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This paper presents an experimental study for turning process in machining by using Takagi–Sugeno–Kang (TSK) fuzzy modeling to accomplish the integration of multi-sensor information and tool wear information. It generates fuzzy rules directly from the input–output data acquired from sensors, and provides high accuracy and high reliability of the tool wear prediction over a wide range of cutting conditions...
Because of the difficulty in understanding the physics of the machining process, several different intelligence methods, which employ cutting forces for estimation tool wear, have been developed in the past few years. Unfortunately, none of them can overcome the difficulty to estimate the errors of approximation during tool wear monitoring. This paper aimed at presenting a tool wear monitoring method...
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