Eventos Anais de eventos
MECSOL 2022
8th International Symposium on Solid Mechanics
Application of Intelligent Filling Methodology in Additive Manufacturing by Fused Filament Fabrication (FFF) with Experimental Validation and Computational Simulation by Finite Elements
Submission Author:
Marcelo Otavio dos Santos , SP
Co-Authors:
Marcelo Otavio dos Santos , Gabriel Honda, Nicholas Queiroz Avedissian, Ed Claudio Bordinassi, Adalto de Farias, Gilmar Batalha
Presenter: Marcelo Otavio dos Santos
doi://10.26678/ABCM.MECSOL2022.MSL22-0029
Abstract
With the advent of additive manufacturing technologies, large companies in the world have delved into studies and research to find out how to adapt their processes to the use of this technology that has changed the way products are manufactured. One of the main concerns observed is the guarantee of the mechanical strength of the printed components once they have had their structure optimized, naturally seeking to reduce printing times and material consumption. The objective of this work was to develop and apply a methodology of structural optimization during the filling of parts in the FFF (Fused Filament Fabrication) additive manufacturing process, called Intelligent Filling. Therefore, the aim is to reduce the mass and printing time of specimens, while maintaining their mechanical strength by only changing the topology of the internal filling. A geometry that worked in normal bending and the PLA material were chosen for computational analysis performed in MSC Marc, Apex GD and Digimat RP software, the latter being specific for additive manufacturing, whereby the behavior of stresses was taken into account at the different simulation stages, as also the maximum deflections obtained, fusion between layers and internal filling involved in the process. From the computational results, some parts were printed applying the Intelligent Filling methodology and other parts were printed with conventional filling, allowing their comparison through experimental tests for each specimen. Both the impressions of the specimens and the tests were performed following the same boundary conditions used in the simulations. It was thus possible to prove the efficiency of the Intelligent Filling method proposed herein by comparative results that showed a reduction in the amount of material used by 26.3% and a 17.4% savings in manufacturing time, while maintaining the mechanical strength of the parts practically unchanged.
Keywords
Additive manufacturing, mechanical strength, structural optimization, Computational simulation, intelligent filling
