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Energy Optimization of Aluminum Melting Furnaces in Automotive Wheel Manufacturing Using an Artificial Intelligence Technique

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Abstract:

Aluminum melting furnaces in automotive wheel manufacturing consume substantial amounts of energy, contributing significantly to the overall carbon footprint. This study introduces a novel AI-based optimization framework that dynamically controls furnace operations, leveraging real-time process data to reduce energy consumption without compromising material quality. Experimental deployment in a production environment demonstrated energy savings of up to 18.5%, confirming the potential of AI in sustainable industrial metallurgy.

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Info:

Periodical:

Advances in Science and Technology (Volume 180)

Pages:

113-118

DOI:

https://doi.org/10.4028/p-d7IFSU

Citation:

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Online since:

July 2026

Authors:

Choosak Pornsing*, Teeraphat Inta, Shunichi Ohmori

Keywords:

Aluminum Melting, Artificial Intelligence, Automotive Manufacturing, Energy Optimization, Reinforcement Learning

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© 2026 Trans Tech Publications Ltd. All Rights Reserved

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References

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