Surface roughness analysis, modelling and prediction in selective laser melting

被引:679
作者
Strano, Giovanni [1 ]
Hao, Liang [1 ]
Everson, Richard M. [1 ]
Evans, Kenneth E. [1 ]
机构
[1] Univ Exeter, Coll Engn Math & Phys Sci, Exeter EX4 4QF, Devon, England
关键词
Additive manufacturing; Surface roughness prediction; Surface analysis; Mathematical modelling; TOP;
D O I
10.1016/j.jmatprotec.2012.11.011
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Selective Laser Melting (SLM) is an increasingly employed additive manufacturing process for the production of medical, aerospace, and automotive parts. Despite progresses in material flexibility and mechanical performances, relatively poor surface finish still presents a major limitation in the SLM process. In this study an investigation of surface roughness and morphology is presented for Steel 316L alloy parts made by SLM. In order to characterise the actual surfaces at different sloping angles, truncheon samples have been produced and an analysis has been conducted at different scales, by surface profilometer and scanning electron microscope (SEM). The surface analysis has showed an increasing density of spare particles positioned along the step edges, as the surface sloping angle increases. When layer thickness is comparable to particle diameter, the particles stuck along step edges can fill the gaps between consecutive layers, thus affecting the actual surface roughness. Classic models for roughness prediction, based on purely geometrical consideration of the stair step profile, fail to describe the observed trend of the experimental data. A new mathematical model is developed to include the presence of particles on top surfaces, in addition to the stair step effect, for the accurate prediction of surface roughness. Results show that surface roughness predicted by this model has a good agreement with the experimentally observed roughness. The paper investigates the key contributing factors influencing surface morphology, and a theoretical model for roughness prediction that provides valuable information to improve the surface quality of SLM parts, thus minimising the need of surface finishing. (C) 2012 Elsevier B.V. All rights reserved.
引用
收藏
页码:589 / 597
页数:9
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