Abstract
For the purpose of manufacturing a high product variety in small production batches at low costs, cyber-physical production systems are being developed, in which cyber-physical systems consisting of sensors, actors, and communication interfaces are implemented in production systems. In order to facilitate a highly adaptive assembly process in cyber-physical production systems, an individualized worker assistance system is required. This has to take into account the different roles, qualifications, and personal characteristics of each individual worker. In this paper, a profile data model for the integration of individual worker information and the modeling of human aspects in cyber-physical production systems is developed. Based on the profile data model, an approach for the development of adaptive and individualized worker assistance systems is presented with the focus on shop-floor workers and foremen with operative planning tasks.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
BMBF: Zukunftsbild Industrie 4.0, https://www.bmbf.de/pub/Zukunftsbild_Industrie_40.pdf
Lee, E.A.: CPS Foundations. Design Automation Conference (ACM), pp. 737–742 (2010)
acatech: Cyber-Physical Systems. Driving Force for Innovation in Mobility, Health, Energy and Production. Munich (2011)
Kagermann, H., Wahlster, W., Helbig, J.: Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0. Securing the Future of German Manufacturing Industry (2013)
Anderl, R., Strang, D., Picard, A., Christ, A.: Integriertes Bauteildatenmodell für Industrie 4.0 - Informationsträger für cyber-physische Produktionssysteme. ZWF - Zeitschrift für wirtschaftlichen Fabrikbetrieb 109, 64–69 (2014)
Strang, D., Anderl, R.: Assembly Process driven Component Data Model in Cyber-Physical Production Systems. In: Ao, S.I., Douglas, C., Grundfest, W.S., Burgstone, J. (eds.) Lecture Notes in Engineering and Computer Science: Proceedings of the World Congress on Engineering and Computer Science 2014, pp. 947–952. Newswood Limited, San Francisco (2014)
Bader, S., Aehnelt, M.: Tracking assembly processes and providing assistance in smart factories. In: Duval, B. (ed.) Proceedings of the 6th International Conference on Agents and Artificial Intelligence, pp. 161–168. SciTePress (2014)
Galaske, N., Wagner, T., Strang, D., Anderl, R., Bruder, R.: Konzept zum Einsatz digitaler Menschmodelle in Cyber-physischen Produktionssystemen. In: GfA (ed.) Gestaltung der Arbeitswelt der Zukunft. 60. Kongress der Gesellschaft für Arbeitswissenschaft vom 12.–14. März 2014, pp. 360–362. GfA-Press, Dortmund (2014)
Spath, D. (ed.): Produktionsarbeit der Zukunft - Industrie 4.0. Fraunhofer Verlag, Stuttgart (2013)
Abele, E., Reinhart, G.: Zukunft der Produktion. Carl Hanser, München (2011)
Schuh, G., Potente, T., Thomas, C.: Design of production control’s behavior. Procedia CIRP 7, 145–150 (2013)
Senderek, R., Geisler, K.: Assistenzsysteme zur Lernunterstützung in der Industrie 4.0. In: Rathmayer, S., Pongratz, H. (eds.) Proceedings of DeLFI Workshops 2015 & 13th e-Learning Conference of the German Computer Society, pp. 36–46 (2015)
Aehnelt, M., Bader, S.: Information assistance for smart assembly stations. In: Loiseau, S. (ed.) Proceedings of the International Conference on Agents and Artificial Intelligence, pp. 143–150. SciTePress (2015)
Aehnelt, M., Bader, S.: From information assistance to cognitive automation: a smart assembly use case. In: Duval, B., van den Herik, J., Loiseau, S., Filipe, J. (eds.) Agents and Artificial Intelligence, pp. 207–222. Springer International Publishing, Cham (2015). (vol. 9494)
Alm, R., Aehnelt, M., Urban, B.: Plant@Hand. In: Matthies, D.J. (ed.) iWOAR 2015. 2nd International Workshop on Sensor-based Activity Recognition and Interaction: 25–26 June 2015, pp. 1–7. Rostock, Germany. Association for Computing Machinery Inc, New York (2015)
Kerber, F., Lessel, P.: Adaptive und gamifizierte Werkerassistenz in der (semi-)manuellen Industrie 4.0-Montage. In: Rathmayer, S., Pongratz, H. (eds.) Proceedings of DeLFI Workshops 2015 & 13th e-Learning Conference of the German Computer Society, pp. 28–35 (2015)
Picard, A., Anderl, R.: Integrated component data model for smart production planning. In: Schützer, K. (ed.) Proceedings of the 19th International Seminar on High Technology, pp. 1–6. Piracicaba, Sao Paulo (2014)
Galaske, N., Christ, A., Anderl, R.: Integration von Menschen in Smart Factories: Ein individualisierbares Profildatenmodell für Industrie 4.0. In: Krause, D., Paetzold, K., Wartzack, S. (eds.) Design for X - Beiträge zum 25. DfX-Symposium, pp. 133–144. TuTech, Hamburg (2014)
Strang, D., Galaske, N., Anderl, R.: Dynamic, adaptive worker allocation for the integration of human factors in cyber-physical production systems. In: Proceedings of the 7th AHFE Conference 27–31 July 2016 (accepted for publication) (2016)
Knoch, S., Reiplinger, M., Vierfuß, R.: Mobile staff planning support for team leaders in an industrial production scenario. In: UBICOMM 2014: The Eighth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies, pp. 44–47 (2014)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Galaske, N., Anderl, R. (2016). Approach for the Development of an Adaptive Worker Assistance System Based on an Individualized Profile Data Model. In: Schlick, C., Trzcieliński, S. (eds) Advances in Ergonomics of Manufacturing: Managing the Enterprise of the Future. Advances in Intelligent Systems and Computing, vol 490. Springer, Cham. https://doi.org/10.1007/978-3-319-41697-7_47
Download citation
DOI: https://doi.org/10.1007/978-3-319-41697-7_47
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41696-0
Online ISBN: 978-3-319-41697-7
eBook Packages: EngineeringEngineering (R0)