Research on intelligent tool management system for composite component machining

To address the challenges encountered during the development of the tool management system—such as the complexity of multi-parameter tool management logic, low efficiency of internal information flow, and difficulties in integrating tool life prediction with real-world operating conditions—a data storage structure suitable for various tool types and machining parameters was designed. Laser-etched QR codes were used to transmit tool information to speed up information flow. By collecting machine tool processing data, it provided raw data support for wear prediction, and established a multi-type tool wear prediction framework. Finally, a multi-type machining tool management system integrating multi-parameter management, identification, and wear prediction is established. The system was validated using one-shot drills machined with composite material, and the system performed effectively. The average error of wear prediction function is within 15%.