ArticlePolymers2025
Effects of Process Parameters on Tensile Properties of 3D-Printed PLA Parts Fabricated with the FDM Method.
Article in Polymers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Comparative Study of Machine Learning Models for Optimal Prediction of Printed-Line Features in Material Extrusion Additive Manufacturing.Materials (Basel, Switzerland) · 2026Article
- Mechanical Performance and Artificial Aging Behavior of Reinforced 3D-Printed PLA Structures for Drone Arm Application.Polymers · 2026Article
- Review
- Advanced additive manufacturing in orthopedics: a comprehensive review of biomaterials, structural design, biological functions and clinical technology applications.RSC advances · 2026Review
- Machine Learning for Predicting Mechanical Properties of 3D-Printed Polymers from Process Parameters: A Review.Polymers · 2026Review
- Effects of Pressurized Water Aging on Reciprocating Friction and Wear of FDM 3D-Printed PLA and Glass Fiber Reinforced PLA Composites.Polymers · 2026Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigates the influence of key fused deposition modeling (FDM) process parameters, namely, print speed, infill percentage, layer thickness, and layer width, on the tensile properties of PLA specimens produced using 3D printing technology. A Taguchi L9 orthogonal array was employed to design the experiments efficiently, enabling the systematic evaluation of parameter effects with fewer tests. Tensile strength and elongation at break were measured for each parameter combination, and statistical analyses, including the signal-to-noise (S/N) ratio and analysis of variance (ANOVA), were conducted to identify the most significant factors. The results showed that infill percentage significantly affected tensile strength, while layer thickness was the dominant factor influencing elongation. The highest tensile strength (47.84 MPa) was achieved with the parameter combination of 600 mm/s print speed, 100% infill percentage, 0.4 mm layer thickness, and 0.4 mm layer width. A linear regression model was developed to predict tensile strength with an R
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Registered trials
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