Multi-sensor and MTConnect dataset of metal cutting anomaly in milling from laboratory and industry settings
Eunseob Kim·Ali Shakouri·Adrian Shuai Li·Mir Imtiaz Mostafiz·Zachary Van Meter·Martin Byung-Guk Jun·Elisa Bertino·Yuseop Sim
This paper presents the Multi-Sensor and MTConnect (MSM) dataset, an open-access resource for anomaly detection in computer numerical control (CNC) metal milling. The dataset integrates synchronized signals from sound sensors, accelerometers, current transformers, and MTConnect-based machine controller data, collected from both laboratory experiments and real industrial production. It covers diverse machining conditions, including normal operations, process anomalies, and tool defects. All data
