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April 1, 2026Journal of Polymer Science2 citationsOpen Access

Optimization of Flexural Strength of PLA Flexural Test Specimens Produced by FDM Using Taguchi L27 Orthogonal Array and Hybrid Regression Model

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MGMehmet Sah GultekinCÖCüneyt Özdemir

Key Points

  • The aim is to optimize the flexural strength of PLA specimens produced by FDM by investigating key process parameters.
  • Analyzed five key factors: printing speed, infill density, layer height, wall thickness, and nozzle temperature.
  • Employed a Taguchi L27 orthogonal array to capture nonlinear effects and parameter interactions.
  • Used analysis of variance (ANOVA) and signal-to-noise (S/N) ratios for data analysis.
  • Developed a regression model to describe relationships between parameters and flexural strength.
  • Wall thickness and layer height were identified as the most influential parameters.
  • Printing speed and infill density had a smaller impact on flexural strength.
  • The regression model achieved an R² of 98.22%, indicating a strong fit.
  • Residual analyses confirmed the model's reliability and absence of overfitting.

Abstract

ABSTRACT Fused Deposition Modeling (FDM) enables manufacturing of complex geometries, but flexural strength of printed parts is highly sensitive to process parameters. This study investigated five key factors—printing speed (PS: 100–150 mm/s), infill density (ID: 50–100%), layer height (LH: 0.20–0.30 mm), wall thickness (WT: 0.8–1.6 mm), and nozzle temperature (NT: 175°C–225°C)—to optimize the flexural strength of PLA specimens. A Taguchi L27 orthogonal array was employed to capture nonlinear effects and parameter interactions more comprehensively than standard designs. Experimental results were analyzed using analysis of variance (ANOVA) and signal‐to‐noise (S/N) ratios. The study found WT and LH to be the most influential parameters, while PS and ID had smaller impacts on flexural strength. Additionally, a regression model was developed to describe the relationship between process parameters and mechanical performance, achieving R 2 = 98.22%, adjusted R 2 = 97.11%, and predicted R 2 = 94.94%. Residual analyses confirmed the model's reliability and absence of overfitting. The optimal parameter combinations identified offer practical guidelines for enhancing flexural strength and reducing variability in FDM‐produced PLA components, supporting efficient and predictable part fabrication.

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Cite This Study

Gultekin et al. (2026) studied this question.

synapsesocial.com/papers/69cd7b345652765b073a9033https://doi.org/10.1002/pola.70116
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