A New Slicer-Based Method to Generate Infill Inspired by Sandwich-Patterns for Reduced Material Consumption

Area of Science:

• Additive Manufacturing
• Materials Science
• Mechanical Engineering

Background:

• Traditional infill patterns in fused filament fabrication (FFF) often use uniform grids, leading to material waste and anisotropic properties.
• Existing methods frequently overlook load-specific requirements, compromising structural integrity and stiffness in critical applications.
• The need for efficient, high-performance parts in additive manufacturing necessitates innovative infill strategies.

Purpose of the Study:

• To introduce a novel, geometry-aware infill method for FFF that optimizes material usage and enhances part stiffness.
• To develop a corrugated infill design inspired by sandwich structures, improving load distribution and structural resilience.
• To address the anisotropic limitations of conventional infill patterns by achieving near-isotropic stiffness.

Main Methods:

• A new infill method was developed, creating an internal cavity and filling the space with continuous, adaptable corrugated extrusion paths.
• The method is geometry-aware, adapting infill based on component contours and load-bearing requirements.
• Simulations were conducted on a 10 cm³ test part to evaluate material consumption, print time, and stiffness.

Main Results:

• The novel infill method demonstrated potential reductions in material consumption by up to 77% and print time by 78%.
• Simulated parts maintained stiffness comparable to those with conventional 100% grid infill.
• The corrugated infill pattern achieved near-isotropic stiffness, improving reliability under varied load orientations.

Conclusions:

• The geometry-aware, corrugated infill strategy offers significant material and time savings in additive manufacturing.
• This method enhances structural resilience and provides balanced stiffness for complex geometries, improving mechanical load reliability.
• The approach integrates with slicer software, simplifying advanced stiffness optimization without complex analysis tools.