Fuzzy Logic and Statistical Analysis of the Compressive Strength of 3D Printed PLA and PETG Based Parts Using Fused Deposition Modeling Additive Manufacturing
Нечеткая логика и статистический анализ прочности на сжатие 3D-печатных деталей из PLA и PETG, изготовленных методом послойного наплавления
2026-06-03
SCID: 54.1/arv5963e
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Fused Deposition ModelingPETGPLAcompressive strengthfuzzy logic model
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Abstract (AI)
ABSTRACT This study investigates the compressive strength of fused deposition modeling (FDM) three-dimensional (3D) printed polylactic acid (PLA) and polyethylene terephthalate glycol (PETG) specimens manufactured using FDM additive manufacturing technique with respect to various processing parameters, such as printing speed, infill density, and nozzle temperature. This study aims to contribute to the limited body of research on compressive strength and to thoroughly examine the effects of different processing parameters on mechanical properties. Experimental data obtained under different processing conditions were used to evaluate the factors influencing compressive strength. A fuzzy logic model was developed to predict these effects, and its accuracy of the predictions was assessed using statistical methods. Fuzzy logic and analysis of variance (ANOVA) analyses were performed to determine the significance of the effects of these parameters on compressive strength. The results showed that infill density was the most influential factor, with ANOVA confirming statistical significance (p = 0.003 for PLA and <0.001 for PETG). PLA reached 81.06 MPa and PETG 52.39 MPa at 100 % infill density, whereas regression analyses achieved R² values of 82.6 % and 99.4 %. Fuzzy logic predictions yielded mean absolute errors of 3.21 % and 3.61 %, confirming the high accuracy and reliability of the proposed model.
Key Findings
1
A fuzzy logic model was developed to predict effects of printing speed, infill density, and nozzle temperature on compressive strength.
2
At 100% infill density, PLA specimens reached compressive strength of 81.06 MPa and PETG specimens reached 52.39 MPa.
3
Fuzzy logic predictions had high accuracy with mean absolute errors of 3.21% for PLA and 3.61% for PETG, supporting model reliability.
4
Infill density is the most influential processing parameter on compressive strength for both PLA and PETG, confirmed by ANOVA (p=0.003 for PLA, <0.001 for PETG).
5
Regression analyses predicting compressive strength achieved R² values of 82.6% for PLA and 99.4% for PETG.
Research Object
Fused Deposition Modeling (FDM) 3D-printed PLA and PETG specimens
Research Subject
Effects of processing parameters (printing speed, infill density, nozzle temperature) on compressive strength and prediction of compressive strength using a fuzzy logic model validated by statistical analysis (ANOVA, regression)
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2026-06-03
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