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To efficiently support ramp-up processes as well as the instruction of new employees in industrial production, increasing the integration of working and learning is one promising approach. In this context, cyber-physical systems in Industry 4.0 enable the creation of work environments with new opportunities to purposefully facilitate learning new tasks. Corresponding measures make use of the large available amount of real-time information and pre-processed production data. The informed selection of appropriate measures has already to be considered in the early planning stages of a production system. Thus, the specific suitability, effectiveness and operating efficiency of work- based learning solutions have to be quantified in advance. This requires an empirical investigation and evaluation of the particular influence in an authentic production setting. The Demonstration Factory of the RWTH Aachen Campus offers an ideal framework for this purpose. It features the real production of marketable products as well as an infrastructure tailored to experiment-based production research.
Schuh et al. (Thu,) studied this question.