Effect of additive manufacturing process parameters on the strength enhancement of carbon fiber reinforced PLA

Additive manufacturing (AM) technology has evolved considerably and its major impact on the substitution of AM products over conventional parts. Fused deposition modeling (FDM) process falls under the classifications AM technique and predominantly produces thermoplastic-based products. The existing studies have explored the performance of Carbon fiber reinforced Polylactide, the understanding of correlation between the structure and property needs to be much focused which motivates to perform this study. In the present work, Carbon fiber reinforced Polylactide was used as a filler to fabricate the tensile specimen by optimize the printing conditions includes layer thickness, infill orientation, infill density, and printing strategy. From the results it has been observed that the sample printed with 0.3 mm layer height, 45° infill orientation, 30% infill density, and cubic printing pattern provides maximum tensile strength among all other samples. The bonding force between the printing layers enhances its mechanical strength. Micro CT scanned images unveiled the surface integrity and bonding between the layers based, void distribution based on infill density and printing pattern. This study reveals the influence of processing parameters on mechanical performance of carbon fiber reinforced PLA. This parameter combination contributes on the development of lightweight structures as it has better strength with minimal material volume.

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Publication Details

Journal
Discover Applied Sciences
Published
2026-09-05
DOI
https://doi.org/10.1007/s42452-026-09468-2
Primary Topic
Additive Manufacturing and 3D Printing Technologies
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article
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Effect of additive manufacturing process parameters on the strength enhancement of carbon fiber reinforced PLA

Jambeswar Sahu, Sonam Shrivastava, S. Dinesh, Chinmaya P. Mohanty et al.
Discover Applied Sciences
Additive Manufacturing and 3D Printing Technologies
article

Effect of additive manufacturing process parameters on the strength enhancement of carbon fiber reinforced PLA

Jambeswar Sahu, Sonam Shrivastava, S. Dinesh, Chinmaya P. Mohanty, Mohanraj J.
article en

Abstract

Additive manufacturing (AM) technology has evolved considerably and its major impact on the substitution of AM products over conventional parts. Fused deposition modeling (FDM) process falls under the classifications AM technique and predominantly produces thermoplastic-based products. The existing studies have explored the performance of Carbon fiber reinforced Polylactide, the understanding of correlation between the structure and property needs to be much focused which motivates to perform this study. In the present work, Carbon fiber reinforced Polylactide was used as a filler to fabricate the tensile specimen by optimize the printing conditions includes layer thickness, infill orientation, infill density, and printing strategy. From the results it has been observed that the sample printed with 0.3 mm layer height, 45° infill orientation, 30% infill density, and cubic printing pattern provides maximum tensile strength among all other samples. The bonding force between the printing layers enhances its mechanical strength. Micro CT scanned images unveiled the surface integrity and bonding between the layers based, void distribution based on infill density and printing pattern. This study reveals the influence of processing parameters on mechanical performance of carbon fiber reinforced PLA. This parameter combination contributes on the development of lightweight structures as it has better strength with minimal material volume.

Discover Applied Sciences
Vellore Institute of Technology University (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 18%
Additive Manufacturing and 3D Printing Technologies
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Effect of additive manufacturing process parameters on the strength enhancement of carbon fiber reinforced PLA — Jambeswar Sahu, Sonam Shrivastava, et al. · Discover Applied Sciences (2026) | TGRS Research Map | TGRS