CONCEPT OF A SELF-LEARNING WORKPLACE CELL FOR WORKER ASSISTANCE WHILE COLLABORATION WITH A ROBOT WITHIN THE SELF-ADAPTING-PRODUCTION-PLANNING-SYSTEM

Johanna Ender, Jan Cetric Wagner, Georg Kunert, Fang Bin Guo, Roland Larek, Thorsten Pawletta
<span title="2019-12-15">2019</span> <i title="Politechnika Lubelska"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rouoer5jhfa6tpjpabn5rp6mdi" style="color: black;">Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska</a> </i> &nbsp;
For some time, the focus of past research on industrial workplace designs has been the optimization of processes from the technological point of view. Since human workers have to work within this environment the design process must regard Human Factor needs. The operators are under additional stress due to the range of high dynamic processes and due to the integration of robots and autonomous operating machines. There have been few studies on how Human Factors influence the design of workplaces
more &raquo; ... for Human-Robot Collaboration (HRC). Furthermore, a comprehensive, systematic and human-centred design solution for industrial workplaces particularly considering Human Factor needs within HRC is widely uncertain and a specific application with reference to production workplaces is missing. The research findings described in this paper aim the optimization of workplaces for manual production and maintenance processes with respect to the workers within HRC. In order to increase the acceptance of integration of human-robot teams, the concept of the Assisting-Industrial-Workplace-System (AIWS) was developed. As a flexible hybrid cell for HRC integrated into a Self-Adapting-Production-Planning-System (SAPPS) assists the worker while interaction.
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