Mechanical investigations on secondary recycled ABS-based composite multi-layered tensile and flexural specimens prepared by fused filament fabrication

The present research work explored the feasibility of using the fused filament fabrication (FFF) technique for the fabrication of non-structural components through in-house prepared composite filaments by utilizing various industrial wastes to address the global issue of recyclability. In this work, the researchers utilized secondary (2º) recycled acrylonitrile butadiene styrene (ABS) as the base matrix and wastes such as wood dust (WD), Fe powder, and bakelite powder (BP) as reinforcements for preparing the multi-layered (layers of different composite material) tensile and flexural composite specimen through FFF technique of additive manufacturing. The reinforced composite feedstock filaments prepared in-house by the twin screw extrusion process were utilized to print multi-layered specimens by varying the infill speed, infill density, and raster angle during the FFF process. The outer three layers on both sides of the multi-layered specimen were printed with filament reinforced with BP and Fe powder whereas the inner layers were composed of WD-reinforced filaments to induce specific characteristics. The influence of printing parameters on the selected mechanical properties of composite specimens was investigated and analyzed through electron-dispersive spectroscopy (EDS) and scanning electron microscopic (SEM) characterization. The optimization results highlighted that 0º raster angle, 100% infill density, and 20 mm/s infill speed yield the best values of the tensile strength (15.35 MPa), flexural strength (32.11 MPa), percentage tensile break elongation (7.16%) and percentage flexural break elongation (12.39%) with the desirability of 0.719 when all the output parameters were taken simultaneously. The main motivation behind the work is to print multi-material smart tiles for low-temperature regions to conserve the heat inside the cabins along with self-assembly features.