E3S Web Conf.
Volume 353, 20228th International Conference on Energy and City of the Future (EVF’2021)
|Number of page(s)||6|
|Section||Energy & Management|
|Published online||29 June 2022|
Energy optimization and predictive maintenance of an asphalt plant: A case study
1 KANTENA TECHNOLOGIES, Paris 75011, France
2 ECAM-EPMI, LR2E, Quartz-Lab (EA 7393), Cergy-Pontoise 95092, France
This communication presents a real-life study dealing with energy optimization by using specific IoT devices in an industrial asphalt plant. The study is conducted by KANTENA TECHNOLOGIES. The objective is to demonstrate that collecting data from the plants is very valuable and useful for process optimization. The data recovered from sensors (IoT) allows us to develop a real-time supervision tool for the production system, in order to : (1) Monitor asphalt plant productions, (2) Track energy consumption and optimize its consumption, (3) Monitor the quality of service of the plant’s sensitive machines while offering predictive maintenance.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.