Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/253677 
Year of Publication: 
2022
Citation: 
[Conference:] Proceedings of the 12th Conference on Learning Factories (CLF 2022), 11.-13. April 2022, Fusionopolis, Singapore [Publisher:] SSRN [Publisher:] Rochester, NY [Year:] 2022
Publisher: 
SSRN Rochester, NY
Abstract: 
The development and deployment of new technologies in industrial production impact employees' workflows and skill requirements. As the complexity of autonomous technology increases, its precise operation becomes more difficult to grasp for employees responsible for the operation, maintenance, and troubleshooting. This general problem of autonomous systems has been described in research as the 'ironies of automation'. While the need for knowledge and understanding of complex and abstract processes increases, the opportunity for direct feedback and learning is diminished. Subsequently, new challenges for training and skill development arise. Recent research has pointed to the importance of holistic process knowledge - as opposed to specific task knowledge - as an essential foundation for individual problem-solving competence. However, further research on the acquisition of problem-solving competences in an Industry 4.0 context is needed. This paper addresses this issue. We first report results from a laboratory experiment that was carried out in a learning factory, evidencing the importance of process knowledge. Based on our findings, we second develop a learning and training concept focusing on the problem-solving abilities of individuals and teams working with 'smart' self-regulating technologies. We expect that the problem-solving abilities of teams are particularly advantageous in smart, complex production settings. We discuss the validation of the concept in the learning factory that will start this year.
Subjects: 
team
problem-solving
assistance systems
experimantal study
ironies of automation
Persistent Identifier of the first edition: 
Document Type: 
Conference Paper
Document Version: 
Published Version

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