Process parameter influence on geometric accuracy of Nylon 12 parts manufactured by FFF

Purpose This study aims to analyze the influence of extrusion temperature, printing speed and layer thickness on dimensional accuracy, geometric deviations and surface roughness of Nylon 12 parts fabricated via fused filament fabrication (FFF). Understanding these effects is key to optimizing the process for precision engineering and biofabrication applications. Design/methodology/approach Hollow cylindrical specimens were printed under varying conditions: extrusion temperature (240°C–270°C), printing speed (40–60 mm/s) and layer thickness (0.1–0.3 mm). Dimensional deviations, roundness, circular runout, cylindricity, straightness and surface roughness were analyzed. Response surface methodology (RSM) was applied to develop predictive models, while gray relational analysis (GRA) was used to optimize process parameters. Findings Higher layer thickness and extrusion temperature increased surface roughness, while higher printing speeds worsened roundness and cylindricity but improved straightness and circular run-out. The optimal parameters identified by GRA were 40 mm/s speed, 0.1 mm layer thickness and 255 °C extrusion temperature. Originality/value This study systematically evaluates geometric deviations in Nylon 12 parts fabricated via FFF, an area with limited prior research. The combined use of RSM and GRA provides a robust approach to minimize geometric errors and enhance print quality, benefiting industries requiring high-precision polymer components, such as aerospace, biomedical engineering and mechanical manufacturing.

Authors

Institutions

Publication Details

Journal
Rapid Prototyping Journal
Published
2025-11-02
DOI
https://doi.org/10.1108/rpj-03-2025-0101
Primary Topic
Additive Manufacturing and 3D Printing Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Process parameter influence on geometric accuracy of Nylon 12 parts manufactured by FFF

Carolina Bermudo Gamboa, Sergio Martín-Béjar, José Andrés López Fernández, Fermin Bañón García
Rapid Prototyping Journal
Additive Manufacturing and 3D Printing Technologies
article

Process parameter influence on geometric accuracy of Nylon 12 parts manufactured by FFF

Carolina Bermudo Gamboa, Sergio Martín-Béjar, José Andrés López Fernández, Fermin Bañón García
article en

Abstract

Purpose This study aims to analyze the influence of extrusion temperature, printing speed and layer thickness on dimensional accuracy, geometric deviations and surface roughness of Nylon 12 parts fabricated via fused filament fabrication (FFF). Understanding these effects is key to optimizing the process for precision engineering and biofabrication applications. Design/methodology/approach Hollow cylindrical specimens were printed under varying conditions: extrusion temperature (240°C–270°C), printing speed (40–60 mm/s) and layer thickness (0.1–0.3 mm). Dimensional deviations, roundness, circular runout, cylindricity, straightness and surface roughness were analyzed. Response surface methodology (RSM) was applied to develop predictive models, while gray relational analysis (GRA) was used to optimize process parameters. Findings Higher layer thickness and extrusion temperature increased surface roughness, while higher printing speeds worsened roundness and cylindricity but improved straightness and circular run-out. The optimal parameters identified by GRA were 40 mm/s speed, 0.1 mm layer thickness and 255 °C extrusion temperature. Originality/value This study systematically evaluates geometric deviations in Nylon 12 parts fabricated via FFF, an area with limited prior research. The combined use of RSM and GRA provides a robust approach to minimize geometric errors and enhance print quality, benefiting industries requiring high-precision polymer components, such as aerospace, biomedical engineering and mechanical manufacturing.

Rapid Prototyping JournalVol. 32(1)
Universidad de Málaga (ES)
Openalex Percentile: Top 65%
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.