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Challenges and Requirements for Improving Overall Equipment Effectiveness with Intelligent Manufacturing Technology in Special Machinery Engineering

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Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future (SOHOMA 2023)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1136))

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Abstract

This paper presents the results of a study conducted to investigate the reasons why advanced, intelligent manufacturing approaches, such as service-orientation, multi-agent systems, artificial intelligence, and digital twins, are not widely used in the field of special manufacturing machinery. The study was carried out among special machinery engineering companies, with a focus on improving availability and overall equipment effectiveness. The observations made during the study revealed several challenges and obstacles that hinder the adoption of these technologies. Based on the observations made during the study, the paper proposes a set of requirements that can facilitate the adoption of intelligent manufacturing approaches to improve the overall equipment efficiency of special manufacturing machinery in a practical manner.

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Notes

  1. 1.

    An empty run of manufacturing machines is used to finalize production without creating production waste for products already started and located on the machine but not to start the manufacturing of new ones.

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Author information

Authors and Affiliations

  1. Augsburg Technical University of Applied Sciences, Augsburg, Germany

    Christoph Legat & Thorsten Schöler

  2. Typedigital GmbH, Augsburg, Germany

    Andreas Kottre

Authors
  1. Christoph Legat
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  2. Thorsten Schöler
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  3. Andreas Kottre
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Corresponding author

Correspondence to Christoph Legat .

Editor information

Editors and Affiliations

  1. Faculty of Automatic Control and Computer Science (Automatica), University Politehnica of Bucharest, Bucharest, Romania

    Theodor Borangiu

  2. UPHF, LAMIH UMR CNRS 8201, Université Polytechnique Hauts de France, Valenciennes cedex 9, France

    Damien Trentesaux

  3. Polytechnic Institute of Bragança, Braganca, Portugal

    Paulo Leitão

  4. Polytech Annecy-Chambéry, LISTIC, Annecy, France

    Lamia Berrah

  5. SYMME, Polytech Annecy-Chambéry, Annecy, France

    Jose-Fernando Jimenez

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Legat, C., Schöler, T., Kottre, A. (2024). Challenges and Requirements for Improving Overall Equipment Effectiveness with Intelligent Manufacturing Technology in Special Machinery Engineering. In: Borangiu, T., Trentesaux, D., Leitão, P., Berrah, L., Jimenez, JF. (eds) Service Oriented, Holonic and Multi-Agent Manufacturing Systems for Industry of the Future. SOHOMA 2023. Studies in Computational Intelligence, vol 1136. Springer, Cham. https://doi.org/10.1007/978-3-031-53445-4_27

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