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About

Xujing Yang is a leading researcher in advanced manufacturing, specializing in the high-precision robotic machining of composite materials. Her work focuses on the critical challenge of chatter detection and suppression in high-speed robotic milling, particularly for carbon fiber reinforced polymer (CFRP) composites—materials notorious for their machining difficulty. Yang’s major contributions lie in pioneering the use of acoustic emission (AE) techniques for real-time process monitoring. Her highly cited 2022 paper, "Chatter Detection and Identification in High-Efficient Robotic Milling CFRP Composites Using Acoustic Emission Technique," has garnered 35 citations, establishing a foundational methodology for identifying unstable cutting conditions. Complementing this, her 2021 study on chatter stability prediction and detection (31 citations) provides a robust framework for preemptive process control. Most recently, Yang advanced the field by introducing wavelet energy entropy of AE signals for online vibration detection (2024), demonstrating her ongoing innovation in signal processing for manufacturing. Her work directly enhances the efficiency, surface quality, and tool life in automated composite machining, making her a key figure in bridging intelligent sensing with robotic manufacturing.