An insight to the failure of FDM parts under tensile loading: finite element analysis and experimental study

Garg, Ashu; Bhattacharya, Anirban

doi:10.1016/j.ijmecsci.2016.11.032

Cited by 141 publications

(94 citation statements)

References 18 publications

(19 reference statements)

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“…It is obvious that these porosities are not caused by fiber pull‐out. Such porosities have also been reported in other literatures and are referred to as gas porosity . The formation of the gas porosity may be due to the shrinkage of the specimen during the cooling process from the molten to the solid state during the FDM printing process.…”

Section: Resultssupporting

confidence: 63%

Laser polishing of Cu/PLA composite parts fabricated by fused deposition modeling: Analysis of surface finish and mechanical properties

et al. 2019

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Fused deposition modeling (FDM) technology decreases production time and cost in engineering industry, but with typical low surface quality. In this study, laser polishing was employed to improve surface quality of copper fiber/polylactide acid (Cu/PLA) composite parts fabricated by FDM. Surface roughness, surface morphology, dynamic mechanical analysis (DMA), and tensile properties were studied. The results showed that after laser polishing, the surface roughness was reduced by more than 91% (from 10.52 to 0.87 μm Sa) at the optimized parameters (the laser power of 5 W and the laser beam diameter of 200 μm). Laser polishing can effectively remove surface defects formed during FDM. DMA showed that the storage modulus, loss modulus, and glass transition temperature of Cu/PLA composites were significantly improved, because the Cu fibers and PLA matrix formed a strong interfacial adhesion after treatment. Moreover, the tensile strength and Young's modulus of the Cu/PLA composites sample also improved by laser polishing. The fracture morphologies were observed, and the possible strengthening mechanism was also discussed.

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Section: Resultssupporting

confidence: 63%

Laser polishing of Cu/PLA composite parts fabricated by fused deposition modeling: Analysis of surface finish and mechanical properties

et al. 2019

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“…As a result of increasing stress that leads to increasing crystal dislocations which impede the previous sliding dislocations that make material be harder which requires an increase of the stress to obtain more deformation. Neck region occurs due to increasing of stress with a smaller cross section of material until failure [23]. Table 1 shows the mechanical properties of mild steel.…”

Section: Experimental Work Materials Propertiesmentioning

confidence: 99%

Experimental and simulation study of mild steel response to lateral quasi-static compression

Lafta¹,

Fareed²,

Said³

2020

JMES

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Collision of structure of a vehicle is not limited to the axial direction but it can occur laterally. The purpose of this paper is to present a study of the energy absorption behavior of different length of the circular mild steel tube under lateral crushing. A ring/tube (length of 10 mm, 35 mm, and 60 mm), 60 mm diameter and 1.5 mm thickness is compressed quasi-statically. Maximum loading setup to Instron machine was 50 kN. The speed of compression is 5mm/min. Finite Element Analysis (FEA) it used to validate the experimental work to ensure of getting accurate results. Numerical results of energy absorption and collapse load showed respectively 96.52% and 94.36% agreement with experimental results. The theoretical results showed 14.37% deviation with experimental and 15.5% with numerical results. The specimen with 60 mm length leads to better energy absorption than the other specimens. The results obtained numerically and experimentally in addition to theoretically showed the energy absorbed and collapse load varies with the length of the tube.

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“…Despite the advances in FDM technologies, they are plagued with interlayer imperfections that can cause delamination and warping, which necessitates a print job to be restarted and the material used will be wasted. Delamination occurs when the adhesion between two layers is weak and warping is caused by the residual thermal strain accumulated during the printing . It turns out that these imperfections are largely dictated by the settings of printing parameters, first‐layer calibration, and model geometry .…”

Section: Three Levels Of Nozzle Height For Four Corresponding Categoriesmentioning

confidence: 99%

Automated Real‐Time Detection and Prediction of Interlayer Imperfections in Additive Manufacturing Processes Using Artificial Intelligence

Jin

Zhang

2019

Advanced Intelligent Systems

109

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Although fused deposition modeling (FDM) additive manufacturing technologies have advanced in the past decade, interlayer imperfections such as delamination and warping are still dominant when printing complex parts. Herein, a selfmonitoring system based on real-time camera images and deep learning algorithms is developed to classify the various extents of delamination in a printed part. In addition, a novel method incorporating strain measurements is established to measure and predict the onset of warping. Results show that the machine-learning model is capable of detecting different levels of delamination conditions, and the strain measurements setup successfully reflects and determines the extent and tendency of warping before it actually occurs in the print job. This multifunctional system can be applied to assess other manufacturing processes to realize autocalibration and prediagnosis of imperfections without human interaction.

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An insight to the failure of FDM parts under tensile loading: finite element analysis and experimental study

Cited by 141 publications

References 18 publications

Laser polishing of Cu/PLA composite parts fabricated by fused deposition modeling: Analysis of surface finish and mechanical properties

Laser polishing of Cu/PLA composite parts fabricated by fused deposition modeling: Analysis of surface finish and mechanical properties

Experimental and simulation study of mild steel response to lateral quasi-static compression

Automated Real‐Time Detection and Prediction of Interlayer Imperfections in Additive Manufacturing Processes Using Artificial Intelligence

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