A hybrid ANN/PSO optimization of material composition and process parameters for enhancement of mechanical characteristics of 3D-printed sample
ISSN: 1355-2546
Article publication date: 28 February 2023
Issue publication date: 2 June 2023
Abstract
Purpose
This paper aims to study the effects of inorganic CaCO3 nanoadditives in the polylactic acid (PLA) matrix and fused filament fabrication (FFF) process parameters on the mechanical characteristics of 3D-printed components.
Design/methodology/approach
The PLA filaments containing different levels of CaCO3 nanoparticles have been produced by mix-blending/extrusion process and were used to fabricate tensile and three-point bending test samples in FFF process under various sets of printing speed (PS), layer thickness (LT), filling ratio (FR) and printing pattern (PP) under a Taguchi L27 orthogonal array design. The quantified values of mechanical characteristics of 3D-printed samples in the uniaxial and the three-point bending experiments were modeled and optimized using a hybrid neural network/particle swarm optimization algorithm. The results of this hybrid scheme were used to specify the FFF process parameters and the concentration of nanoadditive in the matrix that result in the maximum mechanical properties of fabricated samples, individually and also in an accumulative response scheme. Diffraction scanning calorimetry (DSC) tests were conducted on a number of samples and the results were used to interpret the variations observed in the response variables of fabricated components against the FFF parameters and concentration of CaCO3 nanoadditives.
Findings
The results of optimization in an accumulative scheme showed that the samples of linear PP, fabricated at high PS, low LT and at 100% FR, while containing 0.64% of CaCO3 nanoadditives in the matrix, would possess the highest mechanical characteristics of 3D-printed PLA components.
Originality/value
FFF is a widely accepted additive manufacturing technique in production of different samples, from prototypes to the final products, in various sectors of industry. The incorporation of chopped fibers and nanoparticles has been introduced recently in a few articles to improve the mechanical characteristics of produced components in FFF technique. However, the effectiveness of such practice is strongly dependent on the extrusion parameters and composition of polymer matrix.
Keywords
Acknowledgements
This work was supported by Scientific Research Coordination Unit of Adana Alparslan Türkeş Science and Technology University with project number of 22303004.
Citation
Seyedzavvar, M. (2023), "A hybrid ANN/PSO optimization of material composition and process parameters for enhancement of mechanical characteristics of 3D-printed sample", Rapid Prototyping Journal, Vol. 29 No. 6, pp. 1270-1288. https://doi.org/10.1108/RPJ-10-2022-0338
Publisher
:Emerald Publishing Limited
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