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Sensors 23 05431 by barathrajbabu is a document available to read on EtoBox.

The document discusses a Digital Twin (DT) driven tool condition monitoring system for the milling process, focusing on improving machining accuracy and reducing costs through real-time monitoring. It utilizes machine learning algorithms to analyze sensory data from vibrations and sounds, achieving a prediction accuracy of 91% with a Probabilistic Neural Network. The study emphasizes the significance of tool condition monitoring in manufacturing, particularly for the machining of Inconel 625, and highlights

Author
barathrajbabu
Language
EN