An Overview of Research on FFF Based Additive Manufacturing of Polymer Compositet

EasyChair Preprint 7453

Abstract

The current article focuses on FFF technology for polymer-based additive manufacturing. Among the additive manufacturing process, Fused filament fabrication (FFF) is a more popular Additive Manufacturing process. It is regarded as the most accessible, versatile, and cost-effective prototyping procedure for polymer and composite materials. It is a layer-by-layer deposition of a thermoplastic melt filament that can rapidly construct complicated geometries, eliminating design constraints and reducing production costs associated with traditional manufacturing processes. Polymer filament is made by thermoplastically bonding nylon, ABS, PLA, PP, and other thermoplastics with various reinforcements. The inclusion of fiber reinforcement enhances the thermoplastic matrix, allowing FFF to be employed in more structurally complex-shape small tech applications. Single or twin-screw extruders with varying extrusion settings are employed (Temperature, speed) to make a filament. The physical qualities of the produced component are influenced by process parameters such as printing speed, layer height, orientation, raster angle, raster width, air gap, infill structure, fill density, and bed temperature. This review paper provides a brief insight about 3D printer's composite feedstock filament production using thermoplastic matrix and artificial fiber as reinforcement. The feedstock filaments were reportedly utilized for the fabrication of superior components using an FFF printer. Furthermore, the structural, thermal, and mechanical properties of the composite filament samples were studied.

Keyphrases: 3D printing, Additive Manufacturing, Composite fused feedstock filament, Fused Deposition Modelling

@booklet{EasyChair:7453,
  author    = {Jitendra Kumar and Vishal Mishra and Sushant Negi},
  title     = {An Overview of Research on FFF Based Additive Manufacturing of Polymer Compositet},
  howpublished = {EasyChair Preprint 7453},
  year      = {EasyChair, 2022}}