Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring
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...
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Format: | Article |
Language: | English |
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MDPI AG
2021-06-01
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Series: | Energies |
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Online Access: | https://www.mdpi.com/1996-1073/14/12/3620 |
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author | Andre Dionisio Rocha Nelson Freitas Duarte Alemão Magno Guedes Renato Martins José Barata |
author_facet | Andre Dionisio Rocha Nelson Freitas Duarte Alemão Magno Guedes Renato Martins José Barata |
author_sort | Andre Dionisio Rocha |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-10T10:18:28Z |
format | Article |
id | doaj.art-6b4c1d2fa93548f4a006d091dea32265 |
institution | Directory Open Access Journal |
issn | 1996-1073 |
language | English |
last_indexed | 2024-03-10T10:18:28Z |
publishDate | 2021-06-01 |
publisher | MDPI AG |
record_format | Article |
series | Energies |
spelling | doaj.art-6b4c1d2fa93548f4a006d091dea322652023-11-22T00:35:46ZengMDPI AGEnergies1996-10732021-06-011412362010.3390/en14123620Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption MonitoringAndre Dionisio Rocha0Nelson Freitas1Duarte Alemão2Magno Guedes3Renato Martins4José Barata5Department of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, PortugalDepartment of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, PortugalDepartment of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, PortugalIntrosys S.A., Estrada dos 4 Castelos 67, 2950-805 Quinta do Anjo, PortugalIntrosys S.A., Estrada dos 4 Castelos 67, 2950-805 Quinta do Anjo, PortugalDepartment of Electrical and Computer Engineering, NOVA School of Science and Technology, NOVA University of Lisbon, 2829-516 Caparica, PortugalIndustrial 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.https://www.mdpi.com/1996-1073/14/12/3620Apache Kafkacyber-physical production systemsenergy efficiencyIndustry 4.0interoperabilitysmart manufacturing |
spellingShingle | Andre Dionisio Rocha Nelson Freitas Duarte Alemão Magno Guedes Renato Martins José Barata Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring Energies Apache Kafka cyber-physical production systems energy efficiency Industry 4.0 interoperability smart manufacturing |
title | Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring |
title_full | Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring |
title_fullStr | Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring |
title_full_unstemmed | Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring |
title_short | Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring |
title_sort | event driven interoperable manufacturing ecosystem for energy consumption monitoring |
topic | Apache Kafka cyber-physical production systems energy efficiency Industry 4.0 interoperability smart manufacturing |
url | https://www.mdpi.com/1996-1073/14/12/3620 |
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