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<p>Most of the functional parts in automobiles, aerospace, and healthcare devices undergo fatigue stress. The polyethylene terephthalate glycol (PETG) has stronger interlayer adhesion than polylactic acid (PLA) and less warping than acrylonitrile butadiene styrene (ABS) during FDM printing, thus making it highly suitable material for load-bearing applications under cyclic stresses. In the proposed work, the synergetic effect of significant process parameters, i.e., layer thickness, infill density, infill pattern, and nozzle temperature of fused deposition modeling (FDM) printing, has been investigated to enhance the fatigue strength of PETG parts. A total of 24 different configuration of input parameters was obtained with a central composite design (CCD), and samples were fabricated in accordance with ASTM D638 Type IV geometry. Fatigue tests using&#xa0;ASTM D7719-22&#xa0;test method&#xa0;were conducted via&#xa0;a Biss Nano servo-hydraulic machine under tension–tension cyclic loading at 1&#xa0;Hz with four to six replicates per standard ensuring statistical reliability. Finite element analysis (FEA) has been performed to validate stress distribution and correlate the experimental fatigue behavior with numerical stress distribution. Design-driven mathematical model based on response surface methodology (RSM) to find significant parametric effect and a data-driven neural network model based on artificial neural network (ANN) has been designed. Further, ANN with an R<sup>2</sup> of 0.9986 integrated with genetic algorithm (GA-ANN) enhanced the fatigue strength from 11.34 to 11.635&#xa0;MPa with optimized process parameters including layer thickness of 0.299&#xa0;mm, low infill density of 30.02%, moderate nozzle temperature of 244&#xa0;°C, and the triangular infill pattern.</p> Graphical Abstract <p></p>

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Design- and Data-Driven Approach with FEA Framework to Enhance the Tensile–Tensile Fatigue Strength of FDM-Fabricated PETG Components

  • 期刊论文

  • 发表日期：

    2026年5月6日

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  • Vipin Kashyap,
  • Deepak Bhardwaj,
  • Ravinder Gwal,
  • Ravinder Kumar Sahdev,
  • Ashwani Kumar Dhingra,
  • Deepak Chhabra

摘要

Most of the functional parts in automobiles, aerospace, and healthcare devices undergo fatigue stress. The polyethylene terephthalate glycol (PETG) has stronger interlayer adhesion than polylactic acid (PLA) and less warping than acrylonitrile butadiene styrene (ABS) during FDM printing, thus making it highly suitable material for load-bearing applications under cyclic stresses. In the proposed work, the synergetic effect of significant process parameters, i.e., layer thickness, infill density, infill pattern, and nozzle temperature of fused deposition modeling (FDM) printing, has been investigated to enhance the fatigue strength of PETG parts. A total of 24 different configuration of input parameters was obtained with a central composite design (CCD), and samples were fabricated in accordance with ASTM D638 Type IV geometry. Fatigue tests using ASTM D7719-22 test method were conducted via a Biss Nano servo-hydraulic machine under tension–tension cyclic loading at 1 Hz with four to six replicates per standard ensuring statistical reliability. Finite element analysis (FEA) has been performed to validate stress distribution and correlate the experimental fatigue behavior with numerical stress distribution. Design-driven mathematical model based on response surface methodology (RSM) to find significant parametric effect and a data-driven neural network model based on artificial neural network (ANN) has been designed. Further, ANN with an R2 of 0.9986 integrated with genetic algorithm (GA-ANN) enhanced the fatigue strength from 11.34 to 11.635 MPa with optimized process parameters including layer thickness of 0.299 mm, low infill density of 30.02%, moderate nozzle temperature of 244 °C, and the triangular infill pattern.

Graphical Abstract