The contamination of aluminium streams during the different life cycle stages by alloy mixing and/or accumulation of foreign elements, in combination with the limited melt purification options during remelting, represents an important limiting factor in recycling. Consequently, in secondary aluminium production, primary aluminium is used to dilute the concentration of the residual elements, and alloying elements are added to adjust the composition to the target alloy specifications. However, adding elements, for which their refinement in a subsequent recycling step is problematic, results in permanent down-cycling or ‘quality losses’. Hence, it is crucial to more efficiently control the composition of the metal streams prior to remelting. This article focuses on the aluminium cascade recycling chain and presents a Monte Carlo-based decision-support tool aiming to: i) identify all feasible clustering solutions per case based on input/output analysis; ii) quantify their environmental effect, and analyze the trade-offs; iii) consider scrap composition uncertainty/variability. Results reveal that primary resource additions can be minimized by optimizing metal sorting, and thus closing the recycling loop more effectively. Case studies are presented to illustrate the different functions of the tool, including examination of the Pareto front, and evaluation of the ‘recyclability’ of a scrap stream or a sorting solution into different alloy systems.

Paraskevas, D., Ingarao, G., Deng, Y., Duflou, J.R., Pontikes, Y., Blanpain, B. (2019). Evaluating the material resource efficiency of secondary aluminium production: A Monte Carlo-based decision-support tool. JOURNAL OF CLEANER PRODUCTION, 215, 488-496 [10.1016/j.jclepro.2019.01.097].

Evaluating the material resource efficiency of secondary aluminium production: A Monte Carlo-based decision-support tool

Ingarao, Giuseppe;
2019-01-01

Abstract

The contamination of aluminium streams during the different life cycle stages by alloy mixing and/or accumulation of foreign elements, in combination with the limited melt purification options during remelting, represents an important limiting factor in recycling. Consequently, in secondary aluminium production, primary aluminium is used to dilute the concentration of the residual elements, and alloying elements are added to adjust the composition to the target alloy specifications. However, adding elements, for which their refinement in a subsequent recycling step is problematic, results in permanent down-cycling or ‘quality losses’. Hence, it is crucial to more efficiently control the composition of the metal streams prior to remelting. This article focuses on the aluminium cascade recycling chain and presents a Monte Carlo-based decision-support tool aiming to: i) identify all feasible clustering solutions per case based on input/output analysis; ii) quantify their environmental effect, and analyze the trade-offs; iii) consider scrap composition uncertainty/variability. Results reveal that primary resource additions can be minimized by optimizing metal sorting, and thus closing the recycling loop more effectively. Case studies are presented to illustrate the different functions of the tool, including examination of the Pareto front, and evaluation of the ‘recyclability’ of a scrap stream or a sorting solution into different alloy systems.
2019
Paraskevas, D., Ingarao, G., Deng, Y., Duflou, J.R., Pontikes, Y., Blanpain, B. (2019). Evaluating the material resource efficiency of secondary aluminium production: A Monte Carlo-based decision-support tool. JOURNAL OF CLEANER PRODUCTION, 215, 488-496 [10.1016/j.jclepro.2019.01.097].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/347242
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