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A component-based design approach for energy flexibility in cyber-physical manufacturing systems

Author

Listed:
  • Fadi Assad

    (University of Warwick)

  • Emma J. Rushforth

    (University of Warwick)

  • Robert Harrison

    (University of Warwick)

Abstract

Energy flexibility of manufacturing systems helps to meet sustainable manufacturing requirements and is getting significant importance with rising energy prices and noticeable climate changes. Considering the need to proactively enable energy flexibility in modern manufacturing systems, this work presents a component-based design approach that aims to embed energy flexibility in the design of cyber-physical production systems. To this end, energy management using Industry 4.0 technologies (e.g., Internet of Things and Cyber-physical Systems) is compared to the literature on energy flexibility in order to evaluate to what extent the energy flexibility practice takes advantage of Industry 4.0 technologies. Another dimension is the coverage of the life cycle of the manufacturing system which guarantees its sustainable design and the ability to achieve energy flexibility by configuring the energy consumption behaviour. A data-based design approach of the energy-flexible components is proposed in the spirit of the Reference Architectural Model Industrie 4.0 (RAMI 4.0), and then it is exemplified using an electric drive (as a component) in order to show the practical applicability of the approach. The energy consumption behaviour of the component is modelled using machine learning techniques. The digital twin of the studied component is developed using Visual Components virtual engineering environment, then its energy consumption behaviour is included in the model allowing the system integrator/decision-maker to configure the component based on the energy availability/price. Finally, external services in terms of an optimisation module and a deep learning module are connected to the digital twin.

Suggested Citation

  • Fadi Assad & Emma J. Rushforth & Robert Harrison, 2025. "A component-based design approach for energy flexibility in cyber-physical manufacturing systems," Journal of Intelligent Manufacturing, Springer, vol. 36(2), pages 975-1001, February.
    • Handle: RePEc:spr:joinma:v:36:y:2025:i:2:d:10.1007_s10845-023-02280-4
    DOI: 10.1007/s10845-023-02280-4
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    References listed on IDEAS

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    1. Roberto Rocca & Paolo Rosa & Claudio Sassanelli & Luca Fumagalli & Sergio Terzi, 2020. "Integrating Virtual Reality and Digital Twin in Circular Economy Practices: A Laboratory Application Case," Sustainability, MDPI, vol. 12(6), pages 1-27, March.
    2. Chaoyang Zhang & Zhengxu Wang & Kai Ding & Felix T.S. Chan & Weixi Ji, 2020. "An energy-aware cyber physical system for energy Big data analysis and recessive production anomalies detection in discrete manufacturing workshops," International Journal of Production Research, Taylor & Francis Journals, vol. 58(23), pages 7059-7077, December.
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    5. Dmitry Ivanov & Boris Sokolov & Weiwei Chen & Alexandre Dolgui & Frank Werner & Semyon Potryasaev, 2021. "A control approach to scheduling flexibly configurable jobs with dynamic structural-logical constraints," IISE Transactions, Taylor & Francis Journals, vol. 53(1), pages 21-38, January.
    6. Fei Tao & Fangyuan Sui & Ang Liu & Qinglin Qi & Meng Zhang & Boyang Song & Zirong Guo & Stephen C.-Y. Lu & A. Y. C. Nee, 2019. "Digital twin-driven product design framework," International Journal of Production Research, Taylor & Francis Journals, vol. 57(12), pages 3935-3953, June.
    7. Jana Köberlein & Lukas Bank & Stefan Roth & Ekrem Köse & Timm Kuhlmann & Bastian Prell & Maximilian Stange & Marc Münnich & Dominik Flum & Daniel Moog & Steffen Ihlenfeldt & Alexander Sauer & Matthias, 2022. "Simulation Modeling for Energy-Flexible Manufacturing: Pitfalls and How to Avoid Them," Energies, MDPI, vol. 15(10), pages 1-25, May.
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