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Prediction of Extreme Value Areal Parameters in Laser Powder Bed Fusion of Nickel Superalloy 625
Surface Topography: Metrology and Properties ( IF 2.0 ) Pub Date : 2021-06-02 , DOI: 10.1088/2051-672x/ac0061
Jason C Fox 1 , Adam L Pintar 2
Affiliation  

Important to the success of additive manufacturing (AM) is the ability to inspect and qualify parts. The research community is pushing to identify correlations between part function and surface topography, yet little guidance specific to AM surface measurement exists. Thus, development of inspection methods for surface finish are Required. In laser powder bed fusion (LPBF) AM, parts are built through a complex process with many variables, and the length scales of interest on the surface cover a wide range. Full characterization of the surface is time consuming and costly as high resolution in surface measurements decreases field-of-view (FoV), requiring stitching multiple FoVs to cover large areas. Statistical methods exist to estimate the maximum value based on a sample of FoVs, but are not yet commonplace in AM surface measurement. The goal of this work is to understand the use of these statistical methods in the estimation of maximum area valley depth (Sv) of a surface, an extreme value parameter, for which researchers have already found relationship to fatigue life. This work also investigates the effect of microscope objective, measurement region size, and nesting index of areal filters on Sv. A large (i.e., greater than 40 mmנ40 mm) planar LPBF surface is fabricated in nickel superalloy 625 and measured using a focus variation microscope with a 10x objective and again with a 20x objective. Results show that there is little difference in the maximum value of Sv between the two objectives, but the nesting index does have some effect. Results also show that a Type 1 Generalized Extreme Value, or Gumbel, distribution can be used to accurately estimate the maximum value of Sv for a surface from a small set of measurements, providing a framework for users to develop inspection routines that balance measurement time and accuracy of estimation.



中文翻译:

镍高温合金625激光粉末床熔合中极值面参数的预测

增材制造 (AM) 成功的重要因素是检查和鉴定零件的能力。研究界正在努力确定零件功能与表面形貌之间的相关性,但几乎没有针对 AM 表面测量的指导。因此,需要开发表面光洁度检测方法。在激光粉末床融合 (LPBF) AM 中,零件是通过具有许多变量的复杂过程构建的,并且表面上感兴趣的长度范围涵盖了很广的范围。表面的完整表征既费时又费钱,因为表面测量的高分辨率会降低视场 (FoV),需要拼接多个 FoV 以覆盖大面积。存在基于 FoV 样本估计最大值的统计方法,但在 AM 表面测量中尚不普遍。Sv ),一个极值参数,研究人员已经发现了与疲劳寿命的关系。这项工作还研究了显微镜物镜、测量区域大小和面滤波器的嵌套指数对Sv 的影响。大(即,大于 40 毫米和 40 毫米)平面 LPBF 表面是在镍超级合金 625 中制造的,并使用具有 10 倍物镜和 20 倍物镜的聚焦变化显微镜进行测量。结果表明,两个目标之间Sv的最大值差异不大,但嵌套指数确实有一定的影响。结果还表明,第 1 类广义极值或 Gumbel 分布可用于准确估计Sv的最大值 对于来自一小组测量的表面,为用户提供了一个框架来开发平衡测量时间和估计精度的检查程序。

更新日期:2021-06-02
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