The role of people in the age of Industry 4.0

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A central problem in the implementation of Industry 4.0 is the question of the future role of humans in the production of the future. The constantly advancing digitization provides enormous amounts of data, which can be used to expand process knowledge and thus increase efficiency and quality. Intelligent systems that perform pre-processing are needed to evaluate the data volumes, as humans alone can hardly process this flood of information. This results in new or modified process flows, task areas and business models. Established workflows have to be changed and, in some cases, entirely new structures have to be created, which present employees with new challenges. The cognitive load on employees and the need to learn new content and how to use modern technologies is increasing. At the same time, there is a lack of understanding in many places about what the system actually does in the background, which means that acceptance suffers in some cases. This results in additional problems in the transfer of research results into practice.

In the research field of human-machine interaction, we are concerned with how production systems must be designed in order to ensure the most efficient and intuitive interaction possible between humans and the system, and thus to further advance the integration of humans into the digital working world. The strengths of humans, for example creativity, adaptivity, abstract thinking, should be optimally utilized and complemented and enabled by the functions of the system: Humans should pass on their creativity, their (implicit) knowledge and their experience to the system via suitable interfaces. Through an interaction with the system that is as independent of location and time as possible, information, experience and knowledge are to be shared or made available within a company, but also across domains and stakeholders. The resulting knowledge base is to be used to support people in their activities, for example assembly, commissioning, error analysis, learning processes, and decision-making by means of intelligent assistance systems. The individualization of the interaction between human and system plays an important role. Different initial situations and the respective strengths, weaknesses and preferences of the human must be taken into account. This requires the integration of user-centric human-machine interfaces into production engineering systems and the linking or merging of existing digital and physical entities - device/machine, AI, digital twin, DataBase and so on.