem to reduce the need for geo-
graphical agglomeration. But in fact Götz & Jankowska [43] state that Industry 4.0 and
clusters work well together. To quote them, they propose that “Clusters are conducive
environment for testing Industry 4.0 technologies and provide an incubator for Industry
4.0 development (experimental laboratory).”
Figure 2.4: Steps towards new technology/industry
242 Economical & Social Aspects - A Literature Review
It is then showed that Industry 4.0 induces several changes in the way firms choose
to geographically establish themselves. Adopting this new paradigm could allow them
to stop offshoring, and maybe even backshoring their activities. They also still have a
great incentive to be localized near other firms, inside clusters, particularly as Industry
4.0 still entails a lot of uncertainty, hence to develop platforms of collaboration and to
share the risk with other firms.
2.3 Implications of Industry 4.0 for Customers
2.3.1 Industry 4.0 provides a better comprehension of customers’
demand
Nowadays, Industry 4.0 plays an important role in our everyday lives, reshapes busi-
ness models, and products and services portfolios. Based on smart technologies, data
analysis, Internet of Things (IoT), Internet of Services (IoS) and huge innovative in-
vestments, Industry 4.0 allows any object and people to be connected anytime and
anywhere, with anything and anyone, using any path and any service [44]. Moreover, all
these technologies enable device-to-device and human-to-device interactions in a reliable
and robust manner [45]. In this section, we offer to present a literature revue about the
impact of the digital disruption for customers.
First, Industry 4.0 paradigm, also seen as the 4th Industrial Revolution, creates a
convergence between physical products and services, and virtual world, based on ad-
vanced digitalization techniques. To do so, firms use in particular Cyber-Physical Sys-
tems (CPS), accompanied by computer-based processes, allowing an interaction between
physical and digital workflows.
CPS are systems of collaborating computational entities which are in intensive con-
nection and interaction with the surrounding physical world and its on-going processes,
providing and using, at the same time, data-accessing and data-processing services avail-
able on the internet [46]. CPS allow interactions between cyber space and virtual systems
and integrate them to production systems with physical control. These systems bring
together many areas, such as cyber disciplines (software, cloud, IT. . . ) or physical ones
(mechanical, electrical. . . ), including compute and storage capacities, mechanics and
electronics, based on the Internet as a communication medium [47].
The potential of CPS to change customers lives is wide. Indeed, thanks to their com-
plexity and the combination of heterogeneous disciplines, as previously mentioned, they
can be used to produce customized and innovative goods and services, in order to an-
swer heterogeneous needs. They target size 1 production with shortened deadlines and
similar costs to mass production [48]. CPS also allow continuous interactions between
humans (Consumers to consumers, C2C), between humans and machines (Consumers to
252 Economical & Social Aspects - A Literature Review
machines, C2M), but also between machines (Machines to machines, M2M), thanks to
intelligent systems and machine learning, among other smart technologies [49]. Hence,
existing literature agreed on the fact that Industry 4.0 is a combination of traditional
optimized industrial manufacturing and advanced innovative technologies [47].
Second, data analysis is at the center of the 4th Industrial Revolution and have a
significant impact on value creation. Indeed, it allows firms to quickly and efficiently
extract and analyze large datasets, in order to predict customers’ demand, and provide
them products and services fitting perfectly to their needs.
Industry 4.0 comes with CPS, Internet of Things (IoT), Internet of Services (IoS),
Cloud Computing (CC), and more generally smart factories. According to Li et al. [49],
“all these trends have in common the integration of several features in the same place as
a response to challenges of computerized decision making and big data that are prolif-
erated by the internet and cloud computing”. Thus, thanks to these systems developed
during the 3rd Industrial Revolution and its improvements in digitalization, industries
can elaborate better responses to customers’ needs and enhance their utility [49]. The
best tool to achieve this goal is the use of data analysis, and more specifically Big Data.
Chong et al. [50] carried a full study to assess the role of Big Data, Internet and
e-services in business models. They argued that these tools can help reaching a better
understanding and predicting of product demand. They also show that manufacturers
can use online shops and marketplaces as predictors of customers’ needs, using the ex-
ample of Amazon.com. This would allow firms to predict their product demand. Indeed,
online marketplaces are becoming much more efficient than traditional ways of selling
products because they provide online reviews services, which are important predictors
of products sales, paying attention to customers’ requests.
Industry 4.0 is organized around communication channels, that enable exchanges of
information about customers’ needs, technical aspects of production, workers, resources
allocation, downstream and upstream partners, manufacturers and so on. It implies
exchanges of huge amounts of various types of data, collected continuously. Firms can
measure what customers like, what they buy or look at, but also how they are in-
fluenced by advertising, promotions and reviews. They can use Big Data to predict
rigorously customers’ demand, processing huge amounts of data in real time [38]. Large
amounts of data are collected and sent to smart services and production systems to
be analyzed. Thanks to this automation of data processing, products and services can
be customer-adapted. It increases value added for both customers and firms and offer
services and products in real time, perfectly adapted to market demand. Big Data, busi-
ness and data analytics and systems thinking offer leaders in management a systematic
way of thinking for increased understanding and more effective work [28]. These tools
help firms in their decision-making processes, analyzing trends of markets because they
provide a deep understanding of customers’ needs and behaviors. As a result, customers
26You can also read
