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Location and Orientation Dependency in Surface Roughness Of Nickel Super Alloy 625 Parts: Statistical and Distributional Analysis

Published

Author(s)

Saina Abolmaali, Alexander Vinel, Jason Fox, Jia Liu, Daniel Silva, Nima Shamsaei

Abstract

Surface roughness is an important characteristic of additively manufactured parts, as it can impact various mechanical properties, such as friction or fatigue life. Further, surface roughness can change significantly depending on a number of factors: part geometry, build plate location, process parameters or powder characteristics. Generally, it has been previously established that printing angle has a significant effect on surface roughness. In this study we reanalyze a dataset constructed based on Laser-Beam Powder Bed Fusion manufactured nickel super alloy 625 parts, with the goal of evaluating the effect of location and print orientation on variability of surface roughness, particularly relative to printing angle. Different combinations of location orientation-angles factors are tested using ANOVA, with some of the findings significant. In addition, we further consider the question of characterizing surface roughness measures as applied to additive manufacturing and explore distributional analysis (particularly extreme value theory) as a way to qualify these measures.
Proceedings Title
Proceedings of the 32nd Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference
Conference Dates
August 2-4, 2021
Conference Location
Austin, TX, US
Conference Title
Annual International Solid Freeform Fabrication Symposium

Keywords

Additive manufacturing, Roughness, ANOVA test, Extreme value theory

Citation

Abolmaali, S. , Vinel, A. , Fox, J. , Liu, J. , Silva, D. and Shamsaei, N. (2021), Location and Orientation Dependency in Surface Roughness Of Nickel Super Alloy 625 Parts: Statistical and Distributional Analysis, Proceedings of the 32nd Annual International Solid Freeform Fabrication Symposium - An Additive Manufacturing Conference, Austin, TX, US, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=933056 (Accessed April 26, 2024)
Created August 4, 2021, Updated November 29, 2022