Experimental Investigation on Wear of FDM Processed Part

Anoop Kumar Sood; Rajkumar Ohdar; S.S. Mahapatra

doi:10.4028/www.scientific.net/AMR.445.883

Paper Titles

Testing for Green Compression Strength and Permeability Properties on the Tailing Sand Samples Gathered from Ex Tin Mines in Perak State, Malaysia
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Performance of Micro-Hole Drilling by Ultrasonic-Assisted Electro-Chemical Discharge Machining
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Systematical Design of a Refrigerator Foot Height Adjustment Device
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Mechanical Characterization and Modeling of Cyclic Behavior of Ultra High Molecular Weight Polyethylene (UHMWPE)
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Experimental Investigation on Wear of FDM Processed Part
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Fabrication, Mechanical Characterization and FTIR Spectroscopic Analysis of Fish Scale Reinforced Epoxy Composites
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A Method of Analysis to Estimate Thermal Down-Shock Stress Profiles in Hollow Cylinders when Subjected to Transient Heat/Cooling Cycle
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Investigation Using Simulations for the Development of Low Cost Catalytic Converter from Non-Precious Metals
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A Multi-TAD Framework for Recognizing Machining Features Using Hint Based Recognition Algorithm
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 445Experimental Investigation on Wear of FDM...

Experimental Investigation on Wear of FDM Processed Part

Abstract:

Fused deposition modelling (FDM) is one of the rapid prototyping (RP) processes that build part of any geometry by sequential deposition of material on a layer by layer basis. Unlike other RP systems which involve an array of lasers, powders, resins, this process uses heated thermoplastic filaments which are extruded from the tip of nozzle in a prescribed manner. 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 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. Finally, the predictive equation is used to find optimal parameter setting through bacteria foraging optimization algorithm (BFOA).