Effect of Printing Parameters on Dimensional Error, Surface Roughness and Porosity of FFF Printed Parts with Grid Structure

Buj-Corral, Irene; Bagheri, Ali; Sivatte-Adroer, Maurici

doi:10.3390/polym13081213

Cited by 48 publications

(38 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They have concluded that the lower the degree of orientations, the higher the accuracy, and thus the lower the angle for layer deposition. Several studies have focused on improving the dimensional accuracy of 3D-printed parts [32][33][34]. However, in order to increase the application of the FFF process, the strength and mechanical performances of the final parts need to be focused on.…”

Section: Fff Parameters and Their Impact On Part Qualitymentioning

confidence: 99%

In-Process Monitoring of Temperature Evolution during Fused Filament Fabrication: A Journey from Numerical to Experimental Approaches

Vanaei

Shirinbayan

Deligant

et al. 2021

Thermo

View full text Add to dashboard Cite

Fused filament fabrication (FFF), an additive manufacturing technique, unlocks alternative possibilities for the production of complex geometries. In this process, the layer-by-layer deposition mechanism and several heat sources make it a thermally driven process. As heat transfer plays a particular role and determines the temperature history of the merging filaments, the in-process monitoring of the temperature profile guarantees the optimization purposes and thus the improvement of interlayer adhesion. In this review, we document the role of heat transfer in bond formation. In addition, efforts have been carried out to evaluate the correlation of FFF parameters and heat transfer and their effect on part quality. The main objective of this review paper is to provide a comprehensive study on the in-process monitoring of the filament’s temperature profile by presenting and contributing a comparison through the literature.

show abstract

Section: Fff Parameters and Their Impact On Part Qualitymentioning

confidence: 99%

In-Process Monitoring of Temperature Evolution during Fused Filament Fabrication: A Journey from Numerical to Experimental Approaches

Vanaei

Shirinbayan

Deligant

et al. 2021

Thermo

View full text Add to dashboard Cite

show abstract

“…Lowest dimensional error was found in experiment three, obtained with low nozzle diameter, high temperature, low layer height, low print speed and low extrusion multiplier. In an earlier paper, higher relative dimensional errors between 0.82% and 2.60% were reported in prismatic porous samples [ 37 ]. In this present work, lower relative dimensional errors were obtained, ranging between 0.036% and 0.625%.…”

Section: Resultsmentioning

confidence: 99%

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

2021

Self Cite

View full text Add to dashboard Cite

As is widely known, additive manufacturing (AM) allows very complex parts to be manufactured with porous structures at a relatively low cost and in relatively low manufacturing times. However, it is necessary to determine in a precise way the input values that allow better results to be obtained in terms of microgeometry, form errors, and dimensional error. In an earlier work, the influence of the process parameters on surface roughness obtained in fused filament fabrication (FFF) processes was analyzed. This present study focuses on form errors as well as on dimensional error of hemispherical cups, with a similar shape to that of the acetabular cup of hip prostheses. The specimens were 3D printed in polylactic acid (PLA). Process variables are nozzle diameter, temperature, layer height, print speed, and extrusion multiplier. Their influence on roundness, concentricity, and dimensional error is considered. To do this, adaptive neuro-fuzzy inference systems (ANFIS) models were used. It was observed that dimensional error, roundness, and concentricity depend mainly on the nozzle diameter and on layer height. Moreover, high nozzle diameter of 0.6 mm and high layer height of 0.3 mm are not recommended. A desirability function was employed along with the ANFIS models in order to determine the optimal manufacturing conditions. The main aim of the multi-objective optimization study was to minimize average surface roughness (Ra) and roundness, while dimensional error was kept within the interval Dimensional Error≤0.01. When the simultaneous optimization of both the internal and the external surface of the parts is performed, it is recommended that a nozzle diameter of 0.4 mm be used, to have a temperature of 197 °C, a layer height of 0.1 mm, a print speed of 42 mm/s, and extrusion multiplier of 94.8%. This study will help to determine the influence of the process parameters on the quality of the manufactured parts.

show abstract

“…It was observed that print speed (velocity at which the print head moves during printing) does not show a significant impact on the porosity of fused deposition modeling parts (refer to Figure 5 ). This occurs due to the vibrations and errors introduced during the printing process at higher print speed (70 mm/s) led to increased porosity in parts [ 60 ].…”

Section: Resultsmentioning

confidence: 99%

Analysis and Optimization of Dimensional Accuracy and Porosity of High Impact Polystyrene Material Printed by FDM Process: PSO, JAYA, Rao, and Bald Eagle Search Algorithms

et al. 2021

View full text Add to dashboard Cite

High impact polystyrene (HIPS) material is widely used for low-strength structural applications. To ensure proper function, dimensional accuracy and porosity are at the forefront of industrial relevance. The dimensional accuracy cylindricity error (CE) and porosity of printed parts are influenced mainly by the control variables (layer thickness, shell thickness, infill density, print speed of the fused deposition modeling (FDM) process). In this study, a central composite design (CCD) matrix was used to perform experiments and analyze the complete insight information of the process (control variables influence on CE and porosity of FDM parts). Shell thickness for CE and infill density for porosity were identified as the most significant factors. Layer thickness interaction with shell thickness, infill density (except for CE), and print speed were found to be significant for both outputs. The interaction factors, i.e., shell thickness and infill density, were insignificant (negligible effect) for both outputs. The models developed produced a better fit for regression with an R2 equal to 94.56% for CE, and 99.10% for porosity, respectively. Four algorithms (bald eagle search optimization (BES), particle swarm optimization (PSO), RAO-3, and JAYA) were applied to determine optimal FDM conditions while examining six case studies (sets of weights assigned for porosity and CE) focused on minimizing both CE and porosity. BES and RAO-3 algorithms determined optimal conditions (layer thickness: 0.22 mm; shell thickness: 2 mm; infill density: 100%; print speed: 30 mm/s) at a reduced computation time equal to 0.007 s, differing from JAYA and PSO, which resulted in an experimental CE of 0.1215 mm and 2.5% of porosity in printed parts. Consequently, BES and RAO-3 algorithms are efficient tools for the optimization of FDM parts.

show abstract

Effect of Printing Parameters on Dimensional Error, Surface Roughness and Porosity of FFF Printed Parts with Grid Structure

Cited by 48 publications

References 39 publications

In-Process Monitoring of Temperature Evolution during Fused Filament Fabrication: A Journey from Numerical to Experimental Approaches

In-Process Monitoring of Temperature Evolution during Fused Filament Fabrication: A Journey from Numerical to Experimental Approaches

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

Analysis and Optimization of Dimensional Accuracy and Porosity of High Impact Polystyrene Material Printed by FDM Process: PSO, JAYA, Rao, and Bald Eagle Search Algorithms

Contact Info

Product

Resources

About