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  4. Hybrid Intelligence in Production Systems and its Effects on Human Work: Insights from Four Use-Cases
 
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2024
Journal Article
Title

Hybrid Intelligence in Production Systems and its Effects on Human Work: Insights from Four Use-Cases

Abstract
Industry 4.0 has initiated a data-driven transformation of production systems. With AI applications capitalizing on the surge of data availability, their introduction is reshaping workplaces and altering work tasks and profiles around the world. As AI-driven automation of work proliferates, so does the potential for the substitution of human labor. Rather than replacing human work, the concept of hybrid intelligence seeks to combine human and artificial intelligence with the effect of increasing productivity of the overall work system. As such, the concept may prove useful to support human-friendly automation of work, i.e., automation that supports human well-being and empowerment. This requires a deeper understanding of the projected effects of different automation solutions on human workers. In this context, this paper examines possible effects of AI applications in production systems based on four use-cases of coating and machining processes, thereby focussing on the changes from the perspective of workers and the resulting human-AI interactions. The potential challenges and opportunities of the workplace transformation are discussed, specifically highlighting possible implications for the workforce.
Author(s)
Schierhorst, Nikolas J.
Rheinisch-Westfälische Technische Hochschule Aachen
Johnen, Laura
Rheinisch-Westfälische Technische Hochschule Aachen
Fimmers, Christian
Rheinisch-Westfälische Technische Hochschule Aachen
Lohrmann, Vincent
Rheinisch-Westfälische Technische Hochschule Aachen
Monnet, Josefine
Rheinisch-Westfälische Technische Hochschule Aachen
Zhang, Hanwen
Rheinisch-Westfälische Technische Hochschule Aachen
Bergs, Thomas
Rheinisch-Westfälische Technische Hochschule Aachen
Brecher, Christian
Rheinisch-Westfälische Technische Hochschule Aachen
Mertens, Alexander
Rheinisch-Westfälische Technische Hochschule Aachen
Nitsch, Verena  
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Journal
Procedia computer science  
Conference
International Conference on Industry 4.0 and Smart Manufacturing 2023  
Open Access
DOI
10.1016/j.procs.2024.02.106
Additional full text version
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Language
English
Fraunhofer-Institut für Kommunikation, Informationsverarbeitung und Ergonomie FKIE  
Keyword(s)
  • human-AI interaction

  • hybrid intelligence

  • Operator 4.0

  • production systems

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