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Dimensional accuracy of a fused deposition modelling (FDM) built part is greatly influenced by many process parameters. In this study, the effect of five process parameters such as layer thickness, part build orientation, raster angle, air gap, and raster width along with their interactions has been studied using Taguchi's L27 orthogonal array. Experimental results indicate that the measured dimension is always more than the desired value along the thickness direction but the length, width, and diameter of hole of test part are less than the desired value. It has been observed that optimal factor settings for each performance characteristic such as percentage change in length, width, thickness, and diameter are different. In order to minimize four responses simultaneously, the grey-Taguchi method is adopted and optimum factor levels have been reported. Finally, overall dimensional accuracy is predicted using artificial neural network (ANN).

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