Optimization of 3D printed polylactic acid structures with different infill patterns using Taguchi-grey relational analysis

John, Joel; Devjani, Deepak; Ali, Shafahat; Abdallah, Said; Pervaiz, Salman

doi:10.1016/j.aiepr.2022.06.002

Cited by 26 publications

(21 citation statements)

References 27 publications

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“…The GRG is proclaimed by equation (6) and the equation from 2,3,4,5 and 6 are referred from the previously done studies. 33,34 where γ i = Grey relational grade for the i th experimental trial and ‘ n ’ refers to the number of responses.…”

Section: Methodsmentioning

confidence: 99%

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Influence of printing-based factors on the mechanical properties of hexagonal lattice-structured 3D printed novel walnut shell/polylactic acid composite

Mathiazhagan¹,

Sivakumar²,

Palaniyappan

et al. 2023

Journal of Thermoplastic Composite Materials

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The incorporation of bio-based natural fillers and lattice structures in thermoplastic polymer has superior advantages such as a reduction in the usage of conventional polymers with improved damping and mechanical properties. The present work focuses on the development of Walnut Shell/PLA (WSP) lattice-structured composite by the Fused Filament Fabrication technique. The flexural strength, compression strength, and thickness error properties of the hexagon lattice-structured WSP composites are optimized by varying Printing-Based Factors (PBFs) which include infill density (60%, 80%, and 100%), nozzle temperature (190°C, 210°C, and 230°C), printing speed (10 mm/sec, 20 mm/sec, and 30 mm/sec), and layer height (0.1 mm, .2 mm, and .3 mm). The flexural and compression test experiments were conducted as per the ASTM D790 and ASTM D695 standards. The process optimization of the measured responses is made by using Taguchi grey relational grade optimization technique. The experimental outcomes such as compressive and flexural strength and minimal dimensional error are converted into the Grey Relational Grade (GRG) for the optimization process. The results show that the Signal-to-Noise ratio (S/N) from the measured GRG clearly shows that, the lower layer height of 0.1 mm, higher nozzle temperature of 230°C, higher infill density of 100%, and average printing speed of 20 mm/sec is an optimal experimental condition for attaining higher strengths and lower errors. From the Analysis of Variance (ANOVA) analysis, the printing temperature, and layer height are the most persuasive PBFs for the mechanical and physical characteristics with respect to the incorporated lattice structure. The optimized experimental conditions develop maximum flexural and compressive strengths of 4.98 MPa and 28.19 MPa, in addition to a lower thickness error of .186 mm obtained for hexagon lattice-structured WSP biopolymeric composites.

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Section: Methodsmentioning

confidence: 99%

“…The GRG is proclaimed by equation ( 6) and the equation from 2,3,4,5 and 6 are referred from the previously done studies. 33,34…”

Section: Grey Relational Gradementioning

confidence: 99%

Influence of printing-based factors on the mechanical properties of hexagonal lattice-structured 3D printed novel walnut shell/polylactic acid composite

Mathiazhagan¹,

Sivakumar²,

Palaniyappan

et al. 2023

Journal of Thermoplastic Composite Materials

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“…The cellular, nozzle diameter and, strain rate factors are studied using the Taguchi and Grey relational analyse to understand their influences on toughness, stiffness and resilience [14]. The study considered factors that are less commonly correlated to the response outputs, and the factorial design suggested for the Taguchi method was not based on a standard orthogonal array.…”

Section: Introductionmentioning

confidence: 99%

Optimising the Mechanical Properties of Additive-Manufactured Recycled Polylactic Acid (rPLA) using Single and Multi-Response Analyses Methods.

Gebrehiwot,

Espinosa-Leal

et al. 2023

Preprint

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Taguchi’s design of experiment (DoE) and the grey relational analysis are used to optimise fused deposition modelling (FDM) parameters for the tensile strength and Modulus of toughness (MoT) responses of a recycled Polylactic acid (Reform-rPLA) polymer. The influences of the infill geometry, infill density, infill orientation, nozzle temperature and infill speed on the mechanical properties of the material are studied using the \({L}_{18}\) orthogonal array which is based the \({2}^{1}\times {4}^{3}\) factor levels with 3 experimental repetitions. The output responses are first studied individually and combined as a multi-response optimisation using the grey relational analysis method. The analysis of variance (ANOVA) showed that the infill orientation parameter highly influences both the single and multi-response optimisations. In the strength optimisation, the infill orientation and infill density are statistically significant with P-values \(\alpha\) less than the 0.05 criterion. Similarly, the ANOVA for the (MoT) showed that infill orientation and infill geometry parameters are statistically significant. The infill orientation is statistically significant for the multi-response optimisation, followed by the infill density with \({\alpha }=0.08\). On the other hand, the response predictions indicated that the zigzag infill geometry, \(45\%\) infill density, \(90^\circ\) infill geometry and \(205℃\) nozzle temperature led to optimum tensile strength and MoT properties. Our confirmation tests are in good agreement with optimum response predictions. Based on rankings of the mean responses, the first three factors were used to develop linear regression models for the tensile strength and MoT of the material. The predictive models showed average errors of \(7.91\%\) for the tensile strength and \(8.6\%\) for the MoT.

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“…The characteristics of the printed samples largely depend on the process parameters [1]. The primary process parameters include the infill pattern, infill percentage, printing speed, layer thickness, build orientation and raster angle [1,[4][5][6][7]. Some thermoplastic polymers used as filament for 3D printing are Acrylonitrile Butadiene Styrene (ABS), Polylactic acid (PLA), Nylon, Polyether-ether-ketone (PEEK) and Polycarbonate (PC) [4].…”

Section: Introductionmentioning

confidence: 99%

Application of composite material models to determine the Young’s modulus of the grid pattern of partially infilled 3D printed samples

Tognana,

Pomarico,

Montecinos

et al. 2023

Eng. Res. Express

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Additive manufacturing makes it possible to fabricate samples with partial internal infill. This type of sample has a different Young’s modulus than a completely filled sample. In this work, the dependence of the apparent Young’s modulus of samples manufactured by 3D printing on the infill percentage has been experimentally determined, for a given pattern and using a non-destructive technique. Young’s modulus was assumed as an apparent modulus and values were found between 3.39 GPa for the sample with 100% infill and 1.32 GPa for the sample with 20% infill. In particular, a non-linear variation of the apparent Young’s modulus was observed. The specific Young’s modulus presents a minimum for an intermediate infill percentage. The use of a model of composite materials was proposed, as a first approach to determine the apparent Young’s modulus of the parts. The mixture law, the Halpin-Tsai equation generalized by Kerner, a model of foams and the Mori Tanaka method were applied to the dependence of the apparent Young’s modulus on the infill percentage, giving all, except the mixture law, acceptable results. The advantage of applying each model was discussed. This type of analysis would allow a fast semi-empirical approach of the apparent Young’s modulus in partially filled samples with a grid pattern.

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Optimization of 3D printed polylactic acid structures with different infill patterns using Taguchi-grey relational analysis

Cited by 26 publications

References 27 publications

Influence of printing-based factors on the mechanical properties of hexagonal lattice-structured 3D printed novel walnut shell/polylactic acid composite

Influence of printing-based factors on the mechanical properties of hexagonal lattice-structured 3D printed novel walnut shell/polylactic acid composite

Optimising the Mechanical Properties of Additive-Manufactured Recycled Polylactic Acid (rPLA) using Single and Multi-Response Analyses Methods.

Application of composite material models to determine the Young’s modulus of the grid pattern of partially infilled 3D printed samples

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