Regression-Based Prediction of Surface Microgeometry in Biopolymers Processed for Dental Applications

Area of Science:

• Biomaterials Engineering
• Manufacturing Processes
• Dental Prosthetics

Background:

• Dental prosthetic manufacturing requires high precision and surface quality.
• Biopolymer materials offer advantages but present milling challenges.
• Current CAD/CAM procedures need optimization for efficiency and accuracy.

Purpose of the Study:

• To investigate the impact of cutting parameters on the surface roughness of milled biopolymer dental components.
• To identify optimal machining conditions for improved surface quality and process efficiency.
• To provide data for enhancing computer-aided design and computer-aided manufacturing (CAD/CAM) in dentistry.

Main Methods:

• A full factorial design of experiments (DoE) was employed.
• Experiments systematically varied cutting speed, feed per tooth, and cutting depth.
• Surface roughness (Ra values) was measured and analyzed.

Main Results:

• Feed per tooth was identified as the most critical parameter influencing surface roughness.
• Optimized cutting conditions significantly reduced surface roughness compared to standard settings.
• Improved surface quality leads to reduced post-processing and increased manufacturing efficiency.

Conclusions:

• Machining parameter optimization is crucial for producing high-quality biopolymer dental prosthetics.
• Specific adjustments to feed per tooth can dramatically enhance surface finish.
• This research supports the development of more efficient and reproducible CAD/CAM dental manufacturing.