Issues »  Volume 47, Issue 5

Exploring the Impact of Process Parameters on Tensile Strength in Fused Deposition Modelling: A Comprehensive Study with Predictive Models

K. Zouaoui$^{1}$, S. Amroune$^{1}$, M.-S. Chebbah$^{2}$, M. Salamani$^{1}$, M. Fnides$^{3}$, A. Khaldoune$^{1}$

$^{1}$Laboratory of Materials and Mechanics of Structures, Faculty of Technology, University of M’sila, 28000 M’sila, Algeria
$^{2}$Department of Mechanical Engineering, Faculty of Technology, Mohamed Khider University of Biskra, BP 145RP, 07000 Biskra, Algeria
$^{3}$Mechanics and Structures Research Laboratory, May 8th 1945 University, 24000 Guelma, Algeria

Received: 18.05.2024; final version - 09.07.2024. Download: PDF

Fused deposition modelling or 3D printing is a frequently utilized additive manufacturing technique. This approach allows for the creation of light-weight products using various infill strategies and percentages. By adjusting parameters such as temperature, density, speed of printing, etc., components with diverse characteristics can be produced. Polylactic acid (PLA) is favoured for 3D printing due to its low cost and sustainability, being derived from renewable sources and biodegradable. Understanding the mechanical performance of different 3D-printing strategies is essential for optimizing PLA part production. This study is focused on the application of fused deposition modelling for rapid prototyping and manufacturing, particularly, focusing on the influence of extruder temperature, filling density, and weight on the tensile strength of printed PLA samples. The study is adhered to ASTM D-638 tensile standards, with 27 samples printed and tested using an Anycubic i3 Mega machine. The results reveal that extruder temperature minimally affects tensile strength, while filling density has a significant impact, and weight shows no notable effect. Additionally, two predictive models (artificial neural network (ANN) and Taguchi L9) are developed, showing favourable alignment with experimental data, with correlation coefficients reaching 91.03% for the ANN method and 80.75% for stress, 90.13% for strain, and 50.83% for Young’s modulus within the Taguchi method.

Key words: fused deposition modelling, mechanical properties, PLA, ANN, Taguchi’s method, 3D printing.

URL: https://mfint.imp.kiev.ua/en/abstract/v47/i05/0503.html

DOI: https://doi.org/10.15407/mfint.47.05.0503

PACS: 06.60.Vz, 07.05.Mh, 61.46.-w, 62.23.-c, 65.80.-g, 68.35.Gy, 81.40.Jj

Citation: K. Zouaoui, S. Amroune, M.-S. Chebbah, M. Salamani, M. Fnides, and A. Khaldoune, Exploring the Impact of Process Parameters on Tensile Strength in Fused Deposition Modelling: A Comprehensive Study with Predictive Models, Metallofiz. Noveishie Tekhnol., 47, No. 5: 503—521 (2025)

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