Requirements for an Incentive-Based Assistance System for Manual Assembly

Conference paper
Part of the Lecture Notes in Logistics book series (LNLO)


The customization of products and variable market demands result in increasing product varieties and smaller product volumes. As full automation of such processes is not cost-effective yet, the assembly and inspection are often performed at manual workstations. As a consequence, assembly workers have to manage complex assembly processes with a wide diversity of assembly components and varying assembly steps. This increases the need for individual assistance in modern assembly systems. So far, assistance mainly focuses on some process-related aspects of assembly processes, while system acceptance, motivational aspects and individual support needs of the worker are not considered. Therefore, based on theoretical discussions and expert interviews, this paper defines requirements for human-centered assistance systems that combine individual assistance with incentive systems. In a case study, the obtained requirements for incentive-based assistance systems are applied to a modeled assembly process of an extruder for a 3D printer. Finally, general implications and dependencies of the requirements on manual assembly are discussed.


Assistance systems Manual assembly Requirements definition Operator 4.0 Incentive-based assistance Industry 4.0 



The authors would like to thank the European Regional Development Fund (EFRE) and the Bremer Aufbau-Bank (BAB) for their support within the project AxIoM - Gamified AI assistance system for support of manual assembly processes (funding code: FUE0619B).


  1. 1.
    Zäh, M.F., Beetz, M., Shea, K., Reinhart, G., Bender, K., Lau, C., Ostgathe, M., Vogl, W., Wiesbeck, M., Engelhard, M., Ertelt, C., Rühr, T., Friedrich, M., Herle, S.: The cognitive factory. In: Changeable and Reconfigurable Manufacturing Systems, pp. 355–371. Springer, London (2007)Google Scholar
  2. 2.
    Zhang, Z.: Manufacturing complexity and its measurement based on entropy models. Int. J. Adv. Manuf. Technol. 62, 867–873 (2012). Scholar
  3. 3.
    Stecken, J., Linsinger, M., Sudhoff, M., Kuhlenkötter, B.: Didactic concept for increasing acceptance of consistent data standards using the example of assistance systems in assembly. Procedia Manuf. 31, 277–282 (2019). Scholar
  4. 4.
    Koren, Y.: The Global Manufacturing Revolution: Product-Process-Business Integration and Reconfigurable Systems. Wiley, Hoboken (2010)CrossRefGoogle Scholar
  5. 5.
    Müller, R., Vette-Steinkamp, M., Hörauf, L., Speicher, C., Bashir, A.: Worker centered cognitive assistance for dynamically created repairing jobs in rework area. Procedia CIRP 72, 141–146 (2018). Scholar
  6. 6.
    Andolfatto, L., Thiébaut, F., Lartigue, C., Douilly, M.: Quality- and cost-driven assembly technique selection and geometrical tolerance allocation for mechanical structure assembly. J. Manuf. Syst. 33, 103–115 (2014). Scholar
  7. 7.
    ElMaraghy, H., ElMaraghy, W.: Smart adaptable assembly systems. Procedia CIRP 44, 4–13 (2016). Scholar
  8. 8.
    Peruzzini, M., Grandi, F., Pellicciari, M.: Exploring the potential of Operator 4.0 interface and monitoring. Comput. Ind. Eng. 105600 (2018).
  9. 9.
    Lorenz, M., Rüßmann, M., Strack, R., Lueth, K.L., Bolle, M.: Man and machine in Industry 4.0. Bost Consult Gr 18 (2015)Google Scholar
  10. 10.
    Ruppert, T., Jaskó, S., Holczinger, T., Abonyi, J.: Enabling technologies for Operator 4.0: a survey. Appl. Sci. 8 (2018).
  11. 11.
    Romero, D., Bernus, P., Noran, O., Stahre, J., Fast-Berglund, Å.: The Operator 4.0: human cyber-physical systems & adaptive automation towards human-automation symbiosis work systems. In: IFIP Advances in Information and Communication Technology, pp. 677–686. Springer, Cham (2016)Google Scholar
  12. 12.
    Romero, D., Stahre, J., Wuest, T., Noran, O.S., Bernus, P., Fast-Berglund, Å., Gorecky, D.: Towards an Operator 4.0 typology: a human-centric perspective on the fourth industrial revolution technologies. In: International Conference on Computers & Industrial Engineering (CIE46), Tianjin, China (2016)Google Scholar
  13. 13.
    Keller, T., Bayer, C., Bausch, P., Metternich, J.: Benefit evaluation of digital assistance systems for assembly workstations. Procedia CIRP 81, 441–446 (2019). Scholar
  14. 14.
    Lampen, E., Teuber, J., Gaisbauer, F., Bär, T., Pfeiffer, T., Wachsmuth, S.: Combining simulation and augmented reality methods for enhanced worker assistance in manual assembly. Procedia CIRP 81, 588–659 (2019). Scholar
  15. 15.
    Sochor, R., Kraus, L., Merkel, L., Braunreuther, S., Reinhart, G.: Approach to increase worker acceptance of cognitive assistance systems in manual assembly. Procedia CIRP 81, 926–931 (2019). Scholar
  16. 16.
    Lotter, B., Wiendahl, H.-P.(Hrsg): Montage in der industriellen Produktion, 2 Auflage. Springer, Berlin, Heidelberg (2012)Google Scholar
  17. 17.
    Korn, O.: Context-aware assistive systems for augmented work. A framework using gamification and projection. Universität Stuttgart (2014)Google Scholar
  18. 18.
    Hinrichsen, S., Riediger, D., Unrau, A.: Assistance systems in manual assembly. In: Proceedings 6th International Conference Production Engineering and Management, 29 September–30 September 2016, in Lemgo, Germany, pp. 3–14 (2016)Google Scholar
  19. 19.
    DIN EN ISO 9421-110: Ergonomie der Mensch-Maschine-Interaktion. Teil 110: Grundsätze der Dialogestaltung, Germany, Berlin (2006)Google Scholar
  20. 20.
    Hinrichsen, S., Bendzioch, S.: How digital assistance systems improve work productivity in assembly. Adv. Intell. Syst. Comput. 781, 332–342 (2019). Scholar
  21. 21.
    Reisinger, G., Komenda, T., Hold, P., Sihn, W.: A concept towards automated data-driven reconfiguration of digital assistance systems. Procedia Manuf. 23, 99–104 (2018). Scholar
  22. 22.
    Apt, W., Bovenschulte, M., Priesack, K., Weiß, C., Hartmann, E.A.: Einsatz von digitalen Assistenzsystemen im Betrieb, Berlin (2018)Google Scholar
  23. 23.
    Schulz, V.: Nichtmaterielle Anreize als Instrument der Unternehmensführung. Deutscher Universitätsverlag (2000)Google Scholar
  24. 24.
    Van Knippenberg, D.: Work motivation and performance: a social identity perspective. Appl. Psychol. 49, 357–371 (2000). Scholar
  25. 25.
    Deterding, S., Dixon, D., Khaled, R., Nacke, L.: From game design elements to gamefulness: defining “gamification,” Zugl.: dis. Wilhelm Fink Verlag, München (2011)Google Scholar
  26. 26.
    Mekler, E.D., Brühlmann, F., Tuch, A.N., Opwis, K.: Towards understanding the effects of individual gamification elements on intrinsic motivation and performance. Comput. Hum. Behav. 71, 525–534 (2017). Scholar
  27. 27.
    Warmelink, H., Koivisto, J., Mayer, I., Vesa, M., Hamari, J.: Gamification of production and logistics operations: Status quo and future directions. J. Bus. Res. 1–10 (2018).
  28. 28.
    Pötters, P., Klöckner, I., Leyendecker, B.: Gamification in der Montage - Untersuchung von Motivations- und Performancesteigerung bei Mitarbeitern. ZWF Zeitschrift für wirtschaftlichen Fabrikbetr 112, 163–167 (2017). Scholar
  29. 29.
    VDI Verein Deutscher Ingenieure: VDI guideline 2860 - Montage- und Handhabungstechnik: Handhabungsfunktionen, Handhabungseinrichtungen; Begriffe, Definitionen, Symbole (1990)Google Scholar
  30. 30.
    Beinke, T., Freitag, M., Schamann, A., Feldmann, K.: Gamification im E-Learning in Verbindung mit individueller Spieleapplikation für die mitarbeiterorientierte Weiterbildung der Zukunft. Ind. 4.0 Manag. 2, 13–17 (2019)Google Scholar

Copyright information

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.BIBA – Bremer Institut für Produktion und Logistik GmbH at the University of BremenBremenGermany
  2. 2.Faculty of Production EngineeringUniversity of BremenBremenGermany

Personalised recommendations