Künstliche Intelligenz

Intelligent Shopfloor Assistants

Intelligent Shopfloor Assistants

Increasing productivity through the use of generative AI
Eckart Uhlmann ORCID Icon, Julian Polte ORCID Icon, Christopher Mühlich ORCID Icon, Yassin Elsir
In modern production companies, a heterogeneous IT landscape often complicates day-to-day work. A promising antidote is the use of intelligent agents, which use generative AI for routine tasks and can therefore increase efficiency. Whether these intelligent systems can be successfully integrated into existing networks determines whether the flow of information can be improved and manual effort reduced.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 64-71
Introduction of Machine Learning in Production

Introduction of Machine Learning in Production

An SME-specific, holistic guide
Manuel Savadogo, Malte Stonis ORCID Icon, Peter Nyhuis ORCID Icon
Machine learning offers a wide range of potential, especially in production, and is therefore becoming increasingly important. However, small and medium-sized businesses are lacking guidelines that are specifically tailored to their individual challenges to guide them step-by-step through the process. In conjunction with a potential analysis, the determination of relevant prerequisites and a maturity assessment, this article can serve as a guide for SMEs.
Industry 4.0 Science | Volume 40 | 2024 | Edition 6 | Pages 88-95
I4S 6/2024: Machine Learning

I4S 6/2024: Machine Learning

A technology with optimization potential in terms of efficiency, transparency and sustainability
Machine learning takes automation to a new level. But what does this imply for the role of humans, who seem to remain essential for the effective control of AI systems. The development of energy-efficient and fair algorithms and the optimization of data quality are crucial for the future viability of machine learning and artificial intelligence. The articles in this issue examine the technology's key potential and areas of application.
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
AI-Assisted Work Planning

AI-Assisted Work Planning

Extracting expert knowledge from historical data for streamlined efficiency and error mitigation
Jochen Deuse ORCID Icon, Mathias Keil, Nils Killich, Ralph Hensel-Unger
Global competitive pressure is forcing companies to use resources efficiently, especially in high-wage countries. This is further intensified by market and legislative pressure for sustainable products and processes. In the face of digital and ecological change, holistic approaches to optimizing manual work processes are essential. An AI-supported assistance system for work plan creation is intended to remedy this and thus enable more efficient process design.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 74-80 | DOI 10.30844/I4SE.24.5.74
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 ORCID Icon, Olaf Eisele, Sascha Stowasser ORCID Icon
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
Training in Industry 4.0 with AI Tutoring Systems

Training in Industry 4.0 with AI Tutoring Systems

State of technology
Norbert Gronau ORCID Icon, Georg David Ritterbusch ORCID Icon
The rapid development of artificial intelligence (AI) is constantly opening new opportunities, particularly in training for the factory of the future. For employees, this not only means a significant advantage in the actual manufacturing process, but also in the field of continuing education. This paper provides an overview of AI tutoring systems continuing education in the context of Industry 4.0 by presenting a categorization that discusses different approaches of AI tutoring systems by learning methods, application areas and their respective technologies. In addition, an outlook on the disruptive effect of generative AI on AI tutoring systems in Industry 4.0 is given.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 50-57 | DOI 10.30844/I4SE.24.5.50
Pathways to Responsible Use of AI at Work

Pathways to Responsible Use of AI at Work

An organizational change perspective
Valentin Langholf ORCID Icon, Uta Wilkens ORCID Icon, Daniel Lupp ORCID Icon, Niklas Obermann ORCID Icon
The integration of AI in Industry 4.0 is steadily increasing. Applications include both single-purpose and generative AI systems in operation practices as well as training approaches. In addition to the technical challenges posed by these systems, organizations need to assess, plan and support the organizational changes associated with technology integration.
Industry 4.0 Science | Volume 40 | 2024 | Edition 5 | Pages 58-66 | DOI 10.30844/I4SE.24.5.58
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.
Sustainable Food Supply Chains through Artificial Intelligence

Sustainable Food Supply Chains through Artificial Intelligence

A conceptual visualization to promote animal welfare and food quality
Corinna Köters ORCID Icon, Maik Schürmeyer, Alexander Prange ORCID Icon
For the transition to a sustainable economy to succeed in its entirety, logistics must be considered in addition to raw materials and manufactu­ring. Artificial intelligence will play a central role in improving the exchan­ge of data between the individual links in the supply chain and in regula­ting processes and costs at the various stages of production. The meat industry, with its hygienic and increasing ethical requirements for animal welfare, is set to greatly benefit from the digital revolution.
Industry 4.0 Science | Volume 40 | 2024 | Edition 1 | Pages 70-75 | DOI 10.30844/I4SE.24.1.70
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