An investigation on sliding wear of FDM built parts

Present work focuses on extensive study to understand the effect of five important parameters such as layer thickness, part build orientation, raster angle, raster width and air gap on the sliding wear of test specimen built through fused deposition modelling process (FDM). The study provides insight into complex dependency of wear on process parameters and proposes a statistically validated predictive equation. Microphotographs are used to explain the mechanism of wear. The equation is used to find optimal parameter setting through quantum-behaved particle swarm optimization (QPSO). As FDM process is highly complex one and process parameters influence the responses in a non linear manner, artificial neural network (ANN) are employed to confirm the results of present study.