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2019 | OriginalPaper | Chapter

Anode Quality Monitoring Using Advanced Data Analytics

Authors : Bilal Azennoud, Ameline Bernard, Vincent Bonnivard, Hervé Pedroli

Published in: Light Metals 2019

Publisher: Springer International Publishing

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Abstract

The MONSOON project is a European H2020 innovation project dedicated to optimize process industry through resources and energy efficiency. The consortium is composed of 11 partners from 7 European countries. Rio Tinto and Aluminium Dunkerque (AD) are among the industrial partners, while ProbaYes acts as Data Science experts. The MONSOON project has built a two-components platform dedicated to both development and deployment of data analytics functions, employed for AD’s Paste Plant process optimization. The carbon anodes are a key component to the electrolysis reaction. The quality of the anodes (density, composition…) directly impacts the quantity and quality of the produced aluminum. A method, based on machine learning techniques, has been developed for monitoring the quality of the produced anodes and understanding the root causes of non-quality, using real-time Paste Plant data. This article presents the approach proposed in this context, the designed tools, and the first results obtained so far.
Metadata
Title
Anode Quality Monitoring Using Advanced Data Analytics
Authors
Bilal Azennoud
Ameline Bernard
Vincent Bonnivard
Hervé Pedroli
Copyright Year
2019
DOI
https://doi.org/10.1007/978-3-030-05864-7_152

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