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Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring

Author

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  • Andre Dionisio Rocha

    (Department of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, Portugal
    UNINOVA Centre of Technology and Systems (CTS), FCT Campus, Monte de Caparica, 2829-516 Caparica, Portugal)

  • Nelson Freitas

    (Department of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, Portugal
    UNINOVA Centre of Technology and Systems (CTS), FCT Campus, Monte de Caparica, 2829-516 Caparica, Portugal)

  • Duarte Alemão

    (Department of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, Portugal
    UNINOVA Centre of Technology and Systems (CTS), FCT Campus, Monte de Caparica, 2829-516 Caparica, Portugal)

  • Magno Guedes

    (Introsys S.A., Estrada dos 4 Castelos 67, 2950-805 Quinta do Anjo, Portugal)

  • Renato Martins

    (Introsys S.A., Estrada dos 4 Castelos 67, 2950-805 Quinta do Anjo, Portugal)

  • José Barata

    (Department of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, Portugal
    UNINOVA Centre of Technology and Systems (CTS), FCT Campus, Monte de Caparica, 2829-516 Caparica, Portugal)

Abstract

Industrial environments are heterogeneous systems that create challenges of interoperability limiting the development of systems capable of working collaboratively from the point of view of machines and software. Additionally, environmental issues related to manufacturing systems have emerged during the last decades, related to sustainability problems faced in the world. Thus, the proposed work aims to present an interoperable solution based on events to reduce the complexity of integration, while creating energetic profiles for the machines to allow the optimization of their energy consumption. A publish/subscribe-based architecture is proposed, where the instantiation is based on Apache Kafka. The proposed solution was implemented in two robotic cells in the automotive industry, constituted by different hardware, which allowed testing the integration of different components. The energy consumption data was then sent to a Postgres database where a graphical interface allowed the operator to monitor the performance of each cell regarding energy consumption. The results are promising due to the system’s ability to integrate tools from different vendors and different technologies. Furthermore, it allows the possibility to use these developments to deliver more sustainable systems using more advanced solutions, such as production scheduling, to reduce energy consumption.

Suggested Citation

  • Andre Dionisio Rocha & Nelson Freitas & Duarte Alemão & Magno Guedes & Renato Martins & José Barata, 2021. "Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring," Energies, MDPI, vol. 14(12), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:12:p:3620-:d:576942
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    References listed on IDEAS

    as
    1. Andre Dionisio Rocha & Pedro Lima-Monteiro & Mafalda Parreira-Rocha & Jose Barata, 2019. "Artificial immune systems based multi-agent architecture to perform distributed diagnosis," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 2025-2037, April.
    2. Mawson, Victoria Jayne & Hughes, Ben Richard, 2021. "Optimisation of HVAC control and manufacturing schedules for the reduction of peak energy demand in the manufacturing sector," Energy, Elsevier, vol. 227(C).
    3. Müller, Julian Marius & Buliga, Oana & Voigt, Kai-Ingo, 2018. "Fortune favors the prepared: How SMEs approach business model innovations in Industry 4.0," Technological Forecasting and Social Change, Elsevier, vol. 132(C), pages 2-17.
    4. Carla Gonçalves Machado & Mats Peter Winroth & Elias Hans Dener Ribeiro da Silva, 2020. "Sustainable manufacturing in Industry 4.0: an emerging research agenda," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1462-1484, March.
    5. Xiaoxia Chen & Mélanie Despeisse & Björn Johansson, 2020. "Environmental Sustainability of Digitalization in Manufacturing: A Review," Sustainability, MDPI, vol. 12(24), pages 1-31, December.
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    Cited by:

    1. Adrian Kampa & Iwona Paprocka, 2021. "Analysis of Energy Efficient Scheduling of the Manufacturing Line with Finite Buffer Capacity and Machine Setup and Shutdown Times," Energies, MDPI, vol. 14(21), pages 1-25, November.
    2. Marina Crnjac Zizic & Marko Mladineo & Nikola Gjeldum & Luka Celent, 2022. "From Industry 4.0 towards Industry 5.0: A Review and Analysis of Paradigm Shift for the People, Organization and Technology," Energies, MDPI, vol. 15(14), pages 1-20, July.

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