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A study on pyramid-structured LSTM for milling tool wear prediction

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Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Ahead of Print.
Accurate prediction of tool wear is critical for optimizing machining efficiency, minimizing unplanned downtime, and enabling predictive maintenance in intelligent manufacturing systems. However, developing computationally efficient models with high ...