Parametric Optimization of Fused Deposition Modelling (FDM) Process Using PSO Algorithm
6 Pages Posted: 12 Feb 2018
Date Written: December 21, 2017
3D Printing is a layered manufacturing process that builds prototypes by depositing material in layered form using heaters. Prototypes made by 3D Printing are widely used in product development as they can be used for product testing. Prototypes should have a very good mechanical property for functional performance as well as aesthetics. The mechanical properties in 3D printing depends upon different process parameters, namely Layer Thickness, Nozzle Diameter, Infill Density, Part Bed Temperature, Skin Thickness, Raster Angle of Deposition, Raster Width and Length of the parts. In this present work, an attempt has been made to improve the mechanical property, tensile strength of prototypes of Acrylonitrile Butadiene Styrene (ABS) parts fabricated using Fused Deposition Modelling process of 3D Printing. Experiments are conducted using Taguchi’s design of experiments with three levels for each factor. Experiments were carried out on FDM Accucraft i250 machines coupled with KIS-Slicer software and ABS as main material. Parameter effect on tensile strength and there interaction are studied in taguchi method. Using Particle Swarm Optimization (PSO) algorithm optimal values of process parameter are found studied for maximum tensile strength.
Keywords: 3D Printing, FDM, Taguchi Method, Particle Swarm Optimization
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