An Approach on Simplifying the Commissioning of Collaborative Assembly Workstations Based on Product-Lifecycle-Management and Intuitive Robot Programming

  • Werner Herfs
  • Simon Storms
  • Oliver PetrovicEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 903)


Today’s trends in the manufacturing industry lead to shorter product- lifecycles and smaller batch sizes with an increasing number of variants in the product range. These trends make it increasingly difficult to implement fully automated production processes economically. One approach that nevertheless makes the advantages of process automation accessible is partial automation through the application of human-robot collaboration (HRC). Small and medium-sized companies, in particular, lack the necessary expertise to successfully implement this technology. Standardized planning systems can bridge these competence gaps. This paper presents a system of this kind. The combination of product-lifecycle-management with collaboration-specific process planning significantly simplifies the commissioning of HRC-processes in dynamic process environments. In addition, a graphical user-interface, makes robot programming more intuitive in order to avoid the tedious training of code-based robot programming.


Human-robot-collaboration Product-lifecycle-management Intuitive robot programming Assembly planning 


  1. 1.
    Storms, S., Roggendorf, S., Stamer, F., Obdenbusch, M., Brecher, C.: PLM supported automated process planning and partitioning for collaborative assembly processes based on a capability analysis. In: 7th WGP-Jahreskongress Aachen, pp. 241–249 (2017)Google Scholar
  2. 2.
    Finkemeyer, B.: Towards safe human-robot collaboration. In: 22nd International Conference on Methods and Models in Automation and Robotics, pp. 883–888. IEEE Press, New York (2017)Google Scholar
  3. 3.
    Brecher, C., Storms, S., Ecker, C.: An approach to reduce commissioning and ramp-up time for multi-variant production in automated production facilities. In: 3rd International Conference on Ramp-up Management (ICRM). Procedia CIRP 51, 128–133 (2016)CrossRefGoogle Scholar
  4. 4.
    Doltsinis, S., Ferreira, P., Lohse, N.: A symbiotic human–machine learning approach for production ramp-up. IEEE Trans. Hum.-Mach. Syst. 48(3), 229–240 (2018)CrossRefGoogle Scholar
  5. 5.
    Franka Emika GmbH: User Manual: Panda Research. Munich (2018)Google Scholar
  6. 6.
    Do, H.M., Kim, H.-S., Park, D.I., Choi, T.Y., Park, C.: User-friendly teaching tool for a robot manipulator in human robot collaboration. In: 14th International Conference on Ubiquitous Robots and Ambient Intelligence, pp. 751–752. IEEE Press, New York (2017)Google Scholar
  7. 7.
    DIN ISO/TS 15066:2016: Robots and robotic devices - Collaborative robotsGoogle Scholar
  8. 8.
    Zhu, H., Gabler, V., Wollherr, D.: Legible action selection in human-robot collaboration. In: 26th IEEE International Symposium on Robot and Human Interactive Communication, pp. 354–359. IEEE Press, New York (2017)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Laboratory for Machine Tools and Production Engineering (WZL), Chair of Machine ToolsRWTH Aachen UniversityAachenGermany

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