3D Printing of Fiber-Reinforced Polymer Nanocomposites: Additive Manufacturing

Dhanunjayarao, Borra N.; Naidu, N. V. Swamy; Kumar, R. Suresh; Phaneendra, Y.; Sateesh, B.; Olajide, J. L.; Sadiku, Emmanuel Rotimi

doi:10.1007/978-3-030-36268-3_166

Cited by 2 publications

(2 citation statements)

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“…The basic principle behind this MSLA technology is to selectively expose the polymer to UV light masked by an LCD screen. MSLA is a photopolymer 3D printing technique that uses an LCD screen to project a masked image of an object in layers onto a photopolymer vat (Dhanunjayarao et al , 2020). The top-down and bottom-up classifications of SLA are based on build platform movements and the position of LCD (Uribe-Lam et al , 2021).…”

Section: Introductionmentioning

confidence: 99%

“…Visualization, product optimization, rapid design iteration, inspection, prototyping and the creation of functional test models are all examples of MSLA approaches in the fields of aerospace, manufacturing, medicine, architecture and education applications (Kumar and Kim, 2020). 3D-printed microfluidic devices, conductive polymer composite and electronic sensors (Khan and Lazoglu, 2020), biosensors (Shahbazi and Jäger, 2021), magneto responsive materials, shape memory polymers (Nam and Pei, 2019) (Subeshan et al , 2021), self-healing materials (Ghilan et al , 2020), functional composites, structural composites and supercapacitors are the trends of present research (Dhanunjayarao et al , 2020). The ability to model components prior to their manufacturing improves the design’s robustness and reduces design revisions.…”

Section: Introductionmentioning

confidence: 99%

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Parametric optimization for dimensional correctness of 3D printed part using masked stereolithography: Taguchi method

Borra

Neigapula

2022

RPJ

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Purpose Masked stereolithography (MSLA) or resin three-dimensional (3D) printing is one of the most extensively used high-resolution additive manufacturing technologies. Even though, the quality of 3D printing is determined by several factors, including the equipment, materials and slicer. Besides, the layer height, print orientation and exposure time are important processing parameters in determining the quality of the 3D printed green state specimen. The purpose of the paper is to optimize the printing parameters of the Masked Stereolithography apparatus for its dimensional correctness of 3D printed parts using the Taguchi method. Design/methodology/approach The acrylate-based photopolymer resin is used to produce the parts using liquid crystal display (LCD)-type resin 3D printer. This study is mainly focused on optimizing the processing parameters by using Taguchi analysis, L-9 orthogonal array in Minitab software. Analysis of variance (ANOVA) was performed to determine the most influencing factors, and a regression equation was built to predict the best potential outcomes for the given set of parameters and levels. The signal-to-noise ratios were calculated by using the smaller the better characteristic as the deviations from the nominal value should be minimum. The optimal levels for each factor were determined with the help of mean plots. Findings Based on the findings of ANOVA, it was observed that exposure time plays an important role in most of the output measures. The model’s goodness was tested using a confirmation test and the findings were found to be within the confidence limit. Also, a similar specimen was printed using the fused filament fabrication (FFF) technique; it was compared with the quality and features of MSLA 3D printing technology. Practical implications The study presents the statistical analysis of experimental results of MSLA and made a comparison with FFF in terms of dimensional accuracy and print quality. Originality/value Many previous studies reported the results based on earlier 3D printing technology such as stereolithography but LCD-based MSLA is not yet reported for its dimensional accuracy and part quality. The presented paper proposes the use of statistical models to optimize the printing parameters to get dimensional accuracy and the good quality of the 3D printed green part.

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Section: Introductionmentioning

confidence: 99%