Modeling of the Influence of Input AM Parameters on Dimensional Error and Form Errors in PLA Parts Printed with FFF Technology | JoVE Visualize

Modeling of the Influence of Input AM Parameters on Dimensional Error and Form Errors in PLA Parts Printed with FFF Technology

Carmelo J Luis-Pérez¹, Irene Buj-Corral², Xavier Sánchez-Casas²

¹Engineering Department, Arrosadia Campus, Public University of Navarre (UPNA), 31006 Pamplona, Spain.

Polymers|December 10, 2021

View abstract on PubMed

Summary

Optimizing 3D printing parameters for polylactic acid (PLA) hemispherical cups is crucial for minimizing dimensional errors and improving part quality. This study identifies optimal settings for nozzle diameter, temperature, layer height, print speed, and extrusion multiplier to achieve precise manufacturing outcomes.

Area of Science:

Materials Science and Engineering
Additive Manufacturing (AM)
3D Printing Process Optimization

Background:

Additive manufacturing (AM) enables complex part fabrication with porous structures efficiently.
Precise control over input parameters is essential for optimizing microgeometry, form errors, and dimensional accuracy in AM.
Previous research analyzed process parameter influence on surface roughness in fused filament fabrication (FFF).

Purpose of the Study:

To investigate the influence of process parameters on form and dimensional errors of 3D printed hemispherical cups.
To determine optimal manufacturing conditions for minimizing dimensional error, roundness, and surface roughness.
To provide guidance for enhancing the quality of 3D printed parts, particularly those resembling acetabular cups for hip prostheses.

Main Methods:

3D printing of hemispherical cups using polylactic acid (PLA).
Analysis of process variables including nozzle diameter, temperature, layer height, print speed, and extrusion multiplier.
Utilized adaptive neuro-fuzzy inference systems (ANFIS) models and a desirability function for multi-objective optimization.

Main Results:

Dimensional error, roundness, and concentricity are significantly influenced by nozzle diameter and layer height.
High nozzle diameter (0.6 mm) and layer height (0.3 mm) are identified as suboptimal.
Optimal conditions for simultaneous internal and external surface optimization include a 0.4 mm nozzle diameter, 197 °C temperature, 0.1 mm layer height, 42 mm/s print speed, and 94.8% extrusion multiplier.

Conclusions:

Nozzle diameter and layer height are critical parameters affecting dimensional accuracy and form errors in PLA 3D prints.
The study successfully determined optimal process parameters to achieve desired part quality, minimizing surface roughness and roundness while maintaining dimensional error below 0.01.
Findings offer valuable insights for manufacturers seeking to improve the precision and quality of 3D printed components through process optimization.