Processing Optimization of Shear Thickening Fluid Assisted Micro-Ultrasonic Machining Method for Hemispherical Mold...

Area of Science:

• Materials Science and Engineering
• Mechanical Engineering
• Nanotechnology

Background:

• Surface roughness of silicon micro-hemisphere concave molds (CMs) critically impacts Micro-Electro-Mechanical Systems (MEMS) hemispherical resonant gyroscope performance.
• Existing machining methods require improvement to achieve the necessary precision for advanced gyroscope applications.

Purpose of the Study:

• To develop and optimize a novel polishing method for reducing surface roughness in micro-CMs.
• To enhance the performance of MEMS hemispherical resonant gyroscopes through improved mold surface quality.

Main Methods:

• A hybrid polishing technique combining shear thickening fluids (STFs) with micro-ultrasonic machining (MUM) was developed.
• A Categorical Boosting (CatBoost)-genetic algorithm (GA) model was employed to optimize the STF-MUM processing parameters.
• Experimental validation was conducted using five independent repeated experiments to verify the model's effectiveness.

Main Results:

• The proposed STF-MUM method, optimized by the CatBoost-GA model, achieved a significant reduction in micro-CM surface roughness.
• The optimized process resulted in a maximum absolute error of 7.21% and an average absolute error of 4.69%.
• Surface roughness was reduced by up to 28.72% compared to unoptimized experimental results.

Conclusions:

• The STF-MUM polishing method, coupled with CatBoost-GA optimization, offers a highly effective approach for improving micro-CM surface quality.
• This advancement holds significant potential for enhancing the precision and reliability of MEMS hemispherical resonant gyroscopes in critical applications.