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Dynamic, Adaptive Worker Allocation for the Integration of Human Factors in Cyber-Physical Production Systems

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Advances in Ergonomics of Manufacturing: Managing the Enterprise of the Future

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 490))

Abstract

In this paper an adaptive, dynamic, and individualized worker allocation method is presented. The developed method is based on individual worker information, the new flexible cyber-physical production system, and the communication between the participants of such a production system. According to a communication scenario demands of a manufacturing step and a manufacturing station are compared with employee information. This provides the basis for a decision of the worker allocation. Workers are only allocated to manufacturing stations that match their qualifications and personal characteristics. For a better integration of human factors in CPPS, the job satisfaction of each worker also has to be taken into account. Therefore a satisfaction value for each manufacturing operation and manufacturing station is defined and part of the worker information. The aim of the research is to increase the productivity in the production system and the satisfaction of each individual worker.

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References

  1. Lee, E.A.: CPS foundations. In: Design Automation Conference (ACM), pp. 737–742 (2010)

    Google Scholar 

  2. acatech: Cyber-Physical Systems. Driving Force for Innovation in Mobility, Health, Energy and Production. Munich (2011)

    Google Scholar 

  3. Broy, M., Geisberger, E.: AgendaCPS. Integrierte Forschungsagenda Cyber-Physical Systems. Springer, Berlin (2012)

    Google Scholar 

  4. Kagermann, H., Wahlster, W., Helbig, J.: Recommendations for implementing the strategic initiative INDUSTRIE 4.0. Securing the future of German manufacturing industry (2013)

    Google Scholar 

  5. Kopetz, H.: Internet of things. In: Kopetz, H. (ed.) Real-time systems, pp. 307–323. Springer, Boston (2011)

    Chapter  Google Scholar 

  6. Gelenbe, E., Wu, F.-J.: Future research on cyber-physical emergency management systems. Future Internet 5, 336 (2013)

    Article  Google Scholar 

  7. Bundesministerium für Wirtschaft und Technologie: Machine-to-Machine-Kommunikation - eine Chance für die deutsche Industrie. AG2 Kompetenznetzwerk Machine-to-Machine-Kommunikation. Berlin (2011)

    Google Scholar 

  8. Wahlster, W. (ed.): SemProM. Foundations of semantic product memories for the internet of things. Springer, Berlin (2013)

    Google Scholar 

  9. Wahlster, W.: The semantic product memory: an interactive black box for smart objects. In: Wahlster, W. (ed.) SemProM. Foundations of Semantic Product Memories for the Internet of Things, pp. 3–21. Springer, Berlin (2013)

    Google Scholar 

  10. Wahlster, W.: Semantic technologies for mass customization. In: Wahlster, W., Grallert, H.-J., Wess, S., Friedrich, H., Widenka, T. (eds.) Towards the Internet of Services: The THESEUS Research Program, pp. 3–13. Springer International Publishing, Cham (2014)

    Google Scholar 

  11. Wang, W.M., Pförtner, A., Lindow, K., Hayka, H., Stark, R.: Using ontology to support scientific interdisciplinary collaboration within joint sustainability research projects. In: Seliger, G. (ed.) Innovative Solutions. 11th Global Conference on Sustainable Manufacturing; Berlin, Germany, pp. 612–617. Universitätsverl. d. TU, Berlin, 23rd–25th Sept 2013

    Google Scholar 

  12. Horn, S., Claus, A., Neidig, J., Kiesel, B., Hansen, T., Haupert, J.: The SemProM data format. In: Wahlster, W. (ed.) SemProM. foundations of semantic product memories for the internet of things, pp. 127–148. Springer, Berlin (2013)

    Google Scholar 

  13. Horn, S., Schennerlein, B., Pförtner, A., Hansen, T.: Distributed digital product memories. In: Wahlster, W. (ed.) SemProM. Foundations of semantic product memories for the internet of things, pp. 205–219. Springer, Berlin (2013)

    Google Scholar 

  14. 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)

    Google Scholar 

  15. 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)

    Google Scholar 

  16. Picard, A.: Integriertes Werkstückinformationsmodell zur Ausprägung werkstückindividueller Fertigungszustände. Shaker, Herzogenrath (2015)

    Google Scholar 

  17. 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, pp. 947–952. Newswood Limited, San Francisco (2014)

    Google Scholar 

  18. Picard, A., Anderl, R., Schützer, K.: Controlling smart production processes using RESTful web services and federative factory data management. In: Proceedings of the 14th Asia Pacific Industrial Engineering and Management System (APIEMS). Cebu, Philippinen (2013)

    Google Scholar 

  19. 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)

    Google Scholar 

  20. Galaske, N., Anderl, R.: Approach for the development of an adaptive worker assistance system based on individualized profile data model. In: Proceedings of the 7th AHFE Conference, 27–31 July 2016 (accepted for publication)

    Google Scholar 

  21. VDI 3633-1: Simulation of systems in materials handling, logistics and production—representation of human resources in simulation models. VDI, Düsseldorf 03.100.30 (2001)

    Google Scholar 

  22. Scherf, B.: Ein Vorgehensmodell zur Personaleinsatzplanung. In: Fank, M., Scherf, B. (eds.) Handbuch Personaleinsatzplanung, pp. 15–54. Datakontext, Frechen (2005)

    Google Scholar 

  23. Zülch, G., Becker, M.: Computer-supported competence management. Evolution of industrial processes as life cycles of organizations. Comput. Ind. 58, 143–150 (2007)

    Article  Google Scholar 

  24. Khanmohammadi, S., Hajiha, A., Jassbi, J.: Individual job assignment using the qualification matrix. WSEAS Trans. Inf. Sci. Appl. 2, 480–485 (2005)

    Google Scholar 

  25. Denkena, B., Nyhuis, P., Charlin, F., Meyer, G., Winter, F.: Kompetenzorientierte Produktionsplanung. Simulationsbasierte Produktionsplanung unter Berücksichtigung von Mitarbeiterkompetenzen. wt - Werkstattstechnik online 103, 216–220 (2013)

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Integrated Design, TU Darmstadt, Otto-Berndt-Str. 2, 64287, Darmstadt, Germany

    Daniel Strang, Nadia Galaske & Reiner Anderl

Authors
  1. Daniel Strang
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  2. Nadia Galaske
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  3. Reiner Anderl
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Corresponding author

Correspondence to Daniel Strang .

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Editors and Affiliations

  1. RWTH Aachen University , Aachen, Germany

    Christopher Schlick

  2. Poznan University of Technology , Poznan, Poland

    Stefan Trzcieliński

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Strang, D., Galaske, N., Anderl, R. (2016). Dynamic, Adaptive Worker Allocation for the Integration of Human Factors in Cyber-Physical Production Systems. 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_45

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  • DOI: https://doi.org/10.1007/978-3-319-41697-7_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-41696-0

  • Online ISBN: 978-3-319-41697-7

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