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The technological transformation in the European steel industry is driven by digital-ization, which has the potential to strongly contribute to improving production efficien-cy and sustainability. The present paper describes part of the work developed in the early stage of the project entitled “Blueprint “New Skills Agenda Steel”: Industry-driven sustainable Eu-ropean Steel Skills Agenda and Strategy (ESSA)”, which is funded by the Erasmus Plus Programme of the European Union. The project aims at achieving an industry driven, sustainable and coordinated blueprint for addressing the economic, digital and technological developments, as well as increasing energy efficiency and environmen-tal demands through continuously update of qualification, knowledge and skill profiles of the workforce. On the one hand, main aspects of the current state of the technological transfor-mation in the steel sector are described through the analysis of the main recent inno-vation projects and developments. On the other hand, survey results from a dedicated questionnaire addressed to the European steel companies are analyzed, providing an overview on the (planned) technological transformation affecting the steel sector. The existing levels of plant automation and the possible adoption of the new paradigm of Industry 4.0 are discussed, by also considering the possible impact on the workforce. Main results are that the steel industry foresees an implementation of almost all Industry 4.0 technologies not only for competitive but also environmental improve-ment. Because this is foreseen in an incremental way upskilling of the existing work-force is a precondition, not only because of recruitment difficulties on the employ-ment market but also because the existing qualification and experience of the work-place is necessary to unfold the full potential of digital and green transformation.
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Materials and Society: transitions in society, materials and energy
edited by Jean-Pierre Birat, Gaël Fick, Mauro Chiappini, Dominique Millet, Thècle Alix
Current and future aspects of the digital transformation in the
European Steel Industry
Teresa Annunziata Branca
, Barbara Fornai
, Valentina Colla
, Maria Maddalena Murri
, Eliana Streppa
and Antonius Johannes Schröder
Scuola Superiore SantAnna, TeCIP Institute, ICT-COISP Center, Pisa, Italy
RINA CONSULTING Centro Sviluppo Materiali S.p.A. (CSM), Castel Romano (Roma), Italy
Technische Universität Dortmund, Dortmund, Germany
Received: 4 October 2020 / Accepted: 8 March 2021
Abstract. The technological transformation in the European steel industry is driven by digitalization, which
has the potential to strongly contribute to improving production efciency and sustainability. The present paper
describes part of the work developed in the early stage of the project entitled Blueprint New Skills Agenda
Steel: Industry-driven sustainable European Steel Skills Agenda and Strategy (ESSA), which is funded by the
Erasmus Plus Programme of the European Union. The project aims at achieving an industry driven, sustainable
and coordinated blueprint for addressing the economic, digital and technological developments, as well as
increasing energy efciency and environmental demands through continuously update of qualication,
knowledge and skill proles of the workforce. On the one hand, main aspects of the current state of the
technological transformation in the steel sector are described through the analysis of the main recent innovation
projects and developments. On the other hand, survey results from a dedicated questionnaire addressed to the
European steel companies are analyzed, providing an overview on the (planned) technological transformation
affecting the steel sector. The existing levels of plant automation and the possible adoption of the new paradigm
of Industry 4.0 are discussed, by also considering the possible impact on the workforce. Main results are that the
steel industry foresees an implementation of almost all Industry 4.0 technologies not only for competitive but
also environmental improvement. Because this is foreseen in an incremental way upskilling of the existing
workforce is a precondition, not only because of recruitment difculties on the employment market but also
because the existing qualication and experience of the workplace is necessary to unfold the full potential of
digital and green transformation.
1 Introduction
The current industrial transformation results from several
industrial revolutions over the last two hundred years.
From the late 1800s and early 1900s Industry 1.0, based on
the mechanization of work, led to the electrication of work
of Industry 2.0. After this period, in the early 1960s, the
automation of work characterized Industry 3.0. More
recently, in the rst decades of the new millennium the
digitalization of information, supporting the intelligent
automation and the ever-increasing computational resour-
ces, characterized Industry 4.0. The term Industry 4.0,
originated in Germany [1,2], indicates the fourth techno-
logical revolution and refers to the implementation of
advanced automation solutions in production technologies,
supported by a variety of digital technologies. Such concept
includes machine-to-machine communication, Articial
Intelligence (AI) [3] and Industrial Internet of Things
(IIoT) [4] for improving self-monitoring, diagnostic,
forecasting and self-optimization [5] capabilities of auto-
mation systems [6]. Industry 4.0 was considered a new
industrial stage, where different emerging technologies are
converging to provide digital solutions, leading to the
smart factory concept [7]. Concerning the steel sector, the
1st industrial revolution was characterized by the
introduction of coal-powered steel engines. It represents
the rst fundamental shift in the optimisation of industrial
processes, leading to productivity increase and to rst
interactions between workers and machine tools. The 2nd
Industrial Revolution was characterized by the invention
of the production area, the improvement of transportation
technologies and the electrication of industrial processes.
These aspects led to produce cheaper steel through the
Bessemer process and to introduce the open-hearth
furnace. The 3rd Industrial Revolution was based on the
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introduction of a progressive automation of manufactur-
ing, reducing manual work and increasing the industrial
production. In addition, the development of work in
assembly lines, focusing on optimisation and removal of
inefciencies, and based on the integration of computers to
control the whole production process, represented a key
aspect [8]. Finally, in Industry 4.0 breakthrough innova-
tions have been integrated in process automation, includ-
ing Cyber Physical Systems (CPS), Big Data analytics and
Decentralised Control Systems. In particular, CPS are
composed of physical subsystems equipped with computing
and networking resources/facilities to monitor and control
physical processes, where physical processes affect compu-
tations and vice-versa [9]. In addition, big data analytics
refer to processing of large, heterogeneous and unstruc-
tured process and product data for identifying quality
problems and reducing the product failures [10,11]. Finally,
self-organizing production is related to the decentral
solutions based on a new combination of resources,
equipment, and personnel, with a close mutual interaction
and supported by distributed computational resources,
leading to the real-time control of production networks [12].
However, it has to be stated, the industrial develop-
ment phases from Industry 1.0 to 3.0 could not be seen as a
linear and positive development process. According to
Schumpeters Creative Destruction [13] the industrial
revolutions are compared by societal injuries (job losses,
emissions, deaths of workers, etc.). If this will be the same
for the 4th industrial is not quite consensual: While some
scholars expect disruptive changes [14], others foresee
mainly incremental impact via innovative technologies
updating and supporting of existing procedures (esp.
because of the already existing high automation of
production processes) and new jobs appearing [13,15].
Concerning the workforce implications, equivalent scenar-
ios are under discussion: from substitution of work via
robots and related massive job losses over the polarization,
to higher and lower qualications and tasks (by decreasing
the middle operative level), as well as new cooperation
between different levels and working areas, and crowd
working on virtual or digital connected platforms [16,17].
In the transformation of manufacturing industry digitali-
zation is considered as a core technology. It is expected to
impact and transform industry, mainly through a substan-
tial improvement of the entire value chain. Nevertheless,
its effective implementation in the business activities
continues to be slow [18]. In the incoming years, the most
important drivers that professionals and decision makers
need to take into account are sustainability, digital
transformation, innovation and entrepreneurship [19].
In order to measure the achieved level of digitalization
in a country, the European Commission developed a
composite measure (the Digital Economy and Society
Index (DESI),) summarizing indicators related to the
digital performance and digital competitiveness of the
European Union (EU) member states [20]. According
to [21], the way to implement the Industry 4.0 paradigms
consists in integrating technologies, enabling ecosystems of
intelligent, autonomous and decentralised industries and
integrated product-services. The expected results concern
the reduction of the complexity of industry operations, as
well as the increase of their efciency and the reduction of
costs. In this scenario, for instance, a new cross-functional
business unit (DIGI&MET) was developed in order to
implement new plant design concepts, based on digital
innovation, and also new business models [22].
In the incoming years, the adoption of the new digital
technologies, particularly based on advanced automation
and AI, is expected to produce signicant transformation in
industrial activities, although this transformation is
already underway. Promotion of economic growth and
industrial competitiveness is expected. In addition, the
increase of digitalization in the industrial environment will
lead to recruitment of younger workforce, which is
generally more familiar with digital tools. However, some
negative aspects for economy and labor market can affect
companies, such as skill shortages and mismatches,
increased labor costs, production losses due to unlled
vacancies, and higher social costs due to higher unemploy-
ment rates [23]. In this context, the European steel industry
is driving innovation in digital and green technologies, and
plays a key role in progress, economic growth, and job
opportunities [24]. This sector is highly specialised in
production and implementation of cutting-edge technolo-
gies and high value added products and solutions [25]
through the investments in Research & Development &
Innovation (R&D&I) [26]. In addition, sustainability and
emissions reduction represent innovative challenges
and opportunities for companies to maintain their
competitiveness. On this subject, the EU should support
the steel sector in the elaboration of an industrial strategy
based on innovation, trade, sustainability and skills [27,28].
The concepts of digitization and sustainability are
becoming increasingly important and, therefore, they may
represent drivers for the evolution of the EU steel industry.
In spite of the large research activity on individual concepts
like digitalization, digital transformation, Industry 4.0
applications, etc.,the interdependency between Industry 4.0
and sustainability was shown. In particular, sustainability
is one of the main benets of Industry 4.0, together with
productivity optimization or automated knowledge. In
addition, in manufacturing processes, the concepts of
Industry 4.0 can enhance operations to improve the
environmental sustainability of the production processes
[29,30]. The aspects related to Circular Economy have a
key position in EU policy, as the use of resources and
products in a more efcient way can contribute to reduce
industrial emissions and to improve EU industrial growth.
A recent report [31], including different sectors, such as plastic,
cement, aluminum and steel, showed an ambitious circular-
economy scenario by 2050. In addition, digitalization can help
to derive, handle, analyse and understand data and complex
information ows [32]. Furthermore, it can both catalyse
sustainable societies and circular economies, resulting in new
industries, new jobs, innovations and opportunities. The
circular transformation can provide also innovation and
prosperity to labour market and foster economic growth,
resulting in more affordable transition costs.
2 T.A. Branca et al.: Matériaux & Techniques 108, 508 (2020)
Concerning future perspectives, research programs and
activities play a crucial role for implementing Industry 4.0
concepts in steel industry. For instance, 156 projects,
funded by the Research Fund for Coal and Steel (RFCS),
involving digitalization and Industry 4.0-related technolo-
gies, were recently identied [33]. An investigation about
the current research initiatives implementing Industry 4.0
principles and technologies in the EU steel sector was based
on an approach including systematic review of funded
projects, patents analysis, expert interviews and a
qualitative survey of academics and practitioners working
in the steel sector [34]. Results showed that Industry 4.0 is
perceived as important for the steel sector, and the
expected results mainly concern process efciency and
possibility to develop new business models. It is also seen as
an opportunity to develop intelligent support systems for
the workforce. In addition, the lack of qualied personnel is
perceived as one of the main issues. On the other hand,
short payback requirements can represent an issue for
implementing Industry 4.0. In addition, internal manage-
ment is considered a driving force for implementing
Industry 4.0 projects, due to its cross-cutting nature. Steel
manufacturers tend to rely on external expertise and to
cooperate with external partners to implement Industry 4.0
concepts and related tools and technologies.
Although some rst attempts to apply AI to process
modelling and optimization were carried out in the 90-ies,
over the last decade the signicant evolution and increased
availability of computational resources opened far greater
opportunities for AI in steelworks. Therefore, nowadays in
the steel sector signicant technological applications are
ongoing. For instance, applications of Big Data and
Integrated Intelligent Manufacturing (I2M), as well as
applications of AI to process modelling and optimisation
are currently being explored to increase energy efciency
[35,36] and reduce CO
emissions [37,38]. In addition, to
reduce energy consumption and environmental impact,
new methodological approaches can lead to better
management of resources, such as waste materials reduc-
tion, recycling improvement, and reduced natural resour-
ces exploitation [3941]. Furthermore, Digital Twins can
be used for planning and control plant activities. If
products and plants are digitally connected, intelligent
automation of processing steps can be achieved, including
real-time traceability of objects and their states [4244].
In a recent review paper, current technological trans-
formations and main developments funded by EU Research
Programs were described and analyzed along with impact of
digitalization on workforce and economic developments in
the steel sector [45]. As highlighted in this work, the future of
digitalization in the steel sector will be based on integration,
for instance, of Information Technology (IT), automation,
optimization technologies, adaptive online control, through-
process optimization, through-process synchronization of
data, zero-defect manufacturing, traceability and intelligent
and integrated manufacturing. In addition, the challenge of
digitalization is based on vertical, horizontal and transversal
integration of systems and production units as well as along
the whole lifecycle of the plant production. However,
automation of processes already involved the steel produc-
tion chain, leading to reduction of manual labour.
The recruitment shortage in the steel sector is mainly
due to different factors (e.g. lack of adequate proles,
difcult integration of new technologies, in particular
among older workers and employees, age gap between
current and potential workforce, low investments in
training and education, lack of strategies on long-term
competences). Even in the transition from Industry 3.0 to
Industry 4.0, the main fear was represented by workers
replacement by machinery. In particular, automation and
robotic generate new job proles, but can also produce job
losses. For this reason, creation of new jobs and workers
retraining represent signicant future challenges [46]. On
this subject, potentials and opportunities of human-robot
interaction [47] were implemented in a steelmaking process,
by also considering a social innovation paradigm [48]. In
particular, robot can contribute to improve workershealth
and safety conditions by carrying out the most cumber-
some activities, while workers supervise the operations [49].
For all these reasons, and due also to skills gaps,
mismatches and shortages, the steel industry is committed
to face these issues through new strategies and initiatives.
They are based on up-skilling and re-skilling programmes
to improve interdisciplinary skills and preserve competi-
tiveness. In the context of Industry 4.0, the workforce will
be required to interact with digital devices and trust in new
technologies, moving away from monotonous and repeti-
tive works. This will lead to improve skills, such as
teamwork, problem-solving and decision-making, as well as
to a continuous learning process. The implementation of
smart and digital components in the steel sector could
attract more highly educated candidates. Furthermore, the
process to low-carbon competitive steel industry will
produce an increasing demand for research engineers and
technicians holding competences on material recycling and
resource optimization. Strategies for attracting and
retaining qualied people, such as educational programs
implemented in collaboration with universities and
Vocational Education and Training (VET) institutions,
can help to enroll more qualied workforce. A recent study
was focused on gathering perceptions on current and future
steelmaking workforce in the European steel sector from
key stakeholders, students, graduates and jobseekers with
a STEM (Science, Technology, Engineering, and Mathe-
matics) background [50]. In addition, the main drivers and
barriers affecting steelmaking as a possible career choice
were identied, with a specic focus on skills supply and
demand, aiming at providing a clear understanding of the
mismatch between demand and supply to a long-term skill
strategy. The work presented in this paper is part of the
Erasmus+ Blueprint project entitled New Skills Agenda
Steel: Industry-driven sustainable European Steel Skills
Agenda and Strategy(ESSA), started in January 2019.
The ESSA project focuses on the development of a
Blueprint to achieve sustainability in the steel industry,
according to the fast increase of inuence and requirements
of Industry 4.0. The project aims at improving the
competitiveness of the European steel sector via proactive
skills adjustment, also including energy efciency and
environmental aspects. Based on continuous training
activities, workforces skill improvements can be achieved,
according to the sector demands. In particular, some
T.A. Branca et al.: Matériaux & Techniques 108, 508 (2020) 3
signicant challenges, crucial for Industry 4.0, can be faced,
such as re-skilling of current employees and increased
attraction and recruitment of talents. [51,52].
This paper presents a (still limited) rst spotlight on
the foreseen implementation of Industry 4.0 technologies in
the steel sector and its impact on the workforce by the
results of a survey carried out to overview the current state
of digitalization in European Steel Industry. The existing
level of plant automation and the adoption of the new
paradigm of Industry 4.0, including the resulting impact on
the workforce, were assessed. To this aim, a questionnaire
was developed and launched during the early stages of the
project, which was addressed to European steel companies.
The paper is organized as follows: Section 2 presents the
structure of the questionnaire; then, the survey results are
discussed in the Section 3, by considering the planned
Strategy, Technical Aspects and Human Resources (HR)
impact; nally, in the Section 4 some concluding remarks as
well as some notes on the future work are presented.
2 Structure of the questionnaire
The survey aimed at collecting information directly from
the various companys representatives, concerning the
current state of the digitalization in the European Steel
Industry. The on-line questionnaire was partly structured
and partly unstructured. Structured questions provided a
predened set of responses, while unstructured questions
(i.e. questions with open answer) provided deeper
information on the respondentsopinion, to explore and
collect new ideas. The questionnaire was organized into
different sections, as follows: General information, Strate-
gy, Technical Aspects and HR. The rst section mainly
includes country, company size (e.g. Small and Medium-
sized Enterprise-SME, Medium Enterprise, Large Enter-
prise), type of product, production route and output. The
sample considered in the analysis mainly includes large
companies (see Fig. 1) located in several European
countries, as depicted in Figure 2.
The second section includes questions related to the
implemented strategy, such as traditional solutions applied
before Industry 4.0, state of digitalization, priorities on
digital technologies and which of them will be adopted, how
they will affect workforce, companys involvement in
research projects on digitalization (past, current and
future/planned ones). The third section proposes questions
related to technical aspects, such as awareness of
opportunities and threats from additive manufacturing,
areas of applications of digital technologies, expected
benets and major barriers. The fourth section, concerning
HRs, includes questions about gender balance, age prole,
percentage of each category of employers with higher
education, foreseen evolution of workforce size in the
incoming years, awareness of each staff category about
digital competences demands, and training programs on
Industry 4.0 topics.
The representativeness of the survey results in terms of
general information, such as origin country of respondents,
company size, production route and product types, was
taken into account. In particular, answers primarily
involved several professional proles, e.g. board director,
plant managers, Information Communication Technology
(ICT) managers, HR managers. In addition, both produc-
tion routes are represented (i.e. blast furnace route, based
on iron ore, and electric route, based on scrap), with a
majority of respondents coming from the integrated route.
Finally, as far as product types are concerned, they were
mainly represented by at products.
3 Results and discussion
3.1 Strategy
In the rst part of the questionnaire the state of
digitalization and plant automation in the steel industry
before Industry 4.0 was evaluated. In addition, the level of
knowledge and interest on Industry 4.0 enabling technolo-
gies were assessed. Results provided signicant level
(77,78%) of automation, while lower levels of Basic
Automation (BA) and full Process Integration (PI) were
detected. Furthermore, standard solutions, such as
Computer Aided Design (CAD), Product Data Manage-
ment (PDM), production control system, are currently
adopted. As shown in Figure 3, results conrm the
commitment of European steel companies to technological
improvements as a way to increase competitiveness.
The priority and importance for more or less all
companies involved in the survey were mainly focused on
Internet of Things (IoT), Analytics, Cyber Security and PI,
both horizontal and vertical integrations. In particular, PI,
mainly based on IoT, allows communication among
different units, but also leads to security issues. In
particular, IoT concerns a fully connected world, in which
various objects networked and connected by collecting and
exchanging data and information [53]. An online monitor-
ing system based on IoT architecture is typically composed
of four layers: sensing, network, service resource and
applications. For instance, a similar system was imple-
mented in a real continuous steel casting production
line [54]. Therefore, the listed priorities reect future trends
about interconnectivity and automation.
The survey results showed a general trend about the
high awareness of new technologies, although they have not
been applied yet. In particular, currently the most
investigated and applied technological elds in the steel
Fig. 1. % of the enterprises involved in the survey.
4 T.A. Branca et al.: Matériaux & Techniques 108, 508 (2020)
sector are IoT, Cloud Computing, Analytics, Cyber
Security and Product/Process Virtual Simulation. Con-
cerning investment plans, results highlighted the strategic
relevance of the selected technologies in the short term. In
particular, as shown in Figure 4, in the next few years, the
investments on Industry 4.0 technologies will be particu-
larly focused on Cyber Security, Analytics and IoT
applications (highlighted in orange in Fig. 4). Additive
Manufacturing (AM) is a specic 3D printing process,
which in industry makes it possible to build lighter,
stronger components and systems, by depositing material
according to digital 3D design data. In the steel sector this
technology opens up the possibility to develop innovative
alloys. The answers of a specic question on AM conrmed
some awareness about the opportunities and threats,
although AM is not among the main planned investments.
Fig. 2. The European countries involved in the survey.
Fig. 3. Traditional solutions currently applied in the European
steel companies.
Fig. 4. The planned investments within 3 years.
T.A. Branca et al.: Matériaux & Techniques 108, 508 (2020) 5
These results conrm steel industry commitment towards
Industry 4.0 through planned investments, to increase its
Concerning the impact of digital technologies on
workforce, increasing training, requirement of new skills
and upgrading of existing ones were considered as the main
impacts, while workforce deskilling was indicated as less
affected. On the other hand, impacts on employees were
identied, in particular: improvement of work conditions
(e.g. workplace), health and safety, increased working time
and work-life balance.
Finally, another aspect, which was taken into account
in the survey, concerned the participation in the European
joint research projects on digitalisation. Results showed the
current involvement of some companies, while other ones
planned to participate. Nevertheless, signicant percen-
tages of the interviewed companies are not involved. In
particular, about half is currently involved in few projects
(<5) and the remaining is equally divided in up to 10 or
more. In addition, increasing interest in joint research
projects was detected.
3.2 Technical aspects
Concerning the investigated technical aspects, by consid-
ering the areas where digital technologies are applied,
expected benets and major barriers to be overcome during
their application were considered.
Survey results (see Fig. 5)showedthatdigital
technologies are applied in the process chain control,
and where management of large amounts of data is
required (i.e. production, business, etc.). In addition,
maintenance, administration, quality control and HR
management are mainly considered in the application of
Concerning expected benets from adoption of enabling
technologies, results showed a homogeneous distribution of
listed benets (see Fig. 6), with higher results mainly
focused on production in terms of cost reduction and
quality improvement, as well as on increased workplace
safety. In addition, environmental benets, such as
reductions of emissions, wastes and resources consumption,
are ranked high in the results.
Fig. 5. Digitalization in the areas of companies involved in the survey.
Fig. 6. The expected benets from adopting enabling technologies.
6 T.A. Branca et al.: Matériaux & Techniques 108, 508 (2020)
Concerning the main barriers affecting adoption and
application of new technologies, results were mainly
focused on the central categories, based on their impor-
tance (Less important, Moderately important, Very
important), as shown in Figure 7.
In particular, the proposed barriers were enough
uniformly distributed as Moderately important. Further-
more, cost of investment is the most relevant barrier among
Important categories. On the other hand, as shown in
Figure 7, know-how protection was considered as the least
important barrier.
As also shown in Figure 7, the barriers affecting aspects
related to workforce, such as lack of highly skilled
workforce, skill gap and acceptance of new technologies
by the workforce, were highlighted as Moderately impor-
tant, but they were also pointed out as signicant among
the important barriers. In addition, obsolescence of plant/
infrastructures and equipment and compatibility with
existing technologies and process were highlighted as the
most Important barriers.
3.3 Human resources
Regarding workforce proles, focused on HRs and current
and future workforce over the last 5 years, age and
education were taken into account. Although lack of data
and data inhomogeneity were detected, the following
aspects were highlighted:
An imbalance between male and female percentages,
with higher percentage of males in all the three
considered areas, i.e. operations, administration and
services, with the maximum imbalance in the operation
Concerning age prole, the values are reported in
absolute value. According to the available valid data,
results showed a slight workforce age redistribution
during the period from 2015 to 2019. In particular, a
certain stability in each presented age class (lower than
25 and between 25 and 34 years old) can be estimated,
with a substantial rising in the last two years for
personnel from 3544 years old. On the other hand, the
4554 age class showed an opposite trend, i.e. a decrease
from 20152016 to 2019. The last groups (between 55 and
64 years old) showed a stabilization in the overall
considered period, while the over 64 age group presented
a moderate increase.
Higher education represents a requisite for most
production managers and engineers compared to tech-
nicians, operators and apprentices/trainees.
Concerning workforce development in the next 35 years,
the sample was subdivided between the increase and the
decrease of the trend (50% yes, 50% no). Nevertheless,
the common trend focuses on the increase of women
employment, compared to the past, as well as on
recruitment of people with higher qualication, to
incorporate deeper knowledge and stronger skills for
exploiting new technologies.
A further noticeable aspect is represented by the
increased employee awareness related to the need for
digital competences. Among the different proles,
production managers and engineers (compared to
technicians, operators and apprentices/trainees) were
the most aware of the need for digital competences.
Finally, although staff training programs can be crucial
to meet Industry 4.0 challenges, results showed that few
training programmes are currently scheduled on com-
panys digital products and services, communication,
technology and innovation.
4 Conclusions
Although this article is a small and initial attempt to
analyse the digital and green transition of the steel
industry, the results of the conducted survey analysis
support a deeper understanding of the companiestrend
related to implementation of digital technologies in their
production processes and, consequently, about the evolu-
tion of workforce skills. In particular, the survey results
showed signicant levels of automation in the involved
steel companies. This represents a starting point for
improving technological aspects. Concerning Industry 4.0
technologies, they resulted to be generally widely known.
In addition, companies showed interest in IoT, Analytics,
Cyber Security and PI (both horizontal and vertical). Some
Fig. 7. The distribution of the main digitalization barriers.
T.A. Branca et al.: Matériaux & Techniques 108, 508 (2020) 7
of these technologies have already been integrated in the
production processes, and are taken into account in
planned future investments within short time (i.e. 3 years).
Concerning the impact of the digital technologies on
workforce, results highlight the need of improving work
conditions, such as workplace environment and health and
safety aspects, and increased working time and the work-
life balance. In addition, a growing interest in European
research projects is highlighted, although no funding
programmes are mentioned, and some companies have
not been involved in such projects yet.
Currently, digital technologies are applied in all areas of
the companies, in particular in process chain control, and in
areas requiring management of large volumes of data, e.g.
production and business. The expected benets are mainly
dealing with production, such as cost reduction and quality
improvement, working conditions in terms of safer and
healthier workplaces, and improvement of environmental
impacts, such as reduction of wastes, emissions and
resources consumptions. On the other hand, the highlight-
ed barriers for adoption and application of enabling
technologies concern investment costs. These costs should
be assessed by taking into account obsolescence of plant/
infrastructures and equipment. In addition, the compati-
bility with existing technologies should be considered.
Furthermore, the barriers affecting the workforce aspects
consist in lack of highly skilled workforce, skills gap and
lack of condence of some workers (especially older ones) in
new technologies.
Further discussions in the ESSA project underlines that
the impact on the workforce mainly concerns the
requirement of T-shaped skills with a focus on horizontal,
transversal soft-skills (digital, green, social, methodologi-
cal, individual and personal skills) as well as the need of
continuous learning in an interdisciplinary perspective
(and environment). However, the concrete impact of
digitalization on the low skilled workers and the effect
on employment as well as recruitment difculties for high-
skilled workers remain open to further discussion.
As the steel industry is evolving towards industry 4.0
starting mainly from a high level of automation it is more
an evolution or incremental adjustment instead of an
industrial revolution. The survey and discussions in ESSA
stress that the challenge of digitalization concerns the
integration of all systems (sensors, automation, and IT
systems) and all production units in different dimensions
(horizontal, vertical and transversal). In this context, the
steel industrys expectations from digital and green
transformation concentrate on quality, exibility and
productivity through the optimization and new interac-
tions of the individual production units. Economic aspects
include not only the reduction operational costs (i.e.
energy/row materials consumption reduction), but also the
introduction of new business models and organizational
However, it can already be emphasised that people (or
the human factor) are still needed with their experience and
skills to implement and run the new systems. Therefore, an
integration of technological innovation development
within a social innovation process (with co-creation and
teamwork) is supporting an effective technological innova-
tion as well as an upskilling of the workforce is needed to
unfold the potential of these innovations at the workplace.
As discussed with the stakeholders and companies of
the steel industry, even in Industry 4.0 social and
organisational factors are still the driver of productivity
and innovation. To say it with Klaus Schwab [55], Founder
and Executive Chairman of the World Economic Forum:
Leaders and citizens together shape a future that works for
all by putting people rst, empowering them and
constantly reminding ourselves that all of these new
technologies are rst and foremost tools made by people for
The ESSA project, which delivered the described
results, is still in ongoing. The questionnaire will remain
online to involve additional companies and, consequently,
to enlarge the analyzed sample. This will provide
increasingly representative data on the situation of the
European steel sector about the implementation of the new
concepts of industry 4.0.
Acknowledgments. The research described in the present paper
was developed within the project entitled Blueprint New Skills
Agenda Steel: Industry-driven sustainable European Steel Skills
Agenda and Strategy (ESSA)and is based on a preliminary
deliverable of this project. The ESSA project is funded by
Erasmus Plus Programme of the European Union, Grant
Agreement No 2018-3019/001-001, Project No. 600886-1-2018-
1-DE-EPPKA2-SSA-B. The sole responsibility of the issues
treated in the present paper lies with the authors; the Commission
is not responsible for any use that may be made of the information
contained therein. The authors wish to acknowledge with thanks
the European Union for the opportunity granted that has made
possible the development of the present work. The authors also
wish to thank all partners of the project for their support and the
fruitful discussion that led to successful completion of the present
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Cite this article as: Teresa Annunziata Branca, Barbara Fornai, Valentina Colla, Maria Maddalena Murri, Eliana Streppa,
Antonius Johannes Schröder, Current and future aspects of the digital transformation in the European Steel Industry, Matériaux &
Techniques 108, 508 (2020)
10 T.A. Branca et al.: Matériaux & Techniques 108, 508 (2020)
... Industry 4.0 is primarily to leave steel mills. The "lean" concept is still valid during the transition of mills to Industry 4.0 [74,75]. It is assumed that Industry 4.0 technologies will contribute to a decrease in production costs in the long term (from the start of the investment). ...
... The first results of field research on the current state of digitalization in the European steel industry are presented in scientific publications [75]. In this paper, we present the results (online questionnaire) carried out in the steel sector in the EU (the dominant segment was large steel companies). ...
... In this paper, we present the results (online questionnaire) carried out in the steel sector in the EU (the dominant segment was large steel companies). The results are presented by Branca et al. in three areas: strategy, technical aspects, and human relations (HR) [75]. The strategic areas of change for steel producers in terms of the technology challenges of Industry 4.0 are digitization, automation, Internet of Things (IoT), analytics, cybersecurity, and process integration (PI), both for horizontal and vertical integration. ...
Full-text available
The publication presents a picture of modern steelworks that is evolving from steelworks 3.0 to steelworks 4.0. The paper was created on the basis of secondary sources of information (desk research). The entire publication concerns the emerging opportunities for the development of the steel producers to Industry 4.0 and the changes already implemented in the steel plants. The collected information shows the support environment for changes in the steel sector (EU programs), the levels of evolution of steel mills, along with the areas of change in the steel industry and implemented investment projects. The work consists of a theoretical part based on a literature review and a practical part based on case studies. The work ends with a discussion in which the staged and segmented nature of the changes introduced in the analyzed sector is emphasized. Based on the three case studies described in the paper, a comparative analysis was conducted between them. When we tried to compare methods used in the three analyzed steel producers (capital groups): ArcelorMittal, Thyssenkrupp, and Tata Steel Group, it can be seen that in all organizations, the main problem connected with steelworks 4.0 transition is the digitalization of all processes within an organization and in the entire supply chain. This is realized using various tools and methods but they are concentrated on using technologies and methods such as artificial intelligence, drones, virtual reality, full automatization, and industrial robots. The effects are connected to better relations with customers, which leads to an increase in customer satisfaction and the organizations’ profit. The steel industry will undergo further strong changes, bringing it closer to Industry 4.0 because it occupies an important place in the economies of many countries due to the strong dependence of steel producers on the markets of the recipients (steel consumers). Steel is the basic material needed to make many products, and its properties have been valued for centuries. In addition, steel mills with positive economic, social, and environmental aspects are part of the concept of sustainability for industries and economies.
... Integrating fixed and mobile digital tools within conventional organizational processes is the most basic form of workplace digitalization (Meske & Junglas, 2021). Also, a digitalized workplace is established on advanced machine-human collaboration, which boosts the employees' contribution to organizational performance (Branca et al., 2020). Automation and robotization are common attributes of a digitalized workplace, enacting a cyber-physical arrangement of work-related practices (Gutsche & Griffith, 2017;Peifer et al., 2020). ...
Work digitalization may nurture psycho-social strain at work, undermining employees’ health and safety and challenging the ability of small and medium-sized enterprises (SMEs) to achieve organizational excellence. This prevents SMEs from implementing sustainable human resource management practices and from attaining a Total Quality Management approach which is consistent with the Environmental, Social and Corporate Governance criteria. Such considerations are especially true in the post-Covid-19 era where digitalization serves the purpose of ensuring business continuity, avoiding disruptions triggered by social distancing. The article provides empirical evidence of digitalization's implications on psycho-social risks at work perceived by people employed in SMEs, examining the moderating role of, organizational safety and health measures. Two sub-samples of companies operating in the manufacturing sector and in the service industries were involved in the study, which relied on secondary data. The research findings highlighted that digitalization has side effects on psycho-social risks at work. Organizational safety and health measures have a moderating role on psycho-social risks at work; however, it is weak in highly digitalized contexts and it is not significant across manufacturing companies. Tailored organizational safety and health measures should be developed to curb the drawback of digitalization on psycho-social risks at work.
... In the first half of 2021, 40 papers were published regarding green transformation. Mostly however, they related again to the regional point of view and explain the determinants of implementing green transformation strategies (Mets et al., 2021;Yang et al., 2021) in particular countries like Norway (Karlsson and Hovelsrud, 2021), Italy (Alekseenkova, 2021) or specific industries, e.g. the maritime (Alekseenkova, 2021), the energy sector (Palmie et al., 2021) and the steel industry (Branca et al., 2020). Most common are still the papers regarding the road to green transformation in China as well as the status quo and prospects (Zeng et al., 2021;Zhai and An, 2021;Yang et al., 2021;Zhang and Fang, 2021;Hu et al., 2021;Liu et al., 2021), Chinese provinces (Cui and Lui, 2021) or industries Du et al., 2021;Li et al., 2021;Gao et al., 2021). ...
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Green transformation has become one of the most important directions in the further development of the world. It involves the development of green technologies and the creation of legal regulations enforcing, for example, saving energy or reducing the emissions of greenhouse gases, as well as any other activities aimed at changing society’s attitude towards the acceptance of – frequently more expensive but more environment-friendly – technological solutions and legal norms. Thus green transformation can be defined as combining economic growth with caring about the environment in order to guarantee a high quality of life for present and future generations at the level which is attainable due to civilisational development, as well as to an effective and rational use of the available resources. Still, there is no single globally accepted way to this transformation. It is proceeding in a variety of ways and depends on many different factors. The main purpose of the paper is a comparative analysis of the directions of changes occurring in the process of green transformation in EU countries. The added value of the research presented in the paper and its novelty is the analysis of the current patterns of green transformation in EU countries. The paper concentrated on recognizing them and drawing attention to the unfavourable directions of this transformation as well as to its positive aspects. The changes in the process of green transformation were analysed based on data used by the OECD to describe green growth in two periods: 2004 or 2005 as initial data and the last available data (usually 2018 or 2019). For this purpose the TOPSIS method was applied. The EU countries were divided into groups according to their way of applying green transformation. The provided research allows to better understand the course of this transformation in various EU countries.
... The authors of this study commit themselves to the definition that Industry 4.0 encompasses automation, robotics, artificial intelligence, and Internet of Things (IoT) in services and manufacturing, and will result in systems that blur the boundaries of the real world and virtual reality, which will be connected by cyberphysical production systems (CPPS). Industry 4.0 cannot be described in one word; however, the literature often uses the terms digitalization or digital transformation [29,30]. Thus, based on this literature, these terms are also used as a synonym for Industry 4.0 in this study. ...
Full-text available
The research objective of this study is to examine the changes in technological unemployment and to evaluate Keynes’ theory based on a literature analysis concerning the fourth industrial revolution. The methodology used in this study is a literature analysis of 86 papers published between 2011 and 2020 on topics related to Industry 4.0, the labor market, and technological unemployment. The change caused by the labor market raises employment sustainability issues. Among the goals adopted at the 2012 UN Rio+20 Conference on Sustainable Development, this study is directly related to goals 8 and 9, and indirectly to goal 10. Research evidence suggests that the impact of Industry 4.0 processes will reduce the amount of labor needed, bringing us closer to Keynes’ vision of three hours a day. The analysis suggests that reduced working hours will increase economic efficiency through more intensive work. The literature is used to determine whether the trend of reduced working hours can be interpreted as a positive or negative phenomenon. The extent of technological unemployment is determined by the digitalization strategy of each country and the speed of its introduction, as well as the readiness of the education system in a given country to retrain vulnerable groups in the labor market. However, the overall picture is positive: on the one hand, digital transformation opens up a wide range of opportunities for a more human life, and on the other hand, from an economic point of view, digitalization will become an inescapable element of competition by reducing marginal costs. The study’s novelty is that the effects of Industry 4.0 and technological unemployment on the labor market are analyzed in the context of Keynes’ theory.
... Coopetition may take various forms, but interdependency is a pivotal fact when systemic development is discussed in the field of steel businesses. Digital transformation and transition to Industry 4.0 are considered possible for actors in the steel industry solely under the framework of collaboration and fostering of partnerships (Murri et al., 2019;Neef et al., 2018). And when collaboration with direct competitors is difficult due to the high intensity of competition in the market, working with other SMEs who sell complimentary products, and establishing strong personal ties at a managerial level with retired managers who have strong connections in the field, who are still part of business networks, are important tools for SMEs seeking support (Cragg et al., 2019). ...
Purpose The present study aims to tackle SMEs (small and medium-sized enterprises) managers' awareness of coopetition benefits underpinning the process of knowledge sharing with a view to achieve innovative performance. The scrutiny of coopetition is placed within the context of SMEs strategic networks, which foster a fertile ground for competitive knowledge sharing and direct collaboration among members. Design/methodology/approach In total, 102 top managers and business owners of European steel SMEs were questioned regarding various issues related to coopetition, knowledge, collaboration and innovative performance strategies. The collected data were analyzed via the technique of partial least squares structural equation modeling (PLS-SEM). Findings The obtained values confirm that intense competition in the field stimulates SMEs to become aware of the benefits of coopetition. This awareness directly influences the innovative performance of the SMEs, as well as their interest in competitive knowledge sharing and their willingness to engage in direct collaboration. Direct collaboration catalyzes more intense competitive knowledge sharing at the inter-unit level whereas both direct collaboration and competitive knowledge sharing lead to better innovative performance in the case of the studied steel SMEs. Research limitations/implications A key theoretical contribution resides in revealing the influence of manifold factors in the overall equation of innovative performance, integrating competition, coopetition and knowledge sharing as antecedents. Originality/value The research advances a phenomenological view on SMEs networks in their strategy to leverage competitive knowledge and enhance system-driven innovation.
... The last two articles [12,13] tackle the interface between steel production and digitalization. They present digitalization as an enabler of the circular economy and of industrial symbiosis. ...
Industry 4.0, or the fourth industrial revolution, is a new paradigm in manufacturing digitalization, which provides various opportunities for enterprises. Industry 4.0 readiness models are worthy methods to aid manufacturing organizations in tracking the development of their businesses and operations. Nevertheless, there are different Industry 4.0 readiness models; no work has yet analyzed Industry 4.0 readiness degree and causal effects relationships using fuzzy cognitive maps. This paper proposes an Industry 4.0 readiness model that consists of readiness requirements obtained from the literature and validated through a mixed-method approach, including literature reviews and questionnaires. To validate the proposed Industry 4.0 readiness model, the exploratory factor analysis and confirmatory factor analysis methods are used. Fuzzy Cognitive Map is utilized to assess readiness, identify relevant concepts to improve readiness degree, implement Industry 4.0, and analyze causal relationships among concepts and dimensions. Through this model and the FCM method, managers can recognize relevant concepts and predict complicated cause-effect relationships among concepts in two states of static and dynamic analyses to increase readiness degree. The paper concludes by emphasizing managerial implications for successful applications in practice as well as future research suggestions on developing the Industry 4.0 readiness model.
The steel industry is on its way towards more environmentally friendly steelmaking. To achieve the ambitious goals of significant CO2 emissions reduction, new processes, practices, sources of on-line data, and digitalization together with automation will be required. To address these issues, this paper discusses optical emission spectroscopy (OES) as an on-line data acquisition method for industrial electric arc furnaces and ladle furnaces. The current state of the OES as a measurement method in the steel industry together with prospects of new applications are presented with examples based on the authors’ prior research.
Digital technology is gradually changing the organisation of production and work. In this article, the authors explore the implications of such developments for workers through the lens of skill, and the skill needs developing out of the shift towards Industry 4.0 technologies now being employed within the European steel industry. Specifically, the article examines the preparedness of initial vocational training systems to support adaptation to Industry 4.0 and the changes in work and employment that will follow. The article addresses such developments from the point of view of institutional theory, analysing how different institutional architectures influence responses to change.
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This paper aims at exploring the perspective of sustainability when digital transformation is adopted by one organization, although it was not the first goal targeted. Two different cases are analyzed, covering manufacturing and service industries. In those cases different factors will be analyzed, mainly focused on the positive effects of knowledge creation facilitated by direct or indirect application of digitalization. Specific analysis of different cases were carried out to identify different initiatives and the impact on environmental performance. The positive effects of the institutional dimension were also assessed.
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Digitalization represents a paramount process started some decades ago, but which received a strong acceleration by Industry 4.0 and now directly impacts all the process and manufacturing sectors. It is expected to allow the European industry to increase its production efficiency and its sustainability. In particular, in the energy-intensive industries, such as the steel industry, digitalization concerns the application of the related technologies to the production processes, focusing on two main often overlapping directions: Advanced tools for the optimization of the production chain and specific technologies for low-carbon and sustainable production. Furthermore, the rapid evolution of the technologies in the steel sector require the continuous update of the skills of the industrial workforce. The present review paper, resulting from a recent study developed inside a Blueprint European project, introduces the context of digitalization and some important definitions in both the European industry and the European iron and steel sector. The current technological transformation is depicted, and the main developments funded by European Research Programs are analyzed. Moreover, the impact of digitalization on the steel industry workforce are considered together with the foreseen economic developments.
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Automation and digitalization of processes requires an extensive redesign of all interrelated material flow and information flow processes. A major obstacle to effective logistics management is the problem of inconsistent identification and therefore limited traceability. Derived from a steel industry case study and based on a systematic literature review, the authors will investigate potential identification of technologies for consistent identification and traceability of products along the supply chain. This includes an analysis of existing information and communication technology (ICT) approaches to identification in logistics flows, and the discussion of evaluation criteria related to small- and medium-sized enterprises (SME), development of an evaluation methodology, and finally assessment of their major potentials and suitability in SME logistics.
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The premise of this study is to investigate how labor will be affected by the move to a circular economy supported by digitalization. This study thus proposes the introduction of circular economy as a transformation of businesses, society, industries and labor, and it proves that digitalization is one tool to aid that transformation. This chapter does not seek to prognosticate answers or provide a one-size-fits-all solution, as a potential future circular scenario involves major uncertainties and lacks real case studies on which to base predictions. Rather, this chapter offers a conceptual study that seeks to draw upon available literature and research findings in order to answer how the labor conditions are affected when digitalization is used to achieve circular businesses and societies in different ways. The chapter concludes by contending that the circular economy is fundamentally reshuffling our current economic system. As such, it should be viewed as an innovation and as a strategy not only for businesses, but for society as a whole. Digitalization will be an essential instrument in enabling and facilitating the circular economy.
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Production technology in European steel industry has reached such a level, that significant improvements can only be reached by through process optimization strategies instead of separately improving each process step. Therefore, the connection of suitable technological models to describe process and product behavior, methods to find solutions for typical multi-criterial decisions, and a strong communication between involved plants is necessary. In this work, a virtual simulation platform for the design of cyber-physical production optimization systems for long production facilities focusing on thermal evolution and related material quality is presented. Models for describing physical processes, computers, software and networks as well as methods and algorithms for through process optimization were implemented and merged into a new and comprehensive model-based software architecture. Object-oriented languages are addressed and used because they provide modularity, a high-level of abstraction and constructs that allow direct implementation and usage of the cyber-physical production systems concepts. Simulation results show how the proper connection between models, communication, and optimization methods allows feasibility, safety and benefits of cyber-physical production systems to be established. Furthermore, the software architecture is flexible and general and thus, can be transferred to any steel production line as well as outside the steel industry.
Despite the relevance of sustainable Industry 4.0, only limited research has been conducted on this topic. Using and replicating data from AlphaWise, CompTIA, Deloitte, Globant, McKinsey, Morgan Stanley, PAC, PwC, SME, and we.CONECT, we performed analyses and made estimates regarding the link between artificial intelligence-based decision-making algorithms, automated production sys-tems, and big data-driven innovation. The results of a study based on data collected from 5,300 respondents provide support for our research model. Using the structural equation modeling, we gathered and analyzed data through a self-administrated ques-tionnaire.
In this paper the idea of Self-Optimizing Machining Systems (SOMS) is introduced and discussed. Against the background of Industry 4.0, here the focus is the technological level of discrete workpiece production by mechanical machining processes utilizing related machine tools and equipment. Enabling technologies, principles, and methods are described that allow for the implementation of machining systems which are capable of adapting their parameters and settings autonomously, in order to optimize for productivity, quality, and efficiency in manufacturing. Following a description of the meaning and a definition of SOMS as well as a historical retrospection, the required elements of SOMS are discussed and exemplary approaches are presented. Based on sophisticated process planning, monitoring, adaptive control, simulation, artificial intelligence, and machine learning, strategies, state-of-the-art solutions for self-optimization in machining applications are introduced. Several examples showcase how different types of enabling technologies can be integrated synergistically, to improve the manufacturing of parts by SOMS. Finally, the future potential of SOMS as well as challenges and needs are summarized. The paper especially considers the results of the CIRP Cross-STC Collaborative Working Group on SOMS.
Digitalization is widely accepted as a principal technological strategy and is expected to vastly impact and transform industry, predominantly by a substantial improvement of the entire value chain. However, its implementation process remains slow, in particular for small and medium-sized enterprises (SMEs), as they tend to have misconceptions about the complexity and expense of digitalization. The purpose of this research is to analyze factors that affect Brandenburg-State, DEU SMEs in their decision making process for an effective implementation of digital technologies in their daily business routine. The results of this study are based on a survey that was conducted in cooperation with fifty SMEs, which currently face problems in the areas of enterprise resource planning (ERP), CAD/CAM, automation, logistics and production/factory planning. Ten of these SMEs have decided to invest in digitalization measures and started the implementation process. Three of them were chosen for the case study to evaluate potential benefits, trade-offs and barriers hampering the implementation of digitalization technologies. These three companies are considered representative items, since their needs and measures investigated were identical to most of the companies of this survey. It was found that the overwhelming majority of the companies regard ERP implementation as their highest priority when investing in the most cost-effective technology.
Industry 4.0 is a ubiquitous term throughout general newspapers, on company websites or in scientific journals. One of its key constructs is the smart factory, envisioned as a future state of a fully connected manufacturing system, mainly operating without human force by generating, transferring, receiving and processing necessary data to conduct all required tasks for producing all kinds of goods. Although the understanding of smart factory concepts has been sharpened in the last years, it is still difficult for industrial companies to establish a concrete strategy roadmap within the jungle of different terminologies, ideas and concepts. To generate further clarity and to consolidate the previous findings around smart factory for researchers as well as for practitioner, we conducted a systematic literature review. For this purpose, we chose a five steps approach: Scope definition, topic conceptualisation, literature search, literature analysis and synthesis, and synthesis of future research questions. During our review, we found that research within each perspective is fragmented and unequally advanced. Most publications treat single use cases with low generalizability, often rely upon machine data, typically have a technical nature and seldom incorporate impact estimations. In this paper, our key academic and practical contribution lies in the categorisation of the selected publications into eight thematic distinct perspectives within the sphere of smart factory: Decision making, cyber-physical systems, data handling, IT infrastructure, digital transformation, human machine interaction, IoT, and cloud manufacturing and services. These are further developed into the smart factory research model, stating a foundation for future research endeavors.
Steel industry consumes resources and produces important amounts of by‐products. Process modelling, simulation and optimization can address field tests for maximizing by‐products reuse. This paper presents improvements of a long‐lasting research activity on slag reuse by deepening aspects, only marginally considered in the past. An Aspen Plus® based model is developed to assess different Basic Oxygen Furnace slag pre‐treatment configurations or involved techniques. A previously developed reMIND‐based superstructure is upgraded, considering more slag pre‐treatments and qualities. A simplified Aspen Plus®‐based model of mixing of the different pre‐treated by‐products is applied to evaluate the chemical composition of pellets in each scenario, starting from the computed mixtures. The developed tools are exploited to get a holistic view of steelmaking by‐products reuse and to make multi‐objective optimization studies providing different results. For instance, the mixture to be pelletized completely changes if final products quality is (or not) considered in the optimization. Regarding the optimization combining all the considered objective functions, the best slag treatment includes a wet high intensity magnetic separation stage and only some slags qualities are considered in the pellet mixture. A preliminary economic analysis confirms that an optimal combination of internal and external recoveries of by‐products can produce noteworthy revenues. This article is protected by copyright. All rights reserved.