Constantly changing assembly tasks and reduced production cycles increase the risk of cognitive stress of operators. A large number of digital assistance systems implemented in assembly lines contribute to operator’s stress reduction. However, small and medium sized companies confront major challenges in implementing digital assistance solutions due to high investment costs and high customization effort. In addition, technological risks are mainly summarized as i) choosing the right assistance system, ii) realizing suitable interfaces within the in-house IT landscape for machine-to-machine and machine-to-human communication and iii) creating assembly instructions and configuring data systems in terms of supplying specific and adaptable information. Considering the aforementioned challenges and related technological risks, this paper presents a concept for automated data-driven reconfiguration of digital assistance systems. We discuss its impact on certain use cases defined in the TU Wien Pilot Factory Industry 4.0. Finally, we outline learning design principles for students and industrial stakeholders to implement automated reconfigurable digital assistance systems.
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