Surface Quality Improvement for Ultrasonic-Assisted Inner Diameter Sawing with Six-Axis Force Sensors

Area of Science:

• Materials Science
• Mechanical Engineering
• Manufacturing Processes

Background:

• Ultrasonic-assisted inner diameter machining is crucial for hard and brittle materials.
• Sawing force significantly impacts surface quality and tool life in this process.

Purpose of the Study:

• To establish a theoretical model for cutting forces in ultrasonic-assisted inner diameter sawing.
• To improve surface quality and processing efficiency through accurate force prediction.

Main Methods:

• Developed a theoretical model based on indentation fracture mechanics.
• Conducted cutting experiments on alumina ceramics using a six-axis force sensor.
• Validated the model by comparing theoretical predictions with experimental cutting forces.

Main Results:

• The proposed ultrasonic-assisted cutting force model demonstrated higher accuracy.
• Force prediction error was reduced by 5.08% (mean) and 2.56% (variance) compared to existing models.
• Surface roughness (Sa) improved from 1.534 µm to 1.129 µm.

Conclusions:

• The developed model accurately predicts sawing forces in ultrasonic-assisted machining.
• The model provides essential guidance for optimizing process parameters.
• This leads to enhanced processing efficiency and superior surface quality for hard and brittle materials.