Correlation between surface texture and internal defects in laser powder-bed fusion additive manufacturing

AbstractThe availability of an in-situ monitoring and feedback control system during the implementation of metal additive manufacturing technology ensures that high-quality finished parts are manufactured. This study aims to investigate the correlation between the surface texture and internal defects or density of laser-beam powder-bed fusion (LB-PBF) parts. In this study, 120 cubic specimens were fabricated via application of the LB-PBF process to the IN 718 Ni alloy powder. The density and 35 areal surface-texture parameters of manufactured specimens were determined based on the ISO 25,178–2 standard. Using a statistical method, a strong correlation was observed between the areal surface-texture parameters and density or internal defects within specimens. In particular, the areal surface-texture parameters of reduced dale height, core height, root-mean-square height, and root-mean-square gradient demonstrate a strong correlation with specimen density. Therefore, in-situ monitoring of these areal surface-texture parameters can facilitate their use as control variables in the feedback system.

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In-Situ monitoring and modeling of metal additive manufacturing powder bed fusion

10.1063/1.5031504 ◽

2018 ◽

Cited By ~ 2

Author(s):

Jacob Alldredge ◽

John Slotwinski ◽

Steven Storck ◽

Sam Kim ◽

Arnold Goldberg ◽

...

Keyword(s):

Additive Manufacturing ◽

In Situ Monitoring ◽

Powder Bed Fusion ◽

Powder Bed ◽

Metal Additive Manufacturing ◽

Metal Additive

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In-situ monitoring and detection of spatter agglomeration and delamination during laser-based powder bed fusion of Invar 36

Optics & Laser Technology ◽

10.1016/j.optlastec.2020.106741 ◽

2021 ◽

Vol 136 ◽

pp. 106741 ◽

Cited By ~ 1

Author(s):

Mostafa Yakout ◽

Ian Phillips ◽

M.A. Elbestawi ◽

Qiyin Fang

Keyword(s):

In Situ Monitoring ◽

Powder Bed Fusion ◽

Powder Bed

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On the use of spatter signature for in-situ monitoring of Laser Powder Bed Fusion

Additive Manufacturing ◽

10.1016/j.addma.2017.05.004 ◽

2017 ◽

Vol 16 ◽

pp. 35-48 ◽

Cited By ~ 34

Author(s):

Giulia Repossini ◽

Vittorio Laguzza ◽

Marco Grasso ◽

Bianca Maria Colosimo

Keyword(s):

In Situ Monitoring ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Powder Bed

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Meta-Data for In-Situ Monitoring of Laser Powder Bed Fusion Processes

10.1115/1.0002365v ◽

2021 ◽

Author(s):

Shaw Feng ◽

Yan Lu ◽

Albert Jones

Keyword(s):

In Situ Monitoring ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Meta Data ◽

Powder Bed

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In-Situ Monitoring of Laser Powder Bed Fusion Process Anomalies via a Comprehensive Analysis of Off-Axis Camera Data

Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation ◽

10.1115/msec2020-8300 ◽

2020 ◽

Author(s):

Chaitanya Krishna Prasad Vallabh ◽

Yubo Xiong ◽

Xiayun Zhao

Keyword(s):

Real Time ◽

Network Architecture ◽

Video Data ◽

In Situ Monitoring ◽

Process Efficiency ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Monitoring Method ◽

Powder Bed

Abstract In-situ monitoring of a Laser Powder-Bed Fusion (LPBF) additive manufacturing process is crucial in enhancing the process efficiency and ensuring the built part integrity. In this work, we present an in-situ monitoring method using an off-axis camera for monitoring layer-wise process anomalies. The in-situ monitoring is performed with a spatial resolution of 512 × 512 pixels, with each pixel representing 250 × 250 μm and a relatively high data acquisition rate of 500 Hz. An experimental study is conducted by using the developed in-situ off-axis method for monitoring the build process for a standard tensile bar. Real-time video data is acquired for each printed layer. Data analytics methods are developed to identify layer-wise anomalies, observe powder bed characteristics, reconstruct 3D part structure, and track the spatter dynamics. A deep neural network architecture is trained using the acquired layer-wise images and tested by images embedded with artificial anomalies. The real-time video data is also used to perform a preliminary spatter analysis along the laser scan path. The developed methodology is aimed to extract as much information as possible from a single set of camera video data. It will provide the AM community with an efficient and capable process monitoring tool for process control and quality assurance while using LPBF to produce high-standard components in industrial (such as, aerospace and biomedical industries) applications.

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Meta-Data for In-Situ Monitoring of Laser Powder Bed Fusion Processes

10.1115/1.0005378v ◽

2021 ◽

Author(s):

Shaw Feng ◽

Yan Lu ◽

Albert Jones

Keyword(s):

In Situ Monitoring ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Meta Data ◽

Powder Bed

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The Influence of Printing Orientation on Surface Texture Parameters in Powder Bed Fusion Technology with 316L Steel

Micromachines ◽

10.3390/mi11070639 ◽

2020 ◽

Vol 11 (7) ◽

pp. 639 ◽

Cited By ~ 6

Author(s):

Tomasz Kozior ◽

Jerzy Bochnia

Keyword(s):

Surface Texture ◽

Microelectromechanical Systems ◽

Powder Bed Fusion ◽

Additive Technology ◽

Powder Bed ◽

Texture Parameters ◽

316L Steel ◽

Spatial Parameters ◽

The Impact

Laser technologies for fast prototyping using metal powder-based materials allow for faster production of prototype constructions actually used in the tooling industry. This paper presents the results of measurements on the surface texture of flat samples and the surface texture of a prototype of a reduced-mass lathe chuck, made with the additive technology—powder bed fusion. The paper presents an analysis of the impact of samples’ orientation on the building platform on the surface geometrical texture parameters (two-dimensional roughness profile parameters (Ra, Rz, Rv, and so on) and spatial parameters (Sa, Sz, and so on). The research results showed that the printing orientation has a very large impact on the quality of the surface texture and that it is possible to set digital models on the building platform (parallel—0° to the building platform plane), allowing for manufacturing models with low roughness parameters. This investigation is especially important for the design and 3D printing of microelectromechanical systems (MEMS) models, where surface texture quality and printable resolution are still a large problem.

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