当前位置: X-MOL 学术Precis. Eng. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Surface roughness prediction model for Electron Beam Melting (EBM) processing Ti6Al4V
Precision Engineering ( IF 3.6 ) Pub Date : 2021-01-12 , DOI: 10.1016/j.precisioneng.2021.01.002
Manuela Galati , Giovanni Rizza , Silvio Defanti , Lucia Denti

Electron Beam Melting (EBM) is an Additive Manufacturing technique to produce functional components. Because of the high temperature during the EBM process, the surface texture of the as-built parts is extremely complex and unique. This distinctiveness of the surface depends on many factors and needs to be well understood to predict final surface properties accurately. Chief among these factors is the surface design. A proper surface design makes it possible to tailor a surface with specific properties such as biomimetics. However, predictive models are difficult to determine especially for downskin surfaces. To properly tailor a surface, a full factorial Design Of Experiment (DOE) was designed, and 2D and 3D roughness profiles were collected on an ad-hoc artefact using a profilometer and a confocal profilometer. This reference part comprises several surfaces to investigate the effect on surface roughness of different sloping angles, including upskin and downskin surfaces and cavities. The data are analysed using descriptive and inferential statistical tools, also by distinguishing the role of roughness and waviness in the overall surface texture. A deep investigation of the causes of surface roughness made it possible to obtain analytical predictive models. These models are robust and consistent with respect to the experimental observations. Finally, the accurate design of the artefact allows highlighting the relationship between the roughness and the surface slope.



中文翻译:

电子束熔炼Ti6Al4V的表面粗糙度预测模型

电子束熔化(EBM)是一种增材制造技术,用于生产功能部件。由于在EBM过程中温度很高,因此所制成零件的表面纹理极为复杂且独特。表面的这种独特性取决于许多因素,需要充分理解以准确预测最终的表面性能。这些因素中最主要的是表面设计。适当的表面设计可以定制具有特定特性的表面,例如仿生材料。但是,很难确定预测模型,尤其是对于皮下表面。为了适当地修剪表面,设计了全因子实验设计(DOE),并使用轮廓仪和共聚焦轮廓仪在临时工件上收集了2D和3D粗糙度轮廓。该参考零件包括多个表面,以研究不同倾斜角度对表面粗糙度的影响,包括上,下皮表面和空腔。使用描述性和推断性统计工具对数据进行分析,还通过区分粗糙度和波纹度在整个表面纹理中的作用。对表面粗糙原因的深入研究使得获得分析预测模型成为可能。这些模型是鲁棒的,并且与实验观察结果一致。最后,人工制品的精确设计可以突出显示粗糙度和表面坡度之间的关系。使用描述性和推断性统计工具对数据进行分析,还通过区分粗糙度和波纹度在整个表面纹理中的作用。对表面粗糙原因的深入研究使得获得分析预测模型成为可能。这些模型是鲁棒的,并且与实验观察结果一致。最后,人工制品的精确设计可以突出显示粗糙度和表面坡度之间的关系。使用描述性和推断性统计工具对数据进行分析,还通过区分粗糙度和波纹度在整个表面纹理中的作用。对表面粗糙原因的深入研究使得获得分析预测模型成为可能。这些模型是鲁棒的,并且与实验观察结果一致。最后,人工制品的精确设计可以突出显示粗糙度和表面坡度之间的关系。

更新日期:2021-01-24
down
wechat
bug