Tool Coating is a method for enhancing cutting efficiency and extending tool life, essential for machining hard materials. While Polycrystalline Cubic Boron Nitride (PcBN) tools are already well-suited for harsh machining conditions, their durability can be further improved with coatings. However, as the machining operation continues, tool coating loss occurs, reducing the durability of the tool and leading to further, more significant damage. Extensive research has been carried out for significant tool damage like flank wear or crater wear; however, early-stage tool damage is still relatively under-researched. This study proposes a method for real-time detection of initial tool damage during milling using an Acoustic Emission sensor whose high sensitivity makes it especially suitable for detecting minor changes to the milling process. The proposed method is based on Dynamic Time Warping (DTW), a technique that has been shown to be extremely powerful for analyzing time-series data, yet its application to acoustic emission signals remains underexplored. As verification, accelerometer data from the same experiments were analyzed and compared to the acoustic emission results. The findings suggest that the proposed approach enables the Effective monitoring of early tool degradation, providing a method for predictive maintenance and improving tool life management.
Sridhar et al. (Thu,) studied this question.
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