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Authors: Ander Garcia ; Xabier Oregui ; Javier Franco and Unai Arrieta

Affiliation: Vicomtech Foundation, Basque Research and Technology Alliance (BRTA), Mikeletegi 57, 20009 Donostia-San Sebastián, Spain

Keyword(s): Cyber Physical System, Industry 4.0, Time Series, Edge Computing.

Abstract: Pushed by the Industry 4.0 paradigm, the volume of data being captured from manufacturing lines is continuously increasing. To get a deeper insight of manufacturing processes, time series data from key variables of the processes has to be captured, monitored and visualized. This implies that more data variables must be monitored and data must be captured at a higher frequency: from one value of a few key variables to values of several variables captured at frequencies of seconds. Traditional Manufacturing Execution Systems (MES) were not designed for this scenario and cannot cope with these requirements. Thus, new architectures and tools are required to merge Information Technology (IT) and Operation Technology (OT) fields. This paper proposes a lightweight architecture based on micro-services and time series data requirements to connect to manufacturing process controllers, and to capture, store, monitor and visualize relevant data about the process. Moreover, a reference implementa tion based on Open Source tools is presented and validated. (More)

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Paper citation in several formats:
Garcia, A.; Oregui, X.; Franco, J. and Arrieta, U. (2022). Edge Containerized Architecture for Manufacturing Process Time Series Data Monitoring and Visualization. In Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL; ISBN 978-989-758-612-5; ISSN 2184-9285, SciTePress, pages 145-152. DOI: 10.5220/0011574500003329

@conference{in4pl22,
author={Ander Garcia. and Xabier Oregui. and Javier Franco. and Unai Arrieta.},
title={Edge Containerized Architecture for Manufacturing Process Time Series Data Monitoring and Visualization},
booktitle={Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL},
year={2022},
pages={145-152},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011574500003329},
isbn={978-989-758-612-5},
issn={2184-9285},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Innovative Intelligent Industrial Production and Logistics - IN4PL
TI - Edge Containerized Architecture for Manufacturing Process Time Series Data Monitoring and Visualization
SN - 978-989-758-612-5
IS - 2184-9285
AU - Garcia, A.
AU - Oregui, X.
AU - Franco, J.
AU - Arrieta, U.
PY - 2022
SP - 145
EP - 152
DO - 10.5220/0011574500003329
PB - SciTePress