Experimental Investigation of Process Parameters on Surface and Mechanical Performance of 3D Printed Parts

Abstract This study examines the influence of print orientation and printing speed on the mechanical strength and surface roughness of components fabricated from Polylactic Acid (PLA) using the Fused Deposition Modeling (FDM) process. The 3D-printed samples were produced with varying orientations (0°, 90°, and 45°) and print speeds, while other parameters remained constant. All samples had a 100% infill density, a “Lines” infill pattern, and a printing temperature of 210°C. The 0° and 90° samples were printed at 50 mm/s, whereas the 45° samples were printed at 40, 60 and 80 mm/s. Each sample was printed three times to ensure repeatability and obtain an average result. The results indicate that raster angle plays a critical role in determining mechanical performance, with 0° and 90° orientations yielding the highest 72.31 MPa and lowest 56.26 MPa stress values, respectively. Additionally, a nuanced relationship was observed between printing speed, surface roughness, and tensile strength. Surface roughness metrics, including Ra, Rz, and Rq, improved with decreasing printing speed, indicating enhanced surface finishes. The optimal tensile strength of 57.95 MPa was achieved at a moderate printing speed of 60 mm/s, offering the best balance between mechanical strength and surface quality. This research enhances the understanding of parameter optimisation in FDM processes, providing practical insights for the production of high-performance PLA-based components.

Authors

Institutions

Publication Details

Journal
Advances in Materials Science
Published
2025-12-01
DOI
https://doi.org/10.2478/adms-2025-0020
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Experimental Investigation of Process Parameters on Surface and Mechanical Performance of 3D Printed Parts

Gazel Abilezova, Fuad Khoshnaw, Yacine Halouane, Omprakash Varma Etrouth
Advances in Materials Science
Additive Manufacturing and 3D Printing Technologies
article

Experimental Investigation of Process Parameters on Surface and Mechanical Performance of 3D Printed Parts

Gazel Abilezova, Fuad Khoshnaw, Yacine Halouane, Omprakash Varma Etrouth
article en

Abstract

Abstract This study examines the influence of print orientation and printing speed on the mechanical strength and surface roughness of components fabricated from Polylactic Acid (PLA) using the Fused Deposition Modeling (FDM) process. The 3D-printed samples were produced with varying orientations (0°, 90°, and 45°) and print speeds, while other parameters remained constant. All samples had a 100% infill density, a “Lines” infill pattern, and a printing temperature of 210°C. The 0° and 90° samples were printed at 50 mm/s, whereas the 45° samples were printed at 40, 60 and 80 mm/s. Each sample was printed three times to ensure repeatability and obtain an average result. The results indicate that raster angle plays a critical role in determining mechanical performance, with 0° and 90° orientations yielding the highest 72.31 MPa and lowest 56.26 MPa stress values, respectively. Additionally, a nuanced relationship was observed between printing speed, surface roughness, and tensile strength. Surface roughness metrics, including Ra, Rz, and Rq, improved with decreasing printing speed, indicating enhanced surface finishes. The optimal tensile strength of 57.95 MPa was achieved at a moderate printing speed of 60 mm/s, offering the best balance between mechanical strength and surface quality. This research enhances the understanding of parameter optimisation in FDM processes, providing practical insights for the production of high-performance PLA-based components.

Advances in Materials ScienceVol. 25(4)
Satbayev University (KZ), De Montfort University (GB)
De Montfort University
Openalex Percentile: Top 43%
Additive Manufacturing and 3D Printing Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.