Digitalisierung

Assembly in Transition

Assembly in Transition

Empirical results of digitalization
Mathias König ORCID Icon, Herwig Winkler ORCID Icon
Assembly is an important part of industrial production and is also characterized by a high proportion of manual work. Manufacturing companies have an intrinsic interest in increasing personnel productivity and preventing unit labor costs from rising. Many thus hope to gain economic benefits by implementing digitalization projects. The potential of digitalization in assembly must be exploited to achieve these goals.
Industry 4.0 Science | Volume 41 | 2025 | Edition 1 | Pages 42-49
Circular Economy Enabled by Digitization

Circular Economy Enabled by Digitization

Digital networking in the procurement of manufacturing companies
Pius Finkel ORCID Icon, Peter Wurster ORCID Icon, David Pfister
Current developments in digitalization and data economy, especially multilateral data sharing platforms, offer the potential to accelerate the implementation of circular economy practices in the manufacturing industry. This article systematically examines the extent to which digitalization could serve as a catalyst for circular economy in the procurement of such companies. As a basis for the following research, eight experts from five leading global manufacturers and suppliers in the automotive and aviation industries were interviewed. This article demonstrates practical hypotheses for the sustainable design of supply chains and proposes two specific use cases for circular economy practices that can proactively counteract the use of resources.
Industry 4.0 Science | Volume 41 | 2025 | Edition 1 | Pages 26-33 | DOI 10.30844/I4SE.25.1.26
Computer Use in Industrial Business Processes

Computer Use in Industrial Business Processes

A systematic literature review of the last 40 years
Norbert Gronau ORCID Icon
The most important value-adding industrial business processes are product creation and order processing. For 40 years now, Industry 4.0 Science and its predecessor titles have supported the development and implementation of the software used in these industrial business processes. In honor of the journal’s 40th anniversary, a systematic literature review is carried out to identify trends that played a role in the past but no longer do today. The research provides some surprising insights into the topics that have been important in the last 40 years – as well as those that will remain relevant in the future.
Industry 4.0 Science | Volume 41 | 2025 | Edition 1 | Pages 8-14 | DOI 10.30844/I4SE.25.1.8
Large Language Models (LLM) in Production

Large Language Models (LLM) in Production

An analysis of the potential for transforming production processes in modern factories
Pius Finkel ORCID Icon, Peter Wurster ORCID Icon, Robin Radler
The rapid development of generative artificial intelligence is opening up new avenues for the manufacturing industry amid a shortage of skilled workers. Large language models can potentially make production processes in medium- sized businesses more efficient. But how exactly is this potential measured? Key areas of application such as communication, training and knowledge management show why a lot depends on employee acceptance.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 48-55 | DOI 10.30844/I4SE.24.6.48
Digital Solutions for SMEs’ Circularity Transition

Digital Solutions for SMEs’ Circularity Transition

Examples from the textile industry
Markus Winkler, Dieter Stellmach, Guido Grau, Marcus Winkler, Meike Tilebein ORCID Icon
The EU Strategy for sustainable and circular textiles aims to reduce the industry’s environmental impact while at the same time increasing its competitiveness. In this transition towards circularity, firms in the highly fragmented textile value chains need solutions that help overcome barriers and provide support. This paper presents digital solutions that are particularly suited for SMEs and that have been developed with public funding. It aims at encouraging SMEs, not only from the textile industry, to specify their individual transition paths towards circularity and to use digitalization to foster implementation.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 26-33 | DOI 10.30844/I4SE.24.5.26
Digital and Ecological Transformation in Companies

Digital and Ecological Transformation in Companies

Challenges and potential in interaction
Manfred Wannöfel, Bernd Kuhlenkötter ORCID Icon, Christopher Prinz ORCID Icon, Fabian Hoose ORCID Icon, Manfred Wannöffel ORCID Icon
Although the concept of double transformation is being intensely discussed in companies, the practical implementation in operational structures often remains unclear. This article sheds light on how digital technologies and environmental sustainability strategies can be developed either synergistically, antagonistically or independently of each other. In addition, it discusses the different experiences of employees in different industries and the varying progress in the introduction of digital and ecological measures. To this end, it will discuss existing research findings and practical examples that pave the way for the successful integration of both transformation processes in companies.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 34-42 | DOI 10.30844/I4SE.24.5.34
I4S 5/2024: Double Transformation

I4S 5/2024: Double Transformation

Integrating digital and ecological change in the world of work
Change is necessary for companies to maintain their competitive edge—both digital and ecological change. But while external support is at hand, the drive for change must come from companies themselves. In this issue of Industry 4.0 Science, experts of the Academic Society for Work and Industrial Organization discuss how the real-world application of innovative technologies lead to resource-efficient manufacturing.
Additive Manufacturing 4.0 Learning Factory

Additive Manufacturing 4.0 Learning Factory

Digitalization for batch size 1
Fabian Riß, Nicolas Rolinck, Stefan Böhm ORCID Icon, Alessandro Morath
In the course of digitalization, collaboration between humans and machines is inevitable. This should be considered as early as possible in further training. There’s a major obstacle to this in mechanical engineering: the lack of access to the knowledge needed for success. This can have a negative impact on the acceptance of digitalized processes. A teaching and learning platform teaching digitalization on real machines does important work here.
Industry 4.0 Science | Volume 40 | 2024 | Edition 4 | Pages 57-62
Shaping Digital Change in Companies

Shaping Digital Change in Companies

Using the living lab approach and the backcasting method to develop a vision
Annalena Präger, David Koch ORCID Icon, Julia Brandt, Sebastian Schmid
Alongside sustainability, sustainability management is also gaining in importance. At the same time, digitalization continues to advance, embedded in a complex interplay of economic, ecological and social challenges. A sustainability platform that not only records relevant company data, but also ensures the necessary security, can unleash synergies between transformative trends to foster sustainable and efficient corporate development.
Industry 4.0 Science | Volume 40 | 2024 | Edition 3 | Pages 61-66
GAIA-X Maturity Model 

GAIA-X Maturity Model 

Assessing the future viability of cross-company 
data exchange
Maximilian Weiden, Jokim Janßen
In order to cope with growing customer requirements and the associated increase in complexity, companies are opening up their value chains, reducing their vertical integration and increasingly entering into collaborations. Cross-company data exchange along the supply chain is thus becoming a key component for competitiveness and the realization of customer-specific solutions. For this reason, the European Union has launched the GAIA-X project, which aims to create the next generation of data infrastructure for Europe and its companies. The GAIA-X maturity model offers an approach for classifying companies into different development stages and provides concrete requirements for further development along a predefined development path towards becoming a fully-fledged participant in the federated GAIA-X data infrastructure.
Industry 4.0 Science | Volume 40 | 2024 | Edition 3 | Pages 14-20
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