Automated process improves vibrational cutting

Vibration cutting is used in industrial manufacturing to fabricate surface microstructures like micro-pits, fins, grooves and blazed gratings. It uses a small tool that periodically cuts into the workpiece to create such microstructures and requires precise settings to ensure the tool works properly. However, finding the right tool settings for a project is time consuming and inefficient. A method employing machine vision and hearing aims to change that.

Ma et al. developed an automated two-step method to determine proper tool settings with an accuracy of a micrometer in less than two minutes. An industrial camera is first used to assess initial tool settings. Then, a sound pickup detects the vibration signal. A threshold value for sound intensity helps determine when the tool contacts the workpiece. This is used to automatically adjust the cutting depth to within a micrometer.

The method has low requirements for sound pickup, making it suitable for noisy environments and industrial applications. It can also replace the traditional labor-intensive manual tool setting that is prone to mistakes.

“This approach offers a more efficient and cost-effective solution that can be applied across various mechanical machining processes, even with complex workpiece-tool combinations, while maintaining a low cost,” said author Peiyuan Ding.

The authors plan to continue improving the automated tool setting process. By optimizing for tool shape and vibration, they believe they can further tune the accuracy of the cutting depth. They also intend to assess the method’s use under extreme operating conditions and for other machining scenarios such as ultrasonic milling and turning.

Source: “Intelligent tool setting for vibration cutting process using machine vision and hearing,” by Zhihao Ma, Junhao Zhao, Jiahui Liu, Peiyuan Ding, Jianjian Wang, Nanotechnology and Precision Engineering (2025). The article can be accessed at https://doi.org/10.1063/10.0036059 .