Estimation of Net Carbon Consumption in Aluminum Electrolysis Using Multivariate Analysis
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RESEARCH ARTICLE
Estimation of Net Carbon Consumption in Aluminum Electrolysis Using Multivariate Analysis Petre Manolescu1,2,4 · Carl Duchesne1 · Jayson Tessier3 · Gudrun Saevarsdottir4 Received: 7 August 2020 / Accepted: 22 October 2020 © The Minerals, Metals & Materials Society 2020
Abstract In the aluminum electrolysis, the amount of carbon consumed per unit of metal produced is always higher than the theoretical one. Raw material variability, anode properties, and reduction cell operation and performance can influence this discrepancy. Linking these factors to each individual anode could help close this gap thus improving the environmental footprint and reducing production cost. In today’s industrial environment, large volume of data, both structured and unstructured, are collected, otherwise known as big data. These capabilities could enable predicting the consumption for each anode as opposed to estimating it at the plant level as performed so far. This can be achieved using a tracking system to link the pot operation to individual baked and green anode properties. The performance of R&D Carbon Net Carbon Consumption formula was compared to a multivariate statistical approach that considers process data variables gathered from the aforementioned, linked, databases. Given the process data at hand, the prediction power of the net carbon consumption for individual anodes is significantly improved as opposed to using the existing model.
The contributing editor for this article was Hojong Kim. Electronic supplementary material The online version of this article (doi:https://doi.org/10.1007/s40831-020-00310-6) contains supplementary material, which is available to authorized users. * Carl Duchesne [email protected] Petre Manolescu [email protected] 1
Chemical Engineering Department, Aluminium Research Centre‑REGAL, Université Laval, Quebec, Qc G1V 0A6, Canada
2
Alcoa Corporation, Manufacturing Intelligence, Deschambault, Deschambault G0A 1S0, Canada
3
Alcoa Corporation, Smelting Center of Excellence, Deschambault, Deschambault G0A 1S0, Canada
4
School of Science and Engineering, Reykjavik University, Menntavegur 1, Nautholsvik 101, Reykjavik, Iceland
13
Vol.:(0123456789)
Journal of Sustainable Metallurgy
Graphical Abstract
Keywords Net carbon consumption · Anode tracking · Aluminum production · Big data in aluminum smelting
Introduction The aluminum industry is an important part of the Canadian economy, the country being the fourth largest producer in the world [1], with one of the lowest carbon footprints thanks to the use of hydropower. It is produced via the Hall–Héroult process where alumina is dissolved in a molten salt bath (cryolite) and a high, DC, electric current is passed between the anode and the cathode in the cell. In existing technologies, the current can be from 100 kA to over 600 kA. Both the anodic and cathodic electrodes are made of carbon, the anodes being consumable. The preferred technology uses pre-baked anodes, although continuously baking
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