A Sensitivity Analysis-Based Parameter Optimization Framework for 3D Printing of Continuous Carbon Fiber/Epoxy...

Area of Science:

• Additive Manufacturing
• Materials Science
• Composite Materials

Background:

• Three-dimensional printing of continuous carbon fiber/epoxy composites (CCF/EPCs) is a promising additive manufacturing technology.
• The relationship between 3D printing parameters and the mechanical properties of CCF/EPCs requires further computational investigation.

Purpose of the Study:

• To develop a sensitivity analysis (SA)-based parameter optimization framework for 3D printing CCF/EPCs.
• To computationally investigate and optimize the process parameters influencing the mechanical properties of 3D printed CCF/EPCs.

Main Methods:

• Established a surrogate model using support vector regression (SVR) to link process parameters with flexural strength and modulus.
• Performed sensitivity analysis (SA) on the SVR model to determine the importance of each printing parameter.
• Predicted and experimentally verified optimal printing parameters and resulting mechanical properties.

Main Results:

• The SVR surrogate model accurately predicted the relationship between process parameters and mechanical properties.
• Sensitivity analysis identified key parameters significantly affecting the flexural strength and modulus of CCF/EPCs.
• The optimized parameters led to enhanced flexural strength and modulus in the printed samples, validated experimentally.

Conclusions:

• The proposed SA-based framework provides a high-accuracy method for optimizing 3D printing parameters in CCF/EPCs.
• This approach facilitates the advancement of additive manufacturing for high-performance fiber-reinforced polymer composites.
• The study offers a quantifiable method to improve the mechanical performance of 3D printed composite materials.