Mechanical properties evaluation of FFF-printed ABS samples based on different process parameters combined with ANOVA and regression analysis

Tyagi, Bobby; Dubey, Dushyant; Sahai, Ankit; Sharma, Rahul Swarup

doi:10.1177/09544062231151540

Cited by 15 publications

(5 citation statements)

References 33 publications

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“…Due to their operational and mechanical limitations, FDM 3D printing techniques based on material extrusion still need to be researched for MP array fabrication. The FDM is widely used for fabricating continuous structures and sculptures and uses 3D printing filaments rather than expensive resin (Tyagi et al , 2023). The 3D printing filaments have improved mechanical strength and require less post-processing.…”

Section: Comparative Discussion On Digital Light Processing and Fused...mentioning

confidence: 99%

Rapid prototyping of 3d printed micropillars using fused filament fabrication technique for biomedical applications

Khatoon,

Ahmad

2023

RPJ

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Purpose The hygroscopic properties of 3D-printed filaments and moisture absorption itself during the process result in dimensional inaccuracy, particularly for nozzle movement along the x-axis and for micro-scale features. In view of that, this study aims to analyze in depth the dimensional errors and deviations of the fused filament fabrication (FFF)/fused deposition modeling (FDM) 3D-printed micropillars (MPs) from the reference values. A detailed analysis into the variability in printed dimensions below 1 mm in width without any deformations in the printed shape of the designed features, for challenging filaments like polymethyl methacrylate (PMMA) has been done. The study also explores whether the printed shape retains the designed structure. Design/methodology/approach A reference model for MPs of width 800 µm and height 2,000 µm is selected to generate a g-code model after pre-processing of slicing and meshing parameters for 3D printing of micro-scale structure with defined boundaries. Three SETs, SET-A, SET-B and SET-C, for nozzle diameter of 0.2 mm, 0.25 mm and 0.3 mm, respectively, have been prepared. The SETs containing the MPs were fabricated with the spacing (S) of 2,000 µm, 3,200 µm and 4,000 µm along the print head x-axis. The MPs were measured by taking three consecutive measurements (top, bottom and middle) for the width and one for the height. Findings The prominent highlight of this study is the successful FFF/FDM 3D printing of thin features (<1mm) without any deformation. The mathematical analysis of the variance of the optical microscopy measurements concluded that printed dimensions for micropillar widths did not vary significantly, retaining more than 65% of the recording within the first standard deviation (SD) (±1 s). The minimum value of SD is obtained from the samples of SET-B, that is, 31.96 µm and 35.865 µm, for height and width, respectively. The %RE for SET-B samples is 5.09% for S = 2,000µm, 3.86% for S = 3,200µm and 1.09% for S = 4,000µm. The error percentage is so small that it could be easily compensated by redesigning. Research limitations/implications The study does not cover other 3D printing techniques of additive manufacturing like stereolithography, digital light processing and material jetting. Practical implications The presented study can be potentially implemented for the rapid prototyping of microfluidics mixer, bioseparator and lab-on-chip devices, both for membrane-free bioseparation based on microfiltration, plasma extraction from whole blood, size-selection trapping of unwanted blood cells, and also for membrane-based plasma extraction that requires supporting microstructures. Our developed process may prove to be far more economical than the other existing techniques for such applications. Originality/value For the first time, this work presents a comprehensive analysis of the fabrication of micropillars using FDM/FFF 3D printing and PMMA in filament form. The primary focus of the study is to minimize the dimensional inaccuracies in the 3D printed devices containing thin features, especially in the area of biomedical engineering, by delivering benefits from the choice of the parameters. Thus, on the basis of errors and deviations, a thorough comparison of the three SETs of the fabricated micropillars has been done.

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Section: Comparative Discussion On Digital Light Processing and Fused...mentioning

confidence: 99%

Rapid prototyping of 3d printed micropillars using fused filament fabrication technique for biomedical applications

Khatoon,

Ahmad

2023

RPJ

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“…Tao et al (2020) explored the impact of varying orientation angles on tensile strength, revealing that a 0° orientation angle resulted in maximum tensile strength, while 45° led to the minimum. Tyagi et al (2023) delved into the effects of LH, feed rate and extrusion temperature on the tensile and compression properties of FDM-based acrylonitrile butadiene styrene (ABS) structures. Their research used analysis of variance (ANOVA) and Taguchi-based regression analysis to discern the relationship between mechanical characteristics and process parameters.…”

Section: Introductionmentioning

confidence: 99%

Machine learning for forecasting the biomechanical behavior of orthopedic bone plates fabricated by fused deposition modeling

Sharma,

Gupta,

Mudgal

et al. 2024

RPJ

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Purpose Three-dimensional (3D) printing is highly dependent on printing process parameters for achieving high mechanical strength. It is a time-consuming and expensive operation to experiment with different printing settings. The current study aims to propose a regression-based machine learning model to predict the mechanical behavior of ulna bone plates. Design/methodology/approach The bone plates were formed using fused deposition modeling (FDM) technique, with printing attributes being varied. The machine learning models such as linear regression, AdaBoost regression, gradient boosting regression (GBR), random forest, decision trees and k-nearest neighbors were trained for predicting tensile strength and flexural strength. Model performance was assessed using root mean square error (RMSE), coefficient of determination (R2) and mean absolute error (MAE). Findings Traditional experimentation with various settings is both time-consuming and expensive, emphasizing the need for alternative approaches. Among the models tested, GBR model demonstrated the best performance in predicting both tensile and flexural strength and achieved the lowest RMSE, highest R2 and lowest MAE, which are 1.4778 ± 0.4336 MPa, 0.9213 ± 0.0589 and 1.2555 ± 0.3799 MPa, respectively, and 3.0337 ± 0.3725 MPa, 0.9269 ± 0.0293 and 2.3815 ± 0.2915 MPa, respectively. The findings open up opportunities for doctors and surgeons to use GBR as a reliable tool for fabricating patient-specific bone plates, without the need for extensive trial experiments. Research limitations/implications The current study is limited to the usage of a few models. Other machine learning-based models can be used for prediction-based study. Originality/value This study uses machine learning to predict the mechanical properties of FDM-based distal ulna bone plate, replacing traditional design of experiments methods with machine learning to streamline the production of orthopedic implants. It helps medical professionals, such as physicians and surgeons, make informed decisions when fabricating customized bone plates for their patients while reducing the need for time-consuming experimentation, thereby addressing a common limitation of 3D printing medical implants.

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“…Each of these PCs contributes to the overall performance and durability of the prosthesis. To optimize the performance of FFF-printed parts, researchers have extensively explored the influence of various PCs, including the IFP, raster angle, layer thickness, nozzle temperature, [25][26][27][28][29][30][31][32] and NHD. [33][34][35] Kesavarma et al 36 highlighted the significant impact of IFP and internal filling (IF) percentages on the bending behavior of FFF-printed components.…”

Section: Introductionmentioning

confidence: 99%

Characterization of flexural and compressive behavior in polylactic acid composites for low‐cost transtibial prosthetic applications: Influence of reinforcements

Tyagi,

Dixit,

Sahai

et al. 2024

J of Applied Polymer Sci

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Loss of a lower limb leads to immobility, necessitating the use of prosthetic foot and socket as substitutes for lost limbs. However, the production of these prosthetic devices poses challenges due to the wide array of printing settings, materials, and post‐processing techniques involved. The objectives of this study were to examine the compression and flexural behavior of polylactic acid reinforced with carbon fiber fabricated via fused filament fabrication (FFF) and to investigate the effects of process constraints, namely nozzle hole diameter (0.20, 0.40, and 0.60 mm) and internal filling pattern (rectilinear, honeycomb, and triangle). The study employed compression and flexural tests, along with the analysis of failure morphology, on build samples. The resulting data were analyzed using Taguchi ANOVA and response surface methodology (RSM) to determine how compression and flexural behavior vary with the specified process constraints. The research findings demonstrate that the prosthetic socket and foot prosthesis created using FFF exhibit superior flexural and compressive behavior and strength, respectively. These results signify the potential for cost reduction in the production of prosthetic devices. The significance of these results lies in the improvement of prosthetic device production, enabling enhanced mobility and independence for amputees.

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Mechanical properties evaluation of FFF-printed ABS samples based on different process parameters combined with ANOVA and regression analysis

Cited by 15 publications

References 33 publications

Rapid prototyping of 3d printed micropillars using fused filament fabrication technique for biomedical applications

Rapid prototyping of 3d printed micropillars using fused filament fabrication technique for biomedical applications

Machine learning for forecasting the biomechanical behavior of orthopedic bone plates fabricated by fused deposition modeling

Characterization of flexural and compressive behavior in polylactic acid composites for low‐cost transtibial prosthetic applications: Influence of reinforcements

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