Experimental investigation on mechanical and tribological properties of the fused filament fabrication of poly-lactic acid parts with various print orientations

Mohan, E.; Kumar, M. Saravana

doi:10.1007/s00339-022-05579-w

Cited by 8 publications

(2 citation statements)

References 37 publications

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“…The results revealed that the friction and wear properties of the PLA samples varied with different infill densities. Mohan and Saravana Kumar 38 conducted an experimental study to assess the mechanical and tribological spesifications of PLA parts produced with different printing orientations. Their study focused on evaluating the effect of various printing orientations on the mechanical strength and wear behavior of the PLA parts.…”

Section: Introductionmentioning

confidence: 99%

Prediction of friction coefficient and torque in self-lubricating polymer radial bearings produced by additive manufacturing: A machine learning approach

Baş,

Karabacak

2023

Proceedings of the Institution of Mechanical Engineers, Part J:

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Additive manufacturing is a rapidly developing technology that enables the production of complex parts with intricate geometries. Self-lubricating radial bearings are one of the machine elements that can be produced using additive manufacturing. In this research, we present a machine learning-based approach to model the friction coefficient and friction torque in self-lubricating radial bearings manufactured by additive manufacturing using polyether ether ketone (PEEK), polylactic acid (PLA), acrylonitrile butadiene styrene (ABS), and nylon. The proposed approach includes different machine learning models (artificial neural networks, support vector machines, regression trees, linear regression models) that utilize experimental data to predict the coefficient of friction and friction torque of different types of radial bearings. Experimental data were obtained by performing tribological tests on self-lubricating radial bearings under various operating conditions. The results reveal that the machine learning models are successful in predicting the friction coefficient and friction torque in self-lubricating radial bearings with high accuracy. The approach can be utilized to optimize the design and performance of self-lubricating radial bearings manufactured using additive manufacturing.

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Section: Introductionmentioning

confidence: 99%

Prediction of friction coefficient and torque in self-lubricating polymer radial bearings produced by additive manufacturing: A machine learning approach

Baş,

Karabacak

2023

Proceedings of the Institution of Mechanical Engineers, Part J:

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“…Fused deposition modeling (FDM) is most widely used rapid prototyping (RP) technique due to its ability to produce high strength polymer parts (Bakar et al, 2010;Pacurar et al, 2010;Cotoros et al, 2012;Butt et al, 2020). FDM parts are extensively employed in sports, electronics, aerospace, architecture, automobile, robotic and pharmaceutical sectors, etc.…”

Section: Introductionmentioning

confidence: 99%

FDM Fabricated Pla Parts: An Experimental Study of Effect of Process Parameters on Mechanical Properties Under Compressive and Flexural Loading

Kumar,

Teraiya,

Koriya

2022

IJMMT

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The present paper describes an experimental investigation on mechanical properties of poly-lactic-acid (PLA) parts under compressive and flexural loading. The PLA parts are fabricated by fused deposition modelling (FDM) technique. In present work, effect of raster angle, raster width and infill density on strength and modulus of parts under compressive and flexural loading is studied. It is found that infill density affects compressive strength and modulus of parts significantly under compressive loading. Compressive properties increase with increase in infill density. Further, it is found that raster width and infill density significantly influence flexural strength and modulus. Flexural properties increase with increase in infill density, and decrease in decrease in raster width. Further, predictive models are developed for responses, and process parameters are optimized using genetic algorithm to maximize the responses.

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Use of 3D-printed polylactic acid/bioceramic composite scaffolds for bone tissue engineering in preclinical in vivo studies: A systematic review

et al. 2023

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Experimental investigation on mechanical and tribological properties of the fused filament fabrication of poly-lactic acid parts with various print orientations

Cited by 8 publications

References 37 publications

Prediction of friction coefficient and torque in self-lubricating polymer radial bearings produced by additive manufacturing: A machine learning approach

Prediction of friction coefficient and torque in self-lubricating polymer radial bearings produced by additive manufacturing: A machine learning approach

FDM Fabricated Pla Parts: An Experimental Study of Effect of Process Parameters on Mechanical Properties Under Compressive and Flexural Loading

Use of 3D-printed polylactic acid/bioceramic composite scaffolds for bone tissue engineering in preclinical in vivo studies: A systematic review

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