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Human-Machine Cooperation in Self-organized Production Systems: A Point of View

  • Quentin BerdalEmail author
  • Marie-Pierre Pacaux-Lemoine
  • Damien Trentesaux
  • Christine Chauvin
Conference paper
Part of the Studies in Computational Intelligence book series (SCI, volume 803)

Abstract

In the context of Industry 4.0, numerous technologies are developed as well as new paradigms, causing a rupture with historical production control models. This highlights the needs for new approaches aiming to deploy efficiently these new technologies and paradigms within future industrial systems. On the other hand, human-machine system approaches encourage the cooperation between humans and complex artificial systems to react to unexpected events and to ensure an efficient supervision of these artificial systems. The paper focuses on the design of self-organized production systems cooperating with the humans. A literature review is provided based on two views dealing with such a design: a technical and a human-machine system one. Limits and advantages of both views are presented. A merged view, based on the use of the cognitive work analysis (CWA) approach, is then proposed to ensure an efficient cooperation between the human and a self-organized production system. The proposals will be applied to different systems, namely a cobot, a swarm of autonomous AGV and a set of intelligent products.

Keywords

Techno-centred design Human-machine cooperation Human-centred design Intelligent manufacturing system Self-organized production system Industry 4.0 Cognitive work analysis 

Notes

Acknowledgement

This paper was carried out in the context of the HUMANISM ANR-17-CE10-0009 research program, funded by the ANR “Agence Nationale de la Recherche”, and by the SUCRÉ project. The work presented in this paper is also partly funded by the Regional Council of the French Region “Hauts-de-France” and supported by the GRAISYHM program. The authors gratefully acknowledge these institutions.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Quentin Berdal
    • 1
    Email author
  • Marie-Pierre Pacaux-Lemoine
    • 1
  • Damien Trentesaux
    • 1
  • Christine Chauvin
    • 2
  1. 1.LAMIH - CNRS UMR 8201University of ValenciennesValenciennesFrance
  2. 2.Lab-STICC - CNRS UMR 6285University of South BrittanyLorientFrance

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