Available online at www.sciencedirect.com
ScienceDirect
Procedia CIRP 57 (2016) 14 – 19
49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016)
Study Based Analysis on the Current Digitalization Degree in the
Manufacturing Industry in Germany
Eva Bognera*, Thomas Voelkleinb, Olaf Schroedelb, Joerg Frankea
a
Institute for Factory Automation and Production Systems, Friedrich-Alexander University Erlangen-Nuremberg, Egerlandstraße 7-9, 91058 Erlangen
b
Sintec Informatik GmbH, Ludwig-Quellen-Straße 18, 90762 Fürth
* Corresponding author. Tel.: +49-9131-85-28994; fax: +49-9131-302528. E-mail address: eva.bogner@faps.fau.de
Abstract
The fourth industrial revolution and the digital transformation are already major factors in the manufacturing industry and their importance is
ever growing. However, the degree of their practical implementation has to be scrutinized. To define a status quo, it is important to analyze the
situation and to identify deficits, starting points and unexploited potentials.
Still, a detailed understanding of the fourth industrial revolution and the digital transformation is lacking especially in small and medium sized
manufacturing companies. In addition, the fourth industrial revolution is associated by most companies only with logistics as well as production
and manufacturing areas. The opportunities to integrate additional functional areas of the production process and the vertical value chain into
the concept of the fourth industrial revolution are hardly considered. Starting from the point of view that the fourth industrial revolution is
defined as a systematic increase in the flexibility of products and processes through automation, extensive networking and decentralized control
mechanisms, as well as a data acquisition and integration through information and communication technologies, a study concept is developed.
For this purpose, it is not enough to ask only for the present prevalence of technologies of the fourth industrial revolution. It is necessary to
analyze the processes within manufacturing companies.
A survey concept is developed that initially breaks down the vertical value chain as well as the production process into specific sub-processes.
These sub-processes are analyzed regarding their degree of automation and digitalization and networking among themselves. The results of this
survey presents concisely the call for action, the state of implementation and realized solutions of the fourth industrial revolution in Germany.
Furthermore, impulses and best practices for innovative products and business models can be given.
©
Published
by Elsevier
B.V. This
©2016
2015The
TheAuthors.
Authors.
Published
by Elsevier
B.V.is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of Scientific committee of the 49th CIRP Conference on Manufacturing Systems (CIRP-CMS 2016).
Peer-review under responsibility of the scientific committee of the 49th CIRP Conference on Manufacturing Systems
Keywords: Digital transformation; Digitalization degree; Fourth industrial revolution; Study
1. Introduction
Prevailing factors in the manufacturing industry are the
digital transformation and the fourth industrial revolution. As
their importance is ever growing, their actual degree of
implementation has to be captured. The definition of a status
quo requires an analysis of the situation and an identification
of deficits, starting points and unexploited potentials.
However, there is a lack of a detailed understanding of the
fourth industrial revolution and the digital transformation
especially in small and medium sized manufacturing
companies. The fourth industrial revolution may be defined as
a systematic increase in the flexibility of products and
processes through automation, extensive networking and
decentralized control mechanisms, as well as a data
acquisition and integration through information and
communication technologies. Based on this definition a study
concept is developed. The aim of this study is to provide
insight to decision-makers of manufacturing companies about
their current status with respect to the fourth industrial
revolution and to derive recommendations for the integration
of the value chain. Concurrently, a basis for decision-making
should be given that explains how they can achieve an
optimal cost-benefit ratio of their activities with respect to the
fourth industrial revolution and the digital transformation.
2212-8271 © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the scientific committee of the 49th CIRP Conference on Manufacturing Systems
doi:10.1016/j.procir.2016.11.004
15
Eva Bogner et al. / Procedia CIRP 57 (2016) 14 – 19
2. Study concept
In the course of the study, a concept is developed that
enables an objective determination of the degree of
digitalization of different companies.
2.1. Subject of research
The fourth industrial revolution is known as the
introduction of the Internet of Things into the field of
production [2]. New digital technologies like cloud
computing, big data, cyber-physical systems and additive
manufacturing accompany this informatization. The objective
of the revolution is the production of individual products with
the speed and costs of a comparable mass production.
Consequently, there is a need for an increase both in
efficiency as well as flexibility. But the implementation of
information and communication technologies as well as the
increasing networking within the production process alone
will not bring about this industrial revolution. The fourth
industrial revolution therefore is not limited to the production
process. There must be a far-reaching change within
manufacturing companies that goes beyond the production
process. The technologies of the digital transformation enable
completely new processes along the entire value chain, from
research and development through manufacturing and sales to
services concerning the use of a product [3]. At present, value
chains from customer requirements through the product
development to manufacturing are often grown historically
and thus are inflexible. Digital potentials can be found at
every stage along the value chain in different ways and
degrees.
In all, with an appropriate implementation the
digitalization and the related information and communication
technologies are able to make a decisive contribution to value
creation. Thus, digitalization should not be considered
isolated for individual areas and only as a supporting element
of the corporate strategy. Rather, a holistic approach that
covers all areas and functions of a company to exploit digital
potentials and analyze each stage of its value chain separately
has to be developed. This approach should be integrated into
strategic planning and implementation. [4]
For this reason, the study examines not only the degree of
digitalization of the production process of different
companies. Also all other relevant value activities and
business processes are taken into consideration.
Value activities can be divided into two general types,
namely primary and supporting activities (see Fig. 1). Primary
activities deal with the physical production of the product and
its sale and delivery to the customer as well as the customer
service. Supporting activities maintain the primary activities
through the purchasing of inputs, the provision of
technologies, the processing of queries and orders and cover
various functions for the entire company. [1]
Especially in the field of supporting activities, that are still
strongly characterized by manual activities in contrast to the
largely automated production processes, large efficiency
potentials can be realized by their digitalization [5]. However,
the concept of digitalization is often only associated with the
"paperless office" in this field. Digitalization is significantly
more than just the transfer from analog to digital data and
documents [4]. Rather it is about the stronger networking
between the business processes, the creation of efficient
interfaces and the integrated data exchange and management.
Table 1. Fields of examination
Primary activities
Supporting activities
Goods receiving
Query processing
Incoming warehouse
Order processing
Manufacturing/assembly
Product development
Finished-products warehouse
Production planning
Marketing/promotion
Purchasing
Sales
Billing
Logistics/delivery
Aftersales service
Fig. 1. Value chain according to Porter
16
Eva Bogner et al. / Procedia CIRP 57 (2016) 14 – 19
The study is intended to examine the fields of the
supporting as well as the primary activities. The selection of
the fields of examination, however, is limited to those fields
along Porter’s value chain with the highest expected needs for
digitalization and digital potentials. This selection is listed in
Table 1 in detail.
2.2. Research methodology
In the further consideration the digitalization is seen as the
integration and optimization of information and the flow of
goods along the supply chain. The main basis for this is a
consistently digitalized data flow without media
discontinuities along the entire value chain of a company. To
ensure this, all relevant fields of the value chain in a company
need to be digitalized. The working hypothesis therefore is:
The more consistently a company digitalizes its value chain,
the less media disruptions are within the data flows. Thus, the
degree of digitalization of the entire value chain of a company
is the appropriate measure unit for its readiness for the digital
transformation and the fourth industrial revolution.
When operationalizing the measurement of the degree of
digitalization, two issues have to be considered:
x How can the status of a company based on its degree of
digitalization be objectively measured and how can it be
objectively compared with other companies?
x How can a differentiation between aspects of the third and
the fourth industrial revolution be achieved?
During the last three industrial revolutions, activities and
tasks which require only little or no specific qualification
were automated through production facilities and robots. In
course of the digital transformation, information and
communication technologies and computer algorithms start to
exploit new areas of the automation at high speed. This
development can equally be said of an automation that it is
achieved through the use of information technology because
these technologies are able to automate processes where
knowledge is systematically collected and processed as well
as to analyze and to evaluate information. There is also a
substitution of human labor as it can be found in the classical
automation. However, a degree of automation can be
achieved, that goes beyond the conventional automation.
Through IT-based automation solutions, self-regulating
processes can be realized especially in the field of the
production process. [6]
It is assumed that at the present many companies have
difficulties to evaluate the individual level of digitalization of
their processes and need support because of a missing
methodology and missing standards. For this reason, the
degree of automation should be used as a criterion instead of
the digitalization degree. As explained above, especially in
the area of supporting activities the automation degree allows
to draw conclusions about the digitalization degree.
Based on these considerations, two indices are created. The
first index describes the level of digitalization across the
entire value chain of a company. The second index determines
the degree of automation of the production process isolated
from the entire value chain. For this purpose, the production
process is broken down into 21 generalized and transferable
sub-processes which are analyzed in detail.
The index formation for the two indices “Level of
automation in production" and "Degree of automation along
the value chain” is based on scoring models that contain the
relevant question blocks that ask for the degree of
digitalization in the defined fields of examination.
The first set of questions queries the degree of automation
of processes within the field of production. There are four
answer options for each sub-process:
x
x
x
x
1 = mainly made by hand
2 = partially automated
3 = highly automated
4 = self-regulating
In the fourth stage "self-regulating", it can be assumed that
technologies of the fourth industrial revolution technologies
have already been implemented successfully. The other levels
are assigned to the technological level of the third industrial
revolution at the most.
The degree of automation of a company along the entire
value chain is determined within the specified fields of
examination (see Table 1). The answer options for these
processes are:
x 1 = mainly manually
x 2 = partially automated
x 3 = highly automated
Based on the entire value chain "highly automated" is the
highest possible degree of automation. Mainly concerning the
field of supporting activities, this already implies a very high
degree of automation and digitalization. Self-regulating
processes are only to strive for in the production processes.
Respondents could indicate that are not able to give any
information about a process. Companies, which do not
provide a certain process of the value chain, could also remark
this. Furthermore, answering these two sets of questions is can
be done from an objective point of view and independent of
the state of knowledge and the current mind set to the fourth
industrial revolution. The only prerequisite for answering the
questions is the knowledge of the process landscape of the
company. This is ensured through a filter at the beginning of
the survey.
2.3. Effect examination
In addition, the study analyses the effect of activities in the
context of the digital transformation and the fourth industrial
revolution. In order to develop a valid impact model, success
factors in the form of measures and the associated target
figures, which describe the resulting effects, have to be
defined.
Therefore, 23 methods and tools along the value chain
have been selected, which are regarded as the substantial
measures within the framework of the fourth industrial
Eva Bogner et al. / Procedia CIRP 57 (2016) 14 – 19
revolution, for example predictive maintenance and the
analysis of machine data in real-time. These represent the
success factors that have to be evaluated. The
operationalization of their actual implementation is realized
by a three-point scale:
x 1 = not planned yet
x 2 = planned
x 3 = already realized
Simultaneously, these measures are assessed for their
impact and their implementation success. This is done based
on 14 target figures. A principal component analysis results in
three impact dimensions into which they can be classified.
These three overarching impact dimensions can be described
as "productivity", "availability" and "customer satisfaction"
(see Table 2. Target figures). To keep the evaluation of all
criteria operable, a three-point scale with the following
choices is used:
x 1 = not yet realized
x 2 = slightly positive change
x 3 = very positive change
Table 2. Target figures
Impact dimension
Target figure
Productivity
Increase in productivity
Shorter set-up times
Shorter delivery times
Reduction of error rate
Reduction of production costs
Increase in quality
Availability
Reduction of on-site service visits
Reduction of trouble-tickets
Reduction of machine downtime
Reduction of breakdowns
Customer satisfaction
Increase in customer satisfaction
Reduction of complaint rate
Reduction of hotline calls
Increase in delivery reliability
3. Execution of the study
For the purpose of the study, 211 manufacturing
companies headquartered in Germany were interviewed.
These companies come from different sectors: mechanical
engineering, electrical engineering, medical engineering,
logistics, information and communication technology. Only
medium and large size companies are interviewed, small
medium-sized companies are not considered. The
operationalization is based on the Institute for Small Business
Research in Bonn and thus slightly different from the
definition of the European Union [7]. Companies with 150 up
to 499 employees and a sales up to € 50 million are defined as
medium-sized enterprises. Companies with 500 or more
employees or a sales over of 50 million € are described as
large enterprises. The selection of the companies is carried out
randomly from a representative address list of 10,000 German
companies. Thereby, large companies are quoted by a factor
of 2.5 compared to medium-sized companies.
Within the companies, directors or managers are
interviewed. To meet the topics "degree of digitalization of
business processes", functionaries, who declare, that they
“hardly know” the detailed business processes are excluded
from the survey.
The study was carried out both by means of interviews and
an online questionnaire. The content of the questionnaire was
identical for both methods.
4. Results
The study results show that the basic preconditions for the
fourth industrial revolution and the digital transformation
have not been given yet. One the one hand, this is due to the
high degree of manual processes along the entire value chain.
The field of production has the highest degree of automation
within the value chain. About 90 percent of the examined
companies have production processes that are partly or even
highly automated. The areas of marketing, after sales and
product development show the lowest degree of automation.
On the other hand, the examination of the degree of
automation along the production process shows that less than
20 percent of the companies provide the conditions for an
integrated engineering and the fourth industrial revolution.
However, only the companies which fulfill these prerequisites
are fulfilled, provide consistently automated and selfregulating processes. All other companies still have a very
high percentage of manual processes and thus a barrier-free
data continuity along the production process is not possible.
The results of both analyses are shown in a scatterplot
diagram. Each point in this diagram represents a company
examined in the study (see Fig.2). Each company is described
by the maturity level of digitalization (x-value) of its entire
value chain and the degree of automation of its production (yvalue). It can be seen that there is an approximately uniform
distribution of companies around the zero point. On the one
hand, there are companies that have a relatively high degree
of automation in production. However, they just put little
focus on the automation of the entire value chain. These often
are companies which persist in the era of the third industrial
revolution. On the other hand, there are companies where it is
the other way round. There are also a number of companies
within the manufacturing industry, whose maturity level is
below average both in the automation of the production as
well as the entire value chain. The companies in the upper
right quadrant of the scatterplot diagram have already taken a
major step forward in the comprehensive automation. They
show a high level of maturity in both fields.
17
18
Eva Bogner et al. / Procedia CIRP 57 (2016) 14 – 19
Fig. 2. Results of the study
The next step is to answer the question to what extent the
fourth industrial revolution and the digital transformation
contribute to the success of a company. In order to answer this
question the characteristic of the target figures, that describe
the effect of the digitalization, is analyzed. This measurement
is independent from the degree automation. Looking at the
average values of the companies in the 4 quadrants of the
scatterplot, shows a significant relation between the division
within the scatterplot diagram and the success factors of a
company. Based upon this, the following classification is
made:
x Cluster 1: Good practices
(Companies in the upper right quadrant of the scatterplot)
In companies that have high degree of automation in both
dimensions, the implementation of the success factors of
the fourth industrial revolution is clearly above average.
These companies generate the largest contribution to the
corporate success through their measures.
x Cluster 2: Marketeers
(Companies in the lower right quadrant of the scatterplot)
These are companies that just pushed the automation of the
entire value chain and have rather neglected a further
automation of their production. Accordingly, the success
factors related to the integration of the different stages of
the value chain are at an above-average level. The
production process is still rather on the state of the third
industrial revolution, since the production-related success
factors are less taken into account. Interestingly, the
determined contribution to the corporate success is lower
in these companies.
x Cluster 3: Keeper
(Companies in the lower left quadrant of the scatterplot)
Companies in this cluster are very cautious about the
automation of their processes. They rather remain in their
existing structures and processes than implementing new
technologies. If any, these keepers achieve increases in
productivity that are below average and a slight increase in
customer satisfaction.
x Cluster 4: Technologists
(Companies in the upper left quadrant of the scatterplot)
Manufacturing companies of this cluster, focus on the
automation of production. They perfectly implemented the
technologies of the third industrial revolution. However,
they are just at an average level with respect to the
automation of the entire value chain and the
implementation of self-regulating production processes.
This is also reflected in the resulting average contribution
to corporate success.
This positive correlation between the high degree of
automation of both the production and the entire value chain
and the resulting contribution to the corporate success
becomes even more apparent by the aggregated values of the
indices in Table 2.
However, the question arises, if the size and type of the
production of a company have an impact on the results. The
analysis of separate scattering diagrams for large enterprises
and medium-sized businesses, as well as companies with a
mass production and companies that produce in batch size 1,
shows that all scatterplots have an approximate equal
distribution. Thus, the company size and the design of the
production system do not affect the division into the different
company types.
Eva Bogner et al. / Procedia CIRP 57 (2016) 14 – 19
Fig. 3. Comparison of the company types
5. Conclusion
Acknowledgements
It is obvious that the automation and digitalization of the
entire value chain as well as the simultaneous consideration of
the success factors of the fourth industrial revolution increase
the company's success significantly. The more both are
implemented in a company, the higher its performance. This
performance is also a good indicator of the capacity of a
company with respect to the fourth industrial revolution and
the future success of the company.
In addition, the study shows that the fourth industrial
revolution holds great potential benefits. It is necessary to
focus on changes in the production process. However, many
potentials can only be exploited if the processes along the
entire value chain are involved in these changes. Only the
automation and digitalization across the entire value chain of
a company leads to a greater contribution to corporate
success. Many companies have not yet recognized these
opportunities. From today’s point of view, only one quarter of
the surveyed companies of the manufacturing industry will be
able to cope with the disruptive changes of the fourth
industrial revolution.
We thank SINTEC Informatik GmbH for the funding,
execution and publication of the study. Without their support
the realization of this study would not have been possible.
References
[1] M. E. Porter, Wettbewerbsvorteile: Spitzenleistungen erreichen und
behaupten, 8th ed. Frankfurt am Main: Campus, 2014.
[2] A. Weisbecker, M. Burmester, and A. Schmidt, Eds, Mensch und
Computer 2015: Workshopband. Berlin: De Gruyter Oldenbourg, 2015.
[3] Bundesministerium für Wirtschaft und Energie, Industrie 4.0 und Digitale
Wirtschaft: Impulse für Wachstum, Beschäftigung und Innovation (de).
[4] J. Reker, “Digitalisierung im Mittelstand,” Deloitte & Touche GmbH
Wirtschaftsprüfungsgesellschaft, 2013
[5] E. Bogner, J. Götz, H. Fleischmann, and J. Franke, “Automatisierung von
Overheadprozessen: Erschließung von Effizienzpotentialen für Industrie
4.0,” (de), ZWF, vol. 110, no. 7-8, pp. 470–474, 2015.
[6] C. Patscha, H. Glockner, and K. Burmeister, “Gestaltungsräume im
Zeitalter der Komplexität: Positionspapier für die Arbeit der
Expertenkomission Arbeits- und Lebensperspektiven in Deutschland,”
Bertelsmann Stiftung, Güthersloh, 2013.
[7] Insitut für Mittelstandsforschung Bonn, KMU-Definition des IfM Bonn.
Available: http://www.ifm-bonn.org/definitionen/kmu-definition-des-ifmbonn/ (2016, Jan. 15).
19