科研速览 · Science Skim继续刷下去 · Keep skimming →
◆ Journal of Composite Materials2026-04-20· Materials science

Multi-objective optimization of 3D-printed PLA–carbon fiber composites using a hybrid RSM–TOPSIS framework

Vijay Chouhan, Ratnesh Kumar Raj Singh, Rajnish Mallick, Deepa Mudgal

原始摘要(英文原文)· Original abstract
Carbon-fibre reinforced PLA (PLA-CF) composites produced via Fused Deposition Modelling (FDM) offer high specific strength for semi-structural applications; however, optimizing their process parameters to balance load-bearing capacity with ductility under high-throughput conditions remains a critical challenge. This study establishes a robust multi-objective optimization framework combining Response Surface Methodology (RSM) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to tailor the fracture mechanics of PLA-CF. By systematically investigating the synergistic effects of layer height, infill density, infill pattern, and printing speed (150–250 mm/s), the analysis reveals that infill density is the dominant driver for tensile strength (48.5% contribution), while layer height governs ductility. The hybrid RSM-TOPSIS approach successfully identified a practical “sweet spot” for industrial manufacturing: a configuration of 0.25 mm layer height, 80% infill density, Line pattern, and a high printing speed of 225 mm/s. This optimal set yielded a superior mechanical synergy of 30.42 MPa ultimate tensile strength and 7.64% elongation at break. Crucially, Scanning Electron Microscopy (SEM) confirmed that these parameters induce a transition from brittle delamination to a toughening mechanism characterized by extensive fibre pull-out and matrix fibrillation. These findings provide a validated pathway for fabricating tough, structural PLA-CF components at industrially viable production speeds.
读原文 · Read the paper ↗

AI 追问PRO

登录后使用 AI 追问

讨论区

登录后参与讨论

相关论文 · Related

Multi-objective optimization of 3D-printed PLA–carbon fiber composites using a hybrid RSM–TOPSIS framework — 科研速览 Science Skim