Synergetic infill-stress correlation (SISCO): a stress-driven infill strategy for FFF additive manufacturing

The integration of topology optimization (TO) and additive manufacturing (AM) enables lightweight structures, yet density-based TO often yields pseudo-density fields that require post-processing (e.g., thresholding and surface reconstruction) to obtain manufacturable CAD/STL models, especially for material-extrusion processes such as fused filament fabrication (FFF). This study proposes a stress-informed infill strategy, Synergetic Infill–Stress Correlation (SISCO), which keeps the external geometry unchanged and tailors internal infill via a prescribed stress-to-infill mapping derived from finite element analysis. SISCO is implemented through explicit, region-wise G-code scripting to improve traceability and reproducibility. The approach is demonstrated on a three-point-bending beam and evaluated experimentally against a non-optimized (NOP) baseline and a conventional topology-optimized (CTO) reference, fabricated under identical printer/material/process settings. SISCO significantly increased specific structural stiffness by 38.5% versus NOP and 14.2% versus CTO, while yielding a statistically non-significant ∼11% nominal increase in the yield load-to-mass ratio versus NOP. These results support the feasibility of proposed approach as an accessible and efficient pathway for fabricating mechanically efficient parts, as demonstrated for quasi-static bending.