Investigation of Mechanical Properties of 3D-Printed PLA Coated with PU/MWCNTs in a Corrosive Environment

Farajian, Jafar; Hatami, Omid; Bakhtiari, Meisam; Darabinajand, Bahman; Mahboubkhah, Mehran

doi:10.1007/s13369-023-08632-9

Arab J Sci Eng

2024

DOI: 10.1007/s13369-023-08632-9

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Investigation of Mechanical Properties of 3D-Printed PLA Coated with PU/MWCNTs in a Corrosive Environment

Jafar Farajian,

Omid Hatami,

Meisam Bakhtiari

et al.

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Cited by 7 publications

References 41 publications

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Comparison of the performances of Statistical and Artificial Neural Network models in the prediction of geometry and density of PLA/wood biocomposite cubes manufactured by FDM

Contuzzi,

Morvayová,

Fabbiano

et al. 2024

Int J Adv Manuf Technol

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The present study investigates the impact of scanning speed, printing temperature, and layer height on the density, dimensions, errors of parallelism, and surface finish of cubical specimens made of PLA/wood biocomposite and manufactured by Fused Deposition Modelling (FDM). The study examined 64 specimens, each produced with a unique set of process parameters. The Response Surface Methodology (RSM) was employed to evaluate the effects of process parameters on the examined properties of the manufactured cubes. RSM analysis revealed the statistical significance of direct proportion between the layer height, printing temperature, and x-and y-dimensions of the manufactured specimens (with P-values of 0, 0, 0.002, and 0, respectively). Also, the scanning speed and error of parallelism in z-oriented faces were statistically correlated (with a P-value of 0.035). For layer height and cube density, an indirect proportion was observed (with a P-value of 0). Compared to the regression model, ANN exhibited better performance at process parameters effect evaluation. The worse performance of regression models can be attributed to their limited capacity to represent non-linear relationships, while ANN models can capture the complex non-linear nature of the process, leading to better performances (R2 close to 100%). An evaluation of the defects in the specimens was carried out using the go/no-go diagram.

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Comparison of the performances of Statistical and Artificial Neural Network models in the prediction of geometry and density of PLA/wood biocomposite cubes manufactured by FDM

Contuzzi,

Morvayová,

Fabbiano

et al. 2024

Int J Adv Manuf Technol

View full text Add to dashboard Cite

show abstract

Uncertainty propagation in fused filament fabrication process: a multiscale approach

Kizhakkinan,

Rosen,

Raghavan

2024

Int J Adv Manuf Technol

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Silver and magnesium co-doped β-TCP nanoparticles as potential materials for bone tissue engineering

Noori,

Khamis,

Shather

et al. 2024

Appl. Phys. A

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Investigation of Mechanical Properties of 3D-Printed PLA Coated with PU/MWCNTs in a Corrosive Environment

Cited by 7 publications

References 41 publications

Comparison of the performances of Statistical and Artificial Neural Network models in the prediction of geometry and density of PLA/wood biocomposite cubes manufactured by FDM

Comparison of the performances of Statistical and Artificial Neural Network models in the prediction of geometry and density of PLA/wood biocomposite cubes manufactured by FDM

Uncertainty propagation in fused filament fabrication process: a multiscale approach

Silver and magnesium co-doped β-TCP nanoparticles as potential materials for bone tissue engineering

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