Flank wear
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Machine Learning-Driven Force Analysis for Tool Wear Prediction Systems
Abstract: A system designed to forecast tool wear by utilizing a force sensor to monitor the wear of the tool's flank and applying a Convolutional Neural Network (CNN) for forecasting purposes. The methodology is demonstrated through experiments in milling, utilizing dry machining with a ball endmill on a stainless-steel component. The flank wear of the tool is directly assessed using a digital microscope throughout the operation. The forecasts produced by the …
Published in Journal of Mechatronics and Automation · Vol. 11, Issue 3, 2024 · pp. 16–25 Read article
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Minimum Energy Criteria for Machining to Determine Energy-Productivity Relationship
Abstract: In this research segment, cutting rates were changed while depth of cut and feed rate remained fixed. The results of cutting using a standard uncoated carbide insert were compared. Cutting speeds were maintained at a constant. After determining the optimal cutting condition for the equipment and material. To determine optimal tool life and cutting speed, turning operations were performed. In industrial cutting operations, flank wear reduces tool life. For single-point, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 4, 2023 · pp. 81–94 Read article