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Industry 4.0: contributions of holonic manufacturing control architectures and future challenges

Author

Listed:
  • William Derigent

    (CRAN, CNRS, UMR 7039)

  • Olivier Cardin

    (LUNAM Université, Université de Nantes, LS2N UMR CNRS 6004)

  • Damien Trentesaux

    (LAMIH UMR CNRS 8201, Université Polytechnique Hauts-de-France, UPHF)

Abstract

The flexibility claimed by the next generation production systems induces a deep modification of the behaviour and the core itself of the control systems. Over-connectivity and data management abilities targeted by Industry 4.0 paradigm enable the emergence of more flexible and reactive control systems, based on the cooperation of autonomous and connected entities in the decision-making process. From most relevant articles extracted from existing literature, a list of 10 key enablers for Industry 4.0 is first presented. During the last 20 years, the holonic paradigm has become a major paradigm of Intelligent Manufacturing Systems. After the presentation of the holonic paradigm and holon properties, this article highlights how historical and current holonic control architectures can partly fulfil Industry 4.0 key enablers. The remaining unfulfilled key enablers are then the subject of an extensive discussion on the remaining research perspectives on holonic architectures needed to achieve a complete support of Industry 4.0.

Suggested Citation

  • William Derigent & Olivier Cardin & Damien Trentesaux, 2021. "Industry 4.0: contributions of holonic manufacturing control architectures and future challenges," Journal of Intelligent Manufacturing, Springer, vol. 32(7), pages 1797-1818, October.
    • Handle: RePEc:spr:joinma:v:32:y:2021:i:7:d:10.1007_s10845-020-01532-x
    DOI: 10.1007/s10845-020-01532-x
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    References listed on IDEAS

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    1. Adrià Salvador Palau & Maharshi Harshadbhai Dhada & Ajith Kumar Parlikad, 2019. "Multi-agent system architectures for collaborative prognostics," Journal of Intelligent Manufacturing, Springer, vol. 30(8), pages 2999-3013, December.
    2. Mingtao Wu & Zhengyi Song & Young B. Moon, 2019. "Detecting cyber-physical attacks in CyberManufacturing systems with machine learning methods," Journal of Intelligent Manufacturing, Springer, vol. 30(3), pages 1111-1123, March.
    3. Yongxin Liao & Fernando Deschamps & Eduardo de Freitas Rocha Loures & Luiz Felipe Pierin Ramos, 2017. "Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal," International Journal of Production Research, Taylor & Francis Journals, vol. 55(12), pages 3609-3629, June.
    4. Abderraouf Maoudj & Brahim Bouzouia & Abdelfetah Hentout & Ahmed Kouider & Redouane Toumi, 2019. "Distributed multi-agent scheduling and control system for robotic flexible assembly cells," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1629-1644, April.
    5. Yampolskiy, Mark & Horváth, Péter & Koutsoukos, Xenofon D. & Xue, Yuan & Sztipanovits, Janos, 2015. "A language for describing attacks on cyber-physical systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 8(C), pages 40-52.
    6. Herbert A. Simon, 1996. "The Sciences of the Artificial, 3rd Edition," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262691914, April.
    7. Bokrantz, Jon & Skoogh, Anders & Berlin, Cecilia & Stahre, Johan, 2017. "Maintenance in digitalised manufacturing: Delphi-based scenarios for 2030," International Journal of Production Economics, Elsevier, vol. 191(C), pages 154-169.
    8. Olivier Cardin & Damien Trentesaux & André Thomas & Pierre Castagna & Thierry Berger & Hind Bril El-Haouzi, 2017. "Coupling predictive scheduling and reactive control in manufacturing hybrid control architectures: state of the art and future challenges," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1503-1517, October.
    9. Theodor Borangiu & Silviu Răileanu & Thierry Berger & Damien Trentesaux, 2015. "Switching mode control strategy in manufacturing execution systems," International Journal of Production Research, Taylor & Francis Journals, vol. 53(7), pages 1950-1963, April.
    10. Akella, Ravi & Tang, Han & McMillin, Bruce M., 2010. "Analysis of information flow security in cyber–physical systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 3(3), pages 157-173.
    11. Ahmad E. Elhabashy & Lee J. Wells & Jaime A. Camelio & William H. Woodall, 2019. "A cyber-physical attack taxonomy for production systems: a quality control perspective," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2489-2504, August.
    12. Juha Puttonen & Andrei Lobov & Maria A. Cavia Soto & José L. Martinez Lastra, 2019. "Cloud computing as a facilitator for web service composition in factory automation," Journal of Intelligent Manufacturing, Springer, vol. 30(2), pages 687-700, February.
    13. Jose-Fernando Jimenez & Abdelghani Bekrar & Gabriel Zambrano-Rey & Damien Trentesaux & Paulo Leitão, 2017. "Pollux: a dynamic hybrid control architecture for flexible job shop systems," International Journal of Production Research, Taylor & Francis Journals, vol. 55(15), pages 4229-4247, August.
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