Design

Cognitive Assistance Systems in Intralogistics

Cognitive Assistance Systems in Intralogistics

User studies with augmented reality and an AI chatbot
Hendrik Stern ORCID Icon, Michael Freitag ORCID Icon
Assistance systems improve work processes, shorten learning times and increase flexibility in the workplace. Human-centered, resilient and sustainable production approaches where user acceptance is of the utmost importance play a crucial role in the digitized Industry 5.0. Two user studies investigate how useful the support of technologies like augmented reality and AI chat actually is. In the context of cognitive assistance systems in intralogistics, artificial intelligence and augmented reality have a great potential and can contribute to an improvement in process performance. The usability of these systems in terms of human-centricity of Industry 5.0 is crucial. This article describes the results and findings of two user studies conducted in the laboratory for intralogistics work processes (picking and packing). The assistance systems used were evaluated using the System Usability Scale.   Cognitive assistance systems in intralogistics Assistance systems make a ...
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 67-72 | DOI 10.30844/I4SE.24.5.66
Double Transformation as the Key to Sustainability

Double Transformation as the Key to Sustainability

Methodology for evaluating an AI application in manufacturing companies
Jennifer Link ORCID Icon, Markus Harlacher, Olaf Eisele, Sascha Stowasser
EU regulations demand more intensive and transparent sustainable practices from companies. Industry needs to adapt many processes and products to take charge of this responsibility. Artificial Intelligence (AI) in particular offers innovative potential. Firstly, however, this technology needs to be evaluated focusing on weak AI—market-ready systems that perform specific tasks using algorithms and data-supported models efficiently.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 82-89 | DOI 10.30844/I4SE.24.5.82
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.
Modular Learning Factories for Industry 4.0

Modular Learning Factories for Industry 4.0

Acquisition of a target-oriented acton competence to accelerate industrial implementation
Maximilian Dommermuth ORCID Icon
Industry 4.0 requires new teaching content due to its innovation potential. Skills profiles currently in demand often aren't reflected in vocational and tertiary education. Additionally, conventional further education and training often costs considerably money and time. Tailor-made learning opportunities and teaching targeted problem-solving skills in a modular learning factory are a more effective approach.
Industry 4.0 Science | Volume 40 | 2024 | Edition 4 | Pages 24-30 | DOI 10.30844/I4SE.24.4.24
A Learning Factory in Transition

A Learning Factory in Transition

Innovatively meeting the demands of the modern labor market
Nick Ackerhans, Benjamin März
Agile methods are extremely useful in solving complex problems. This is particularly beneficial in market environments where the routines of traditional corporate management are constantly being questioned. Agility is closely linked to the core ideas of Lean Management, as evidenced by the focus on processes and people. Lean factories facilitate a hands-on engagement with Lean principles, thereby promoting agile process management in various production contexts.
Industry 4.0 Science | Volume 40 | Edition 4 | Pages 63-68
The Key to Successful Digitalization

The Key to Successful Digitalization

Development, implementation and benefits of digital twins in Industry 4.0
Andreas Bayha ORCID Icon, Sönke Knoch ORCID Icon, Dirk Schöttke ORCID Icon
The success of technologies depends not only on their innovative strength and acceptance, but also on their management. Decision-makers evaluate factors like technical framework conditions and organizational requirements, with the demand for flexibility adding to the complexity. Industry 4.0 addresses this with networking, transparency and decentralized decisions. Digital twins, which can be implemented with open source software, play a key role.
Industry 4.0 Science | Volume 40 | Edition 4 | Pages 42-49
Simulated Production Environment Today

Simulated Production Environment Today

Evaluation of the numerical process simulation of selective laser melting
Emre Sahin ORCID Icon, Lennart Grüger ORCID Icon, Sebastian Härtel ORCID Icon
Numerical simulation for the optimization of conventional manufacturing processes is common practice in industry, but isn’t yet fully developed for generative manufacturing processes. The simulation of powder bed fusion (PBF) especially, with their more than 130 influencing factors, poses major challenges. Nevertheless, the methods developed can substantially accelerate product development, as an examination of common procedures and innovative approaches shows.
Industry 4.0 Science | Volume 40 | 2024 | Edition 4 | Pages 70-77 | DOI 10.30844/I4SE.24.4.70
Maturity Levels of Smart Knowledge Services

Maturity Levels of Smart Knowledge Services

Self-assessment and GAP analysis
Isger Glauninger ORCID Icon, Nick Tugarin ORCID Icon, Christian van Husen ORCID Icon
Digitalization opens up new forms of operational training. A growing focus is on smart services, which allow for proactive engagement with customer demands and empower businesses in times of digitalization. While traditional learning environments are rarely tailored toward individual needs, smart services offer new opportunities. Decentralization, previously only a utopic vision, is becoming the reality now.
Industry 4.0 Science | Volume 40 | 2024 | Edition 4 | Pages 50-56
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
Learning Factories as Innovative Training Locations for SMEs

Learning Factories as Innovative Training Locations for SMEs

Qualitative analysis of concepts and cooperations
Kathleen Warnhoff ORCID Icon, Simon Dabrowski ORCID Icon, Lea Müller-Greifenberg, Denise Gramß, Monika Stricker
In the context of Industry 4.0, learning factories are important places for company-based learning. Studies show that they have continued to develop since their emergence and are no longer limited to vocational and academic education. This leads to the question of how much the concept of the learning factory represents an innovative approach to further training in small and medium-sized enterprises (SMEs). This article focuses on three selected learning factories relevant to continuing education that were analyzed using qualitative methods with regard to their concepts and cooperation. The findings are embedded in a theoretical framework that links the scientific discussion on learning locations and educational cooperation. The empirical findings from three learning factories illustrate relevant learning locations for continuing education in SMEs.
Industry 4.0 Science | Volume 40 | 2024 | Edition 4 | Pages 32-41
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