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Whitepaper - Industry 4.0: From vision to implementation


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Starting from the three elements task, product and factory, specific projects will be developed to shape the vision of Industry 4.0 and illustrated with practical examples. These will be assessed for Industry 4.0 according to their investment needs and strategic value input. Tips for the development of the necessary strategy and new software architecture follow this article.
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Scheer GmbH
Uni-Campus Nord
66123 Saarbrücken
AWS Institute for Digital
Products and Processes gGmbH
Uni-Campus Nord
66123 Saarbrücken
Tel.: +49 681 93511-0
Fax: +49 681 93511-100
Tel.: +49 681 93511-0
Fax: +49 681 93511-111
Industry 4.0: From Vision to Implementation
Industry 4.0: From vision to implementation ............................................................... 1
A. What lies behind the term Industry 4.0? ............................................................... 2
B. Business drivers for I4.0 ....................................................................................... 4
I. „Smart Factory“ .............................................................................................. 5
II. Product view .................................................................................................. 8
III. Logistics ....................................................................................................... 10
IV. New Business models in I4.0 ....................................................................... 11
C. Implementation strategies for I4.0. ..................................................................... 12
I. Strategy 1: Blue Ocean Strategy .................................................................. 12
II. Step by step concepts .................................................................................. 14
III. Smart Services ............................................................................................. 17
D. Roadmap to I4.0 ................................................................................................. 20
E. New demands on IT Systems ............................................................................ 21
F. Complementary concepts to I4.0 ........................................................................ 24
Reference list ............................................................................................................ 25
Figure 1: Industry 4.0: The Big Change ...................................................................... 4
Figure2: Implementation Strategy ............................................................................. 12
Figure 3: Scheer BPaaS Platform Architecture ......................................................... 23
Industry 4.0: From vision to Implementation
Industry 4.0: From vision to implementation
Prof. Dr. Dr. h.c. mult. August-Wilhelm Scheer, Scheer GmbH; AWS Institute for
Digital Products and Processes gGmbH, Saarbrücken,,
The content of this whitepaper appears as an article in the specialist magazine
Starting from the three elements task, product and factory, specific projects will be
developed to shape the vision of Industry 4.0 and illustrated with practical examples.
These will be assessed for Industry 4.0 according to their investment needs and
strategic value input. Tips for the development of the necessary strategy and new
software architecture follow this article.
Industry 4.0
Open Innovation
Product Lifecycle Management
Smart Factory
Smart Services
About the author:
Prof. Dr. Dr. h.c. mult. August-Wilhelm Scheer is the sole shareholder and Managing
Director of the Scheer Holding GmbH in Saarbruecken and shareholder and
chairman of the advisory board of Scheer GmbH, a company founded under the roof
of this Holding. He is emeritus Professor of Business Administration, in particular
information systems, at the University of the Saarland and founder of the AWSi, the
AWS Institute for Digital Products and Processes.
Industry 4.0: From vision to Implementation
A. What lies behind the term Industry 4.0?
The expression Industry 4.0 (I4.0) emerged out of a working group of the research
alliance for the development of a vision for a future industrial landscape influenced by
the internet. The term was, in particular, shaped by the leaders of the group Prof. Dr.
Henning Kagermann, Prof. Dr. Dr. h.c. mult. Wolfgang Wahlster as well as Prof. Dr.
Wolf-Dieter Lukas (The Research Alliance was a group set up by the Federal Ministry
of Education and Research with representatives from research, business and the
community for the development of guidelines for the high-tech strategy of the Federal
Government to which the author also belonged)
The term is designed to describe the fourth industrial revolution triggered by the
internet. The numbering methodology is justified by the invention of the steam
engine, production line organisation, automation and now the entry of the internet
into industrial organisations. This numbering methodology is disputed: for example,
the well-known futurologist Jeremy Rifkin speaks merely of the third industrial
revolution (cp. Rifkin, 2014). If one has no “inherent” charisma, a number of
behavioural patterns can give specific help.
However you view it, the term I4.0 has spread rapidly and established itself in
science and practice as a buzz-word that challenges. For example, the large
business associations ZVEI (Electrical and Electronic Manufacturers Association),
VDMA (German Engineering Association) and BITKOM (Federal Association for
Information Technology, Telecommunications and New Media) have joined together,
consolidated under the BDI, to develop a common platform for I4.0 and in almost
every larger industrial concern I4.0 is a major topic of discussion. In the USA the
topic is handled by the Industrial Internet Consortium (IIC) to which the country’s
most significant industrial and IT companies belong. German companies also work
with the IIC.
Specialist scientific organisations in German business administration teaching are
also addressing the subject of I4.0, albeit a little slowly. It should be noted that, for
business administration teaching, the organisation of an industrial concern, in
particular through the work of Erich Gutenberg and his school, has always been
Industry 4.0: From vision to Implementation
viewed with particular importance. Many planning processes and accounting systems
were developed especially for industrial organisations.
The invention of the term I4.0 does not automatically mean that the subject can be
competently mastered and implemented. It therefore behoves German science and
industry to show that not only has a vision been created, but also that it can be
competently implemented.
The definitions of I4.0 are many facetted and complex. Many take up more than a ½
DIN A4 page and are extremely technically oriented. In particular, the main focus is
often placed singularly on factory automation. In contrast, it shall be shown here how
new information technologies led by the internet (in particular the Internet of Things)
affect all the significant functions of an industrial concern and are leading to new
business models with new products and services as well as business processes.
This significant development, known also as the Digitisation of the Economy is
affecting all sectors so that I4.0 stands out as just one view of a particular sector.
The term Internet of Things is designed to convey that not only people communicate
via the internet but also all “things” such as materials, products and machines.
Internet communication conventions (Internet Protocol IP) are used here: each
“thing” is allocated an IP address. With this new form IPv6, 3.4 x 10 to the power of
38 addresses are available, meaning that the allocation of addresses is not a
technical hurdle. In this sense the term “Internet of Everything” is also used.
In the following article an overview of the starting points relevant to business
administration for I4.0 will be given initially, then however the main focus will be
placed on the implementation strategies currently being observed by companies. The
author draws on his experiences gained from research, consultancy and
implementation projects run by the 8 innovative IT companies in the Scheer Group.
Industry 4.0: From vision to Implementation
B. Business drivers for I4.0
The availability of a new technology alone does not mean that its use can be
commercially justified, i.e. that industrial companies benefit from it. The gain often
comes first through new organisational possibilities.
Significant new technologies from I4.0, and in particular the business administrative
drivers that deliver benefits, will be examined in the following article.
The author’s Y-model (Figure 1) shows the significant productive process types of an
industrial company where the effects of I4.0 on them are explained in the sections
that follow. The model goes back to work the author undertook in the 1980s on the
subject of Computer Integrated Manufacturing (CIM) (cp. Scheer, 1990). Back then,
similar concepts were discussed but could not be realised due to the underdeveloped
status of information technology. With today’s technology however these ideas can
be re-visited and expanded upon.
Figure 1: Industry 4.0: The Big Change
Graphic symbols in the Y-Model show functions and the bars contain the operational
driving forces from I4.0. Significant technologies associated with I4.0 are shown
outside these.
Industry 4.0: From vision to Implementation
The upper sections of the Y model show planning activities, the lower sections show
the short term control and realisation layer.
The left side branch of the Y-Model shows order driven business processes in an
industrial company. Procurement orders for the required materials and resources and
production orders for items to be produced derive from customer orders. The
planning and control of these orders are designated as logistics. External logistics
constitutes the relationship to the customer and suppliers; internal logistics
constitutes the internal order processing task.
The right hand side of the Y model shows processes necessary for the products to
be made. Through the use of CAD/CAE systems the research and development
processes in the upper right hand side create the geometric product descriptions
and, through the work plans, the manufacturing rules (work plans). The machine
resources required are defined from the factory planning.
Logistics and product related processes are closely connected in the factory. Items to
be produced are assigned by the manufacturing rules to resources in line with type,
quantity, time and quality, the production promptly controlled and the results
recorded. The finished products are then passed to the shipping department and
delivered to the client.
The financial accounts and controlling departments accompany the process from a
value viewpoint but are not in the foreground.
The three significant starting points, factory, product development as well as
procurement and sales logistics are addressed in the following sections.
I. „Smart Factory“
Significant new I4.0 technologies in the factory are so-called Cyber Physical Systems
(CPS). These are software intensive production systems connected to the internet
and able to communicate with each other as well as with intelligent materials.
Materials are described as intelligent if they carry their properties such as quality and
manufacturing steps with them in a data storage system (chip). Via Radio Frequency
Identification (RFID) technologies these materials can navigate their way through the
Industry 4.0: From vision to Implementation
manufacturing process practically independently. CPS systems and materials
coordinate capacity needs and offers over a quasi-marketplace. Should a CPS
suddenly fail, then another system can automatically take over the function and the
system organises the flow of materials itself independently.
The organisational driver for business management is the ability of a factory to self-
organise virtually without human input. This is a form of extreme decentralisation. In
the last 40 years a trend towards decentralising factory control has been clearly
recognisable and this is now being pushed to the extreme. Up till the 1980s a
centralised approach was dominant: production orders were defined by a centralised
planning process leading, in turn, to these being completed in the factory. A wide
variety of interruptions in the factory led to plans becoming almost immediately out-
of-date rendering the centralised approach a failure. As a next step the factory was
split into smaller organisational units (production islands, control station areas,
flexible production systems, and handling centres) which afforded a certain degree of
autonomy. End-to-end self-control of the production process is the logical
consequence of this development. If all the elements contributing to a system
understand their status, and the demands of the task at hand are known, then
algorithms can provide the solution to the problem of coordination.
In an expanded function, self-organisation leads to self-optimisation. If, for example,
it is recognised that part of a machine has become worn, then production
components for which the condition of the machine is sufficient can be allocated
The high flexibility of CPS makes possible the strong individualisation of the
manufacturing process as the changeover of system processes takes place with no
loss of time and therefore also with no costs. For this reason, the long discussed
manufacture of quantities with batch size 1 is possible at the cost of mass production.
A further significant technology is the cost effective storability of mass data in the
production process (big data), made possible by price reductions in storage media
and new “in memory” database technologies (the saving of data in the computer’s
memory and not in external storage mediums, thus the term “in-memory”). Sensors
Industry 4.0: From vision to Implementation
measure the condition of machines, materials and production peripherals in real time.
Analytical evaluation processes should not only explain past performance, rather
they should use actual conditions to trigger immediate action and, beyond this, give
indications of expected future system performance. The best known example is that
of predictive maintenance in which the current performance of the system points
towards abnormalities leading, for example, to the advice that a particular component
may need to be replaced in the near future.
The grade of fineness in data collection is as good as user-definable in its degree of
sophistication. Thus, per machine, for example a turbine or a compressor, 100-200
measuring points can be defined which can be queried in real time. The data volume
to be processed is then correspondingly high.
In Figure 1 a sample of the energy consumption of a machine over a period of many
seconds is provided. Through real time analysis, it can be determined whether the
system, through irregular energy consumption, requires any maintenance.
Collectively, the combination of technologies is leading to the vision of a factory able
to control itself in real time.
An intermediate level is currently provided by so-called Manufacturing Execution
Systems (MES) that serve as an intermediate layer between the factory and the
upper parts of the Y model and are responsible for the filtering and compression of
data. It is to be expected that hierarchical approaches will disappear more and more
and that all components of an industrial operation will communicate directly with each
This certainly increases the complexity of the entire system immensely so that the
end-to-end realisation of the vision of a smart factory should be viewed with caution.
It should be remembered that 30 years ago, during the discussion around CIM
concepts, the intrinsically and logically sensible concepts quickly fell into disrepute
due to their high costs or lack of any possibility to implement them. For this reason
the smart factory should by all means be defined as a target, but one accompanied
by realistic implementation steps. This point will be revisited in Section 3.
Industry 4.0: From vision to Implementation
II. Product view
The upper right hand side of the Y model shows product development as well as the
development of closely related services.
The strong flexibility of the manufacturing process up to batch size 1 manufacturing
demands the stronger individualisation of product development. This can bring
competitive advantages and thus yield the benefits of factory automation.
Specifically, this means that the number of product variations can be increased right
up to the completely individual production for a client. This is shown graphically in
Figure 1 though the individual production of a running shoe for a client. This can lead
to far-reaching consequences. As a rule, customers do not want to wait long for their
product, so individualisation demands that the production location needs to move
closer to where the client is. In other words, the individual design of a running shoe is
of little use if the product needs to be made far away in Asia and the client must wait
weeks or months for delivery. New technologies, such as 3-D printing for example (in
which a part is produced out of a geometric 3-D model in multiple layers of material),
enable the immediate production of a replacement part otherwise unavailable for
delivery. Concepts such as the speed-factory from Adidas even enable the
presentation of the direct manufacture of a running shoe in the shop following a scan
for the fit.
In any event, 3-D printing has already increased the speed of development of new
products through the faster development of prototypes (rapid prototyping)
New product ideas can be generated not only by the company’s own development
department, but also by the systematic involvement of further employees in the
business, customers, and suppliers and right up to anyone with an interest.
This can take place through the use of internet forums and is known as „open
In an I4.0 environment with intelligent materials and processing equipment, all
activities undertaken over the lifetime of a product, such as repairs, maintenance,
adjustments etc. as well as the application and application conditions of the product
can be automatically recorded and stored. This leads to the concept of transparent
Industry 4.0: From vision to Implementation
product lifecycle management (PLM). This also leads to immense amounts of data
that can only be handled by the Big Data techniques touched upon. Analysis of this
data, alongside the legally required traceability of parts in respect of warranties, can
lead above all to suggestions for product improvements and the optimisation of
operating conditions. In doing so, individual product data can be stored in a chip in
the product itself or in the manufacturer’s database.
Evaluation of PLM data by the manufacturer brings new possibilities in product
related services. Predictive maintenance provided by the company’s own
maintenance team has already been referred to with the capture of machine data in
the factory. But only the data of individual machines is available.
If the machine manufacturer itself captures the data from ALL the machines it has
made, then it has an incomparably large amount of data and can define and produce
cross comparisons about machine performance as it sees fit. For example, if a
manufacturer has agreed maintenance contracts with its customers it can optimise
the maintenance process with its ability to determine appropriate measures before
the engineer visits or by being able to determine the time of visit individually based
on need.
Many machine manufacturers already earn significant amounts through maintenance
contracts. This ability can be further strengthened through PLM.
An extreme further development in maintenance services is the takeover of operating
responsibility for machines by the manufacturer itself. This concept is known as BOO
build, own, operate. The manufacturer knows its machines and production facilities
best and is able, via PLM data, to analyse their performance and optimise their
operation dependent on all operating conditions. It is therefore likely that the
manufacturer will operate systems itself at clients or in production facilities it has set
up itself. The client is no longer buying plant or machinery, it is receiving and paying
for a service.
Manufacturers of aero engines no longer sell their systems today with the
aeroplanes, rather they lease the systems to the airlines, control their performance in
real time, undertake maintenance and price their service on the basis of the flying
Industry 4.0: From vision to Implementation
time delivered. The airline can thereby concentrate on its core business.
Manufacturers of medical equipment (for example dialysis machines) sell their
systems not only to hospitals, but also run corresponding provision centres and sell
services such as increasing the quality of life, or cleansed blood, rather than
machines. This trend is being continued in the context of I4.0 and more and more
industrial companies are taking on the character of service providers. Car
manufacturers see themselves as providers of mobility and are setting up
subsidiaries that rent out their own cars in the form of car sharing.
III. Logistics
The upper left hand side of the Y-Model Logistics is also being significantly
changed by I4.0.
In the first instance a customer can issue orders, change them or cancel them,
through many different channels (omni-channel) such as standard computers,
laptops or smart phones. The supplier’s order capture and processing system must
behave transparently vis-à-vis the differing entry channels: it must be omni-channel
capable. All channels must be usable in a mix: this means, for example, that a client
can place an order via a standard computer but then change or cancel it via a smart
This means technically that the user interface must be adapted automatically to the
medium. Together with individualisation, a client’s ease of access to a supplier leads
to increased instances of change and thereby to the increased demands on flexibility
of product design and manufacture already described. The customer can change
what he originally specified, for example the colour of his car, virtually just before the
start of the manufacturing process.
Only when the flexibility of product development and manufacture becomes clear to
the customer, will he or she see the benefits of I4.0.
The individualisation of products through increased variations of type and customer
individual manufacture increases the number of suppliers and diminishes the
manufacturing depth of a company. New suppliers must be identified quickly and
immediately integrated into the supplier network. Interruptions within the supply chain
Industry 4.0: From vision to Implementation
must be identified early and dealt with quickly. The call-off of pre-products and
materials will become divided into smaller sections.
The entire network must become transparent at any one moment for all involved. The
information relationships for call-offs between a direct supplier and recipient found
today are no longer sufficient. In fact the entire supply chain network must become
transparent. In the RFID-based Automotive Network (RAN) research project
sponsored by the German Federal Ministry of Economic Affairs, this has been
achieved as a prototype by the use of a centralised virtual database and RFID
technologies for the automobile industry and its suppliers and is currently being
implemented for real by some of the parties involved. In Figure 1 this approach has
been indicated graphically via a network in which all nodes are connected via a
virtual central database.
IV. New Business models in I4.0
With the description of the three starting points for I4.0, factory, product and logistics,
it has already become clear how much the business administrative drivers,
individualisation, decentralisation, self-control, open innovation, service orientation
and transparency will change companies. New business models are being created.
One business model describes the basic principle upon which a company creates its
performance and value; in short how it achieves its turnover and profit.
It consists of a revenue model that describes whether, for example, the company
achieves its revenues more through services such as maintenance, BOO (build, own,
operate) or through the sale of its products. With I4.0 the revenue model can be even
more complicated if a customer can “pay” with data about the use of a product, rather
than with money, as the manufacturer can use this data to offer new services.
A further component of a business model is the resource model that describes the
resources required by a company. With I4.0 this model is of particular importance as
with this model the investment sums necessary are determined. Without expanding
further on the description, it is enough to say that, in the context of I4.0 far reaching
strategic concepts need to be discussed around the definition of this business model.
Industry 4.0: From vision to Implementation
C. Implementation strategies for I4.0.
The following section looks at implementation approaches being conducted in
practice. In figure 2 these are shown in the x-axis in order of the investment
necessary. The amount of the investment stands for the degree of complexity as well
as the effort required in time. Shown in the y-axis is the extent to which the aim of
complete fulfilment of the I4.0 vision has been reached, or respectively how much of
the strategy can be reached. The vertical line shows the starting point and potential
of the strategy.
Figure2: Implementation Strategy
I. Strategy 1: Blue Ocean Strategy
With a Blue Ocean Strategy (no 1 in Figure 2) disruptive innovation through I4.0 is
strived for (cp. Kim/Mauborgne, 2005). This means that a break with the existing is
made and that, by virtually following a green-field strategy, a new company with a
new business model is created. An example of this is Google Car. As of now a car
spends 95% of its time stationary and is driven for only 5% of the time. Google Car
aims to reverse this relationship: the car should be driven 95% of the time and
remain stationary for only 5% of the time. This leads to the requirement of a car
sharing concept and driverless service in order that, having reached its destination, a
car can be delivered to its next user. Instead of the ownership of a car, the principle
of the accessibility of mobility comes to the fore. Google propagates a 10 x model
Industry 4.0: From vision to Implementation
quite emphatically: this means that innovation does not aim to provide a gradual
improvement, rather it should be 10 x better than the existing concept. The Tesla
car, with its uncompromising electronic approach can be seen as an example of a
Blue Ocean strategy.
The characteristic of a blue ocean strategy is not that an existing business model is
further optimised, it is rather that it is broken with, with as many of the principles as
possible. The mobility concept of UBER-POP also breaks with the principle of a
commercial taxi service and follows the principles of a service without marginal costs,
whereas, for example the MyTaxi system merely provides for the digitisation of a taxi
central office and can therefore be seen as a continuation of innovation.
Disruptive innovations are often associated with high capital requirements. It is clear
from the outset that breakeven can only be reached only after a number of years (5-
10). The financing can therefore come from a highly profitable independent business
sector (Google) of from third party investors (Tesla).
In Germany, as opposed the USA, the Blue Ocean Strategy for I4.0 is hardly
discernible. This may lie in the fact that (for the time being) German industry
continues to be very successful with its traditional business models and therefore,
because of an investor’s dilemma-effect, is wary of disruptive concepts. The
comparable willingness to undertake very risky investments through venture capital
businesses and wealthy business angels is also missing. If anything, the German
automobile industry itself is only coasting towards a transition to electro-mobility.
Admittedly, approaches such as the construction of a new factory for the company
Wittenstein in Felbach are giving disruptive impulses, as here, for example,
ecological, energy and production technological innovations are being implemented
concurrently. The factory is being constructed in a residential area so that employees
do not have far to travel to work, the environmental impact is being drastically
reduced by the use of new energy concepts and production is being highly
Also the fact that a traditional machine construction company such as Trumpf has
been granted a full banking licence and is therefore setting the scene for a new
business model as a financial services provider, as well as seller of its products,
Industry 4.0: From vision to Implementation
carries disruptive potential within it. A tendency in Germany exists that I4.0 projects
are more likely to be realised by hidden champions in mid-sized industrial companies
than by “lighthouse” projects backed by large marketing budgets. This illustrates, for
example, the enthusiastic engagement of internationally successful mid-sized
companies such as Claas, Miele or Harting in the “excellence cluster” in East
Westphalia Lippe OWL.
In Figure 2 the disruptive strategy 1 is distinguished though a high capital
requirement and a high degree of realisation for the vision of I4.0.
II. Step by step concepts
In many cases it can be seen that German companies are approaching the vision of
I4.0 step by step
Strategy 2: Solving conventional problems with new technologies
As yet complex or unsatisfactory individual solutions to problems can be re-visited
with I4.0 techniques. There are many examples of this that can be named.
For example, a machine manufacturer can reduce internal material transport runs
(milk runs) through the mobile querying of material stocks at production or assembly
stations by switching from fixed transport run plans to runs controlled by need, this
avoiding empty trips.
Through the use of 3D scanners, a manufacturer of agricultural machines has
improved precision and quality by the connection of the body work to the chassis (the
so called “marriage”) thus avoiding time wasting re-working.
A screw manufacturer improves its Kanban system by building sensors and cameras
into the Kanban container so that stocks can be controlled continuously without
human visual checks.
A car parts manufacturer improves its goods-in process through the use of RFID
technology to automate counting controls and warehousing.
In Figure 2 these approaches are characterised by a comparatively modest capital
requirement that, due to their specialist nature, nevertheless yield only limited
potential for the I4.0 vision.
Industry 4.0: From vision to Implementation
Strategy 3: I4.0 Factory Islands
A car parts manufacturer installs a new production line following I4.0 principles. All
work stations are connected to the internet and fulfil CPS criteria. Material flows are
mostly controlled themselves using RFID techniques. High substitution possibilities
exist between the production systems in cases of interruption. Materials and
equipment are monitored in real time by sensors and maintained predictively (cp.
Lepratti et al., 2014). The example is in itself already impressive but has only pilot
project character in relation to the whole company.
A mid-sized foundry business implements a Manufacturing Execution System (MES)
in order to connect the data capture systems (Borland Database Engine or BDE) to
the control layer and to build a data filter to the planning systems lying above it.
This example shows an approach valid for the entire manufacturing process moving
in the direction of real-time manufacturing, but it is missing the use of CPS. The
hierarchical approach of an MES in fact contradicts the principle of self-control but
can act as a transit station towards I4.0 as, in terms of the whole architecture, a
standardisation of procedures results.
Although only minor aspects of I4.0 have been tracked, the examples require high
capital input and can be seen as starting points for further steps. Nevertheless, it is
only factory organisation that has been addressed; new business models have hardly
been discussed.
Strategy 4: PLM and Open Innovation Islands
A manufacturer of motors sets up a product memory database in line with PLM. At
the same time it reorganises its development department. Alongside the construction
data, the manufacturing parts lists and the work plans were removed from the ERP
system and included in a new product database. In total, these measures indicate a
new information systems architecture for the company. The focus is on the creation
and administration of product related data thus accommodating the trend towards
greater product variations and product individuality. The logistics functions in sales
and procurement, as well as in production planning become applications accessing a
product database and no longer require the administration necessary with current
ERP systems.
Industry 4.0: From vision to Implementation
A toy manufacturer involves its customers in the product development process by
offering payment for outstanding new product ideas. Suggestions can be outlined
and submitted via the internet using a simple CAD system.
In Figure 2, the first example is used as a benchmark. It leads to end-to-end flexibility
in product design and opens the way to new business models. Nevertheless, large
capital contributions are required for the organisational and technical rearrangement
of the development process. Strategies 4 and 3 have been ranked accordingly.
Strategy 5: Logistics Islands
The end-to-end re-organisation of supply chain management requires the
involvement of customers and suppliers as well, possibly over multiple stages as
already implied by the description of the RAN project above.
From the viewpoint of an individual company, improved flexibility and cost savings
can be achieved through the integration of direct suppliers and customers as well as
transport systems. The end-to-end use of RFID technologies as well as real time
monitoring of transport statistics gives early indications of expected arrival times as
well as contents based on type, measurements and quantity.
Sensors placed on the transport route capture specific incidents such as unusual
temperatures or vibrations. Early indications are given of any necessary individual
delivery checks. RFID controlled goods yard management regulates the transport
from the entry gate to arrival in the warehouse. Notification of means of transport and
the allocation of warehouse space belong to this system as well.
The set-up for the customer of omni-channel access to the ordering and tracking
process is a major integration problem. Alongside its channels of distribution to the
trade, a manufacturer of technical consumer goods sets up a direct sales channel via
an e-Shop. This now requires stock control to be accurate to the second as opposed
to the day, as has thus far been necessary. Distribution is now subdivided into
smaller sections and must be handled by a new service provider.
Whilst the first example serves more the improvement of internal logistics processes,
the second example opens up new business models.
Industry 4.0: From vision to Implementation
Overall the investment required is mid-level and the strategy opens up moderate
development perspectives due to its selective approach.
III. Smart Services
As already emphasised, I4.0 opens industrial companies to far reaching strategic
potential through new types of services. Through terms such as “shared economy”
this potential has been strikingly expressed and shows system relevant standards.
Ownership of products and resources is no longer in the forefront of client demands,
it is rather now access to services associated with them. This means that industrial
companies are taking on the character of service providers for the functions
associated with their products. Automobile companies are becoming mobility
services providers, compressor manufacturers offer air energy and so on.
Such a development is not new. In the 19th century, practically all producers of goods
supplied their own water and energy requirements through their own wells or sources
of energy such as wind, water or steam. These were their property and had to be
built and maintained by themselves. Today, water and energy is supplied by
independent companies and paid for as used: they are more or less drawn on as
Industrial companies can however create additional services associated with their
specialist competencies or supplement their product range. The significance of this
development is also recognised in I4.0 research. The Federal Ministry of Research
(BMFT) and the Federal Ministry for Economic Affairs and Energy (BMWi) have both
agreed to joint research projects on smart services to supplement current I4.0
Strategy 6: I4.0 Consulting
As pioneers for I4.0, industrial companies that have gathered experience with new
technologies and forms of organisation can pass this on to other companies. To this
end, they can set up their own consulting companies. This can happen by hiving off
the IT department which can now offer its services to the market, thanks to the
enrichment of its specialist competencies. The cost centre that is IT becomes a profit
centre. A further benefit exists in that the company can now address new customer
Industry 4.0: From vision to Implementation
needs thus increasing its rate of innovation, benefiting its parent company. This
development is already clear to see. At a smaller scale, such businesses can
become, for example, specialists for RFID technologies or material flow controls. At a
large scale, major service providers for the design of comprehensive I4.0 solutions
can be created if industrial world-wide market leaders in the German automobile
industry or machine manufacturing industry include their hundreds, or possibly
thousands of IT and manufacturing specialists. I4.0 as a service provision itself could
hereby become a German export success. Even though start-up costs are incurred,
the hiving-off of a department is more of an organisational problem than an
investment problem. In Figure 2 however, the high potential of reaching
comprehensive I4.0 concepts has been allocated to the strategy of limited investment
Strategy 7: Product related services
The connection to the internet of complex products such as tooling machines or
printing machines leads to significant gains in information about the worldwide
performance of these products under diverse operating conditions. Companies often
have many thousands, or even ten thousand, of their products in active operation.
This knowledge can be used by industrial companies to offer their customers
maintenance contracts at especially competitive rates.
There are, however, still significant obstacles to overcome. If the manufacturer
receives machine data from its customer it must adapt to the formats that its
customers use, and reformat it correspondingly when using the data with its own
systems. (Vice versa, an industrial company that receives data from a supplier for its
own manufacturing processes must reformat it in its own data organisation.)
It is obvious that, with the multiple types of data and differing customers and
suppliers, a set of data standards are essential. The first attempts at this have been
made by UMCM (Universal Machine Connectivity for MES) from the MES umbrella
association and the architecture from the OPCUA-Foundation. Nevertheless, further
work at an international level is necessary, for example from the IIC. In all probability,
industry standards driven by international market leaders in information technology
will prevail in the end
Industry 4.0: From vision to Implementation
Problems of data security are also solvable. If machines offer open interfaces to their
controls then, in principle, these are usable in both directions. In order to prevent
miss-use and sabotage (remember the stuxnet cyber-attack in an Iranian nuclear
power station or the hacking of the security mechanisms for the remote control of
vehicles from a renowned German automobile manufacturer) complex security
measures must be undertaken.
For the data administration concept and the services built upon these, a complex
worldwide infrastructure consisting of one’s own, and customer organisations, as well
as the corresponding IT, must be built up.
In Figure 2 a mid-level investment requirement has therefore been estimated. As a
wide variety of information about the performance of machines is created, for
example about the degree of use or about improvement possibilities of the products,
this strategy has been assigned with good development potential.
Strategy 8: BOO
BOO describes the transition of an industrial company to a complete service
provider. It no longer sells its customers the product, but merely the product
functionality as a service. A pioneer for this was the company Hilti in Liechtenstein
that, early on, rented out its tool products rather than selling them. The leasing offer
from machine manufacturers, through working together with banks, showed an early
change to the status of service providers. The sale of functionality and the raising of
invoices dependent on use is then the logical evolution.
The example of an agricultural equipment manufacturer that becomes a provider of
harvest services illustrates this clearly. Its core competence lies in the information
technology connection of agricultural machines with each other and with the logistics,
and also, for example, with the means of transport used for the fruit harvested. In the
area of smart farming, automation is further advanced than in classic industries.
The reason for this is, for example, that no administrative obstacles exist, such as
traffic controls in fields, and it is therefore easier to make use of driverless satellite
controlled systems.
Industry 4.0: From vision to Implementation
For a manufacturer of agricultural machinery that makes use of all technical and
organisational possibilities the result is a profitable business model. It can decide
independently when and how it deploys its combine harvesters on a customer’s
fields. Alongside the optimisation of this service, on the basis of its knowledge of its
machines and their operating conditions, it could even rent land and market the
agricultural produce itself. Information on climate conditions and prospects for the
harvest based on quantity and quality available to it via the internet connections of its
machines allow it to determine a prognosis for price developments. With this in
mind there are no limits to the creativity employable to find new business models.
New possibilities are also appearing in the field of medical technology. New
evaluation possibilities for the recognition of patterns in illnesses, not available to
individual doctors, are emerging from the (anonymous) results of research studies by
manufacturers of medical equipment. A paradigm change in analysis techniques in
relation to big data is currently that analysis free of hypothesis can be conducted.
This is leading to the ability of non-specialist analysts such as information scientists
to recognise surprising medical correlations.
In Figure 2 a larger investment requirement has been allocated to BOO strategies
because of the consistent change in business models and the transition from sales
profits to service dependent rental income. But this also opens up greater
development perspectives.
D. Roadmap to I4.0
The individual pursuit of only one of the strategies developed will not automatically
lead to a master concept for I4.0. Rather more, the steps should be integrated into a
master concept yet to be developed.
It is recommended that an in-house working group, complemented by external help,
develops a far reaching vision for a 5 year period in which the question is asked
which products the company will offer, how the profits are to be made, which
customer groups are to be serviced, which resources will be required: in short, how
the business model will look.
Industry 4.0: From vision to Implementation
Individual projects can be arranged in this business model in the form of a roadmap.
In order to acquire expertise not yet available (for example about the business of
providing services) decisions about the acquisition of companies also belong to this
roadmap. A manufacturer of electronic switch boxes, that has thus far viewed itself
as a manufacturer of goods, wishes to position itself in the future as a provider of
building security or building control and therefore buys a service provider as a form of
“germ cell” for this change. Or, a company that has thus far regarded its strength as
being in the high competency of its development and manufacturing engineers
recognises that, in the future, more software engineers will be required and therefore
buys a software business.
An important organisational question is also, whether the targeting of new fields of
business should be executed by the existing company or whether a new company,
acting more like a start-up business, should be founded.
The founding of a new company allows new approaches to be pursued regardless of
the company’s past: in other words avoiding the inertia effects of the innovator’s
dilemma phenomenon.
Discussions about the degree of maturity of the business can be stimulants for the
creation of priorities in implementation steps. If the company already operates far in
advance of its competition in one field, then it may not be worth making significant
investments in this field if the company is lagging behind its competition in other
areas of the business. It would, perhaps, be better served reducing its competitive
E. New demands on IT Systems
Although the focus of this paper has been on questions of business management, we
should not ignore the fact that I4.0 will be making great demands on the further
development of IT systems. Their support will, in the end, be a decisive factor for
Industry 4.0: From vision to Implementation
success or failure. New software architecture is a particular requirement. The phrase
“software eats the world” underlines the significance of this.
From a user point of view, it has already been noted that future software architecture
for industrial companies should be more product centred. This means that the
product definition should take centre stage and that the logistical functions should
access the product database. Currently however, ERP systems administer parts lists
and work plans. A product oriented architecture would trigger fundamental changes
and weighting between technical and business administrative functions. The
technical software architecture will also change. The software must be responsive at
all times and allow intervention in ongoing processes, in other words it must be
driven by events. Hierarchical architectures and the separation of logistics, product
development, manufacturing and accounts will be overturned. All processes will
become intertwined. The traditional pyramid models from the technical field level to
the top of the organisation lose their significance: the organisation of industrial
companies will become flat!
The Y model used serves only a logical form of ranking. In reality, the sides of the Y
model merge as the processes weave together across all areas, can be changed at
any time and must offer discretionary intervention points.
These requirements lead to a global requirement for responsibility of the software. All
applications must be omni-channel capable, the status of all ongoing processes must
be permanently transparent and accessible for changes necessary. The technical
consequences for software are far reaching. The Business Process as a Service
(BPaaS) software architecture developed by the Scheer Group GmbH follows these
principles. The broad architecture is illustrated in Figure 3.
Industry 4.0: From vision to Implementation
Figure 3: Scheer BPaaS Platform Architecture
The high flexibility is achieved by a platform orientation where in each case software
services are available. This represents a conscious departure from the architectural
principles of large monolithic ERP systems. On the contrary, smaller software units
are built, such as apps that can be flexibly and individually changed and connected
by users.
The integration platform makes possible the easy connection of differing systems
using a model based system. The process platform provides functional building
blocks as services. In the application platform processes are bundled into complete
This platform thinking makes possible the ad-hoc adaptation of an application or a
process to the individual requirements of the user (tailoring). Via the platform,
processes can be connected with people and things.
Industry 4.0: From vision to Implementation
F. Complementary concepts to I4.0
Although I4.0 is driven by new production and information technologies, people
centred organisational concepts continue to be important. Even with highly
automated production techniques, lean management, team building and the
emotional engagement of employees in particular remain important success factors.
Education and the willingness of employees to engage in lifelong learning are major
success factors. The aim of I4.0 is not a factory devoid of people, rather more it is the
synthesis of the use of information technology and classical people centred forms of
Industry 4.0: From vision to Implementation
Reference list
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in the automobile industry, Erlangen 2014.
Rifkin, J., The zero marginal costs society, Frankfurt u.a. 2014.
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Industry 4.0: From vision to Implementation
Whitepaper Nr. 1: 16 Tipps für Start-ups in der High-Tech-Industrie, Prof. Dr. A.-W.
Scheer, Juni 2013
Whitepaper Nr. 2: Tipps für den CIO: Vom Tekki zum Treiber neuer Businessmo-
delle, Prof. Dr. A.-W. Scheer, September 2013
Whitepaper Nr. 3: Die Universität und ihre Region, Prof. Dr. A.-W. Scheer, Juli 2014
Whitepaper Nr. 4: Tipps für Entscheider: Meine 10 wichtigsten strategischen
Entscheidungsregeln, Prof. Dr. A.-W. Scheer, August 2014
Whitepaper Nr. 5: Industrie 4.0: Von der Vision zur Implementierung, Prof. Dr.
A.-W. Scheer, Mai 2015
Whitepaper Nr. 6: Folge als Forscher dem weißen Kaninchen in das IT-
Unternehmerwunderland, Prof. Dr. A.-W. Scheer, Juni 2015
Whitepaper Nr. 7: Thesen zur Digitalisierung, Prof. Dr. A.-W. Scheer, Juli 2015
Whitepaper Nr. 8: Hochschule 4.0, Prof. Dr. A.-W. Scheer, August 2015
Whitepaper Nr. 9: Industry 4.0: From vision to implementation, Prof. Dr. A.-W.
Scheer, August 2015
Industry 4.0: From vision to Implementation
... Industry [22], [23], [24],. [25] 10 Information and media [26], [27], [28]. ...
... Insurances [29], [30], 22 , 23 , 24 . ...
... The Industry is facing the transition to a new phase, the Industry 4.0, characterised by the intelligent networking of machines and processes for industry with the help of information and communication technology [22]. This initial definition of Industry 4.0 has been further extended to include the concepts of smartness [23] and sustainability [24]. ...
D3.2. v0.8 (7th September 2022, h15.30)
... Industry [97], [98], [99], [100], [101] . ...
... The Industry sector is nowadays facing its transition to a completely new phase, the Industry 4.0, characterised by the intelligent networking of machines and processes for industry with the help of information and communication technology (Scheer,[97]). This initial definition of Industry 4.0 has been further extended to include the concepts of smartness (Zuo,[98]) and sustainability (Leng et al. [99]). ...
D3.2 Ontochain State of the Art - Blockchain Application and Technologies
... Industry [94], [95], [96], [97], [98] . ...
... The Industry is facing the transition to a new phase, the Industry 4.0, characterised by the intelligent networking of machines and processes for industry with the help of information and communication technology [94]. This initial definition of Industry 4.0 has been further extended to include the concepts of smartness [95] and sustainability [96]. ...
... Klingenberg (2017) posed that the 4IR results from technical advances, economic scenarios, and demographic changes. It should be noted that technological advances do not necessarily mean new technologies (Scheer, 2015). Oguro (2016) claimed that AI, the Internet of things (IoT), and big data are core elements of the 4IR. ...
... Industrial revolution 4.0 brings many common benefits such as: Faster production with less manpower; data are collected more sophistically; decisions are made more quickly; the ability to control the supply chain from raw materials to end consumers while ensuring equal quality among batches of products (Scheer, 2015). In addition, machine learning works more precisely when more detailed data are available to make better decisions. ...
Vietnam has been in the process of modernization and industrialization for the last 40 years. Vietnam's socio-economic development strategies are in line with this vision. However, the country needs a sharper strategy to take advantage of the significant technological development and the IT boom, also known as the 4th industrial revolution or the industrial revolution 4.0. This research aims at identifying key factors that Vietnam should focus on for a comprehensive national strategy to develop within the industrial revolution 4.0. The research results help policymakers, researchers and managers establish a strategic vision for the economic development in Vietnam. A survey is conducted among 145 respondents who are either working for the Government, academic institutions, or managing enterprises. Findings of the research involve levels of awareness about industrial revolution 4.0 and the readiness for industrial revolution 4.0 in Vietnam. Moreover, three factors are also identified to be the key elements of a strategy for social-economic development in Vietnam, including human resources, policies, and infrastructure.
... Industry [39], [40], [41], [42], [43] . ...
... The Industry is facing the transition to a new phase, the Industry 4.0, characterised by the intelligent networking of machines and processes for industry with the help of information and communication technology [39]. This initial definition of Industry 4.0 has been further extended to include the concepts of smartness [40] and sustainability [41]. ...
... In general, they are more limited in the sense of autonomous capabilities and usually fed with very detailed information on their surrounding environment. The integration of robots and other intelligent devices into industrial scenarios is researched in the Industry 4.0 proposal [18] [19], which aims to revolutionize industrial solutions by enhancing them with cloud-based intelligent solutions to optimize manufacturing. ...
Conference Paper
Robotic applications have prominently emerged in automating a wide range of high-precision tasks in industry, logistics, health and military applications. More recently, applications focused on socio-cultural contexts, such as caretaking and personal assistance, have begun to gain traction. In parallel, earlier focus on mechanical and mathematical/control solutions has visibly shifted toward aspects of intelligent and collaborative functions. These changes have brought various aspects of the fields of cognitive infocommunications (CogInfoCom) and Internet of Digital Reality (IoD) to the forefront, both in terms of design methodologies and application areas. While CogInfoCom places emphasis on new kinds of cognitive capabilities / entities that are neither purely human, nor purely artificial, IoD highlights the integration of such capabilities and entities in networked settings created to support specific semantic contexts. Importantly, the scope of such capabilities and/or entities is not limited only to intelligent agents and collaborating humans but also to less capable agents (e.g., cyber-physical and industrial control devices). In a socio-cultural context, the interaction between a robot and other agents (particularly a human) can be viewed as the communication of cognitive entities through some form of Cognitive Infocommunication channels. This paper proposes a new way to view the communication between intelligent robots and cognitive entities.
... According to Klingenberg and Antunes (2017) the 4IR is made from technical advances, economic scenarios, and demographic changes. Scheer (2015) believes that technological advances do not mean new technologies. In fact, some of them were already present 30 years ago but only became feasible recently with the development of information and communication technology (ICT) (Brettel et al., 2014). ...
The purpose of this study was to determine new leadership styles in the context of the level of development of the Vietnamese economy in the last years and what is likely to happen in the next 10 years or more. Another aim was to create the combination of leadership best thinking that will enable Vietnamese leaders to adapt successfully in the implementation of the fourth industrial revolution (4IR) in Vietnam. The 4IR is fundamentally different because it involves the fusion of a range of new technologies that link the physical, digital and biological worlds, impacting all disciplines, economies, and industries. Transformational analysis in combination with documents review, in-depth interviews with Delphi technique in VUCA (Volatile, Uncertain, Complex and Ambiguous) environment with 64 top government leaders, researchers, and scholars. including hi-tech enterprises conducted to see the major characteristics and skills that a leader needs in the digitalization ages in the digitalization age. The study results were that there are five models of leadership in 4IR best practices: traditional leadership, transformational leadership, agile leadership, block-chain leadership, and human values and ethics. The principal conclusion was that the more resilience Vietnam is ready, the more successful Vietnam will achieve beyond the 4IR.
... Two trends that are driving the development of smart manufacturing are 1) more flexible production, to meet the need of increased customization, and 2) more autonomous operations and monitoring to increase productivity and improve quality [1]. The digital transformation of industry fueled by Industry 4.0 and the development of 5G cellular technology, is in many ways a response to these trends. ...
5G has been defined to address new use cases beyond consumer-focused mobile broadband services. In particular industrial use cases, for example in smart manufacturing, have been addressed in the 5G standardization, so that 5G can support industrial IoT services and wireless industrial networking. To this end, 5G needs to integrate with the industrial network based on Ethernet and TSN. 5G can create new opportunities for smart manufacturing by enabling flexibility and increasing the automation in the production. This paper provides an overview of the use cases and requirements for smart manufacturing that can be addressed with 5G and which are validated in three industrial 5G trial systems. The capabilities of 5G are described for providing non-public networks that support industrial LAN services based on Ethernet and TSN. The 5G radio access network functionality is described and discussed for practical deployments. The paper provides an overview of the current state-of-the-art of using 5G for smart manufacturing.
Despite a long-term decline in the circus industry, Cirque du Soleil profitably increased revenue 22-fold over the last ten years by reinventing the circus. Rather than competing within the confines of the existing industry or trying to steal customers from rivals, Cirque developed uncontested market space that made the competition irrelevant. Cirque created what the authors call a blue ocean, a previously unknown market space. In blue oceans, demand is created rather than fought over. There is ample opportunity for growth that is both profitable and rapid. In red oceans--that is, in all the industries already existing--companies compete by grabbing for a greater share of limited demand. As the market space gets more crowded, prospects for profits and growth decline. Products turn into commodities, and increasing competition turns the water bloody. There are two ways to create blue oceans. One is to launch completely new industries, as eBay did with online auctions. But it's much more common for a blue ocean to be created from within a red ocean when a company expands the boundaries of an existing industry. In studying more than 150 blue ocean creations in over 30 industries, the authors observed that the traditional units of strategic analysis--company and industry--are of limited use in explaining how and why blue oceans are created. The most appropriate unit of analysis is the strategic move, the set of managerial actions and decisions involved in making a major market-creating business offering. Creating blue oceans builds brands. So powerful is blue ocean strategy, in fact, that a blue ocean strategic move can create brand equity that lasts for decades.
The zero marginal costs society
  • J Rifkin
Rifkin, J., The zero marginal costs society, Frankfurt u.a. 2014.
CIM – The computer controlled industrial company
  • A.-W Scheer
Scheer, A.-W., CIM – The computer controlled industrial company, 4th edition, Berlin u.a.1990.
1: 16 Tipps für Start-ups in der High-Tech-Industrie
  • Whitepaper Nr
Whitepaper Nr. 1: 16 Tipps für Start-ups in der High-Tech-Industrie, Prof. Dr. A.-W. Scheer, Juni 2013
2: Tipps für den CIO: Vom Tekki zum Treiber neuer Businessmodelle
  • Whitepaper Nr
Whitepaper Nr. 2: Tipps für den CIO: Vom Tekki zum Treiber neuer Businessmodelle, Prof. Dr. A.-W. Scheer, September 2013
3: Die Universität und ihre Region
  • Whitepaper Nr
Whitepaper Nr. 3: Die Universität und ihre Region, Prof. Dr. A.-W. Scheer, Juli 2014
5: Industrie 4.0: Von der Vision zur Implementierung
  • Whitepaper Nr
Whitepaper Nr. 5: Industrie 4.0: Von der Vision zur Implementierung, Prof. Dr. A.-W. Scheer, Mai 2015
6: Folge als Forscher dem weißen Kaninchen in das IT- Unternehmerwunderland
  • Whitepaper Nr
Whitepaper Nr. 6: Folge als Forscher dem weißen Kaninchen in das IT- Unternehmerwunderland, Prof. Dr. A.-W. Scheer, Juni 2015
9: Industry 4.0: From vision to implementation, Prof
  • Whitepaper Nr
Whitepaper Nr. 9: Industry 4.0: From vision to implementation, Prof. Dr. A.-W. Scheer, August 2015
Hrsg.), Transparency in global supply chains in the automobile industry
  • R Lepratti
  • S Lamparter
  • R Schröder
Lepratti, R./Lamparter, S./Schröder, R. (Hrsg.), Transparency in global supply chains in the automobile industry, Erlangen 2014.