Unlocking Dual Utility: 1D-CNN for Milling Tool Health Assessment and Experimental Optimization

In a novel application of 1D Convolutional Neural Networks (1D-CNN), this study pioneers a tri-class classification framework for accurately forecasting the Remaining Useful Life (RUL) of milling tools. By harnessing the 1D-CNN’s innate capability to analyze raw time-series data, we elimi...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Ghazal Farhani, Srihari Kurukuri, Ryan Myers, Nelson Santos, Mohammed Tauhiduzzaman
Format:	Article
Language:	English
Published:	IEEE 2024-01-01
Subjects:	1D-CNN RUL prediction CNC machining
Online Access:	https://ieeexplore.ieee.org/document/10539970/