Adaptive infill method for FDM based on cross-section features and transition layers
Xiaowei Meng, Ketai He, Chenlong Zhai, Yangwei Du, Zunyou LiuPurpose
This paper aims to report the implementation and initial experimental evaluation of an adaptive infill method for fused deposition modeling that combines cross-section-driven variable-density assignment with an explicit transition-layer branch triggered at detected geometric discontinuities, all operating at the slicing stage without external geometry modification or load-path input.
Design/methodology/approach
A continuous exponential mapping converts the slice-wise cross-sectional area sequence into a layer-specific infill density bounded by user-defined limits. A dual-criterion detection module identifies abrupt geometric transitions using area-change rate and centroid displacement; a sliding-window slope-exclusion rule prevents false detection on continuous gradients; densified reinforcement layers are inserted only at flagged abrupt interfaces. The two algorithmic branches were exercised separately on two test geometries – compression specimens with circular necked profiles and tensile specimens with rectangular stepped profiles – printed in polylactic acid (PLA) at 20\% baseline infill density with five specimens per group.
Findings
The adaptive group showed a marginal trend toward higher first peak force on compression specimens (5.6∼kN to 5.9∼kN, +5.4\%; Welch’s t-test, p = 0.054) and a statistically significant 15.4\% higher peak load on tensile specimens (803.2∼N to 926.8∼N; p = 0.043), with mass increases of 0.5\% and printing time increases below 7\%. A directional check with glycol-modified polyethylene terephthalate (PETG) at three specimens per group gave +14.2\% tensile peak-load difference (p = 0.0045), consistent in direction with the PLA result. Sparse-infill toolpath length differed from the uniform baseline by less than 1.5\%. The algorithm transferred without modification to three geometries of greater complexity.
Originality/value
This work presents an integrated implementation that combines an existing class of cross-section-driven variable-density assignment with an explicit transition-layer detection and reinforcement branch within a single slicing-level pipeline, together with per-layer diagnostic data that make the algorithm’s geometric decisions inspectable.