Statistical analysis of spatter velocity with high-speed stereovision in laser powder bed fusion

Barrett, Christopher B.; Carradero, Carolyn; Harris, Evan; Rogers, Kirk; MacDonald, Eric; Conner, Brett

doi:10.1007/s40964-019-00094-6

Cited by 31 publications

(9 citation statements)

References 29 publications

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“…Off-axis video-imaging in the visible range Yang et al, 2020a, b;Tan et al, 2020;Yin et al, 2020;Zhang et al, 2019a, b;Nassar et al, 2019;Bidare et al, 2018a,b;Zheng et al, 2018;Zhang et al, 2018;Ye et al, 2019Ye et al, , 2018aAndani et al, 2018;Ozel et al 2018;Repossini et al, 2017;Ly et al 2017;Andani et al, 2017;Liu et al, 2015;Bidare et al, 2017 Off-axis stereo vision in the visible range Eschner et al, 2020a;Eschner et al, 2019;Barrett et al, 2019;Barrett et al, 2018a Off-axis NIR/IR video imaging Yang et al, 2020b;Grasso and Colosimo, 2019;Grasso et al, 2018a;Ozel et al, 2018 Off-axis X-ray video imaging Young et al 2020;Leung et al, 2019;Guo et al, 2018;Zhao et al, 2017Off-axis Schlieren videoimaging Bidare et al, 2018aBidare et al, 2017 Air-borne acoustic emissions Air-borne acoustic emission detector Shevchik et al, 2019;Wasmer et al, 2019;Ye et al, 2018b;Kouprianoff et al (2018) Level 2 monitoring methods involve off-axis mounted sensors, mainly cameras in the visible range or thermal cameras. Unlike in level 1 methods, high temporal resolution is needed to capture fast and transient phenomena, whereas high spatial resolution is needed to characterise the spatial features of interest.…”

Section: Signatures Of Interest Sensing Methods References (L-pbf) Re...mentioning

confidence: 99%

“…In most cases, focus was on the characterisation of the by-product ejection mechanism and the correlation of salient properties measured via high-speed video imaging (e.g, the number of spatters, their size, velocity, spread in space) with different process parameters. Recent studies proposed a high-speed stereo vision setup to identify and track individual spatters in the 3D space above the layer (Eschner et al 2020a, Barrett et al 2019.…”

Section: Measurement Of Process By-productsmentioning

confidence: 99%

“…the number of spatters, their size, velocity, spread in space) with different process parameters. Recent studies proposed a high-speed stereo vision setup to identify and track individual spatters in the 3D space above the layer (Barrett et al 2018a, 2019, Eschner et al 2019. Spatter tracking along its trajectory may improve the characterisation of process byproducts and provide additional insights about their origination mechanism and the influence of process parameters (an example is shown in figure 15(c)).…”

Section: Measurement Of Process By-productsmentioning

confidence: 99%

See 2 more Smart Citations

In-situ measurement and monitoring methods for metal powder bed fusion: an updated review

Grasso

Remani

Dickins

et al. 2021

Meas. Sci. Technol.

138

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The possibility of using a variety of sensor signals acquired during metal powder bed fusion processes, to support part and process qualification and for the early detection of anomalies and defects, has been continuously attracting an increasing interest. The number of research studies in this field has been characterised by significant growth in the last few years, with several advances and new solutions compared with first seminal works. Moreover, industrial powder bed fusion systems are increasingly equipped with sensors and toolkits for data collection, visualisation and, in some cases, embedded in-process analysis. Many new methods have been proposed and defect detection capabilities have been demonstrated. Nevertheless, several challenges and open issues still need to be tackled to bridge the gap between methods proposed in the literature and actual industrial implementation. This paper presents an updated review of the literature on in-situ sensing, measurement and monitoring for metal powder bed fusion processes, with a classification of methods and a comparison of enabled performances. The study summarises the types and sizes of defects that are practically detectable while the part is being produced and the research areas where additional technological advances are currently needed.

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Section: Signatures Of Interest Sensing Methods References (L-pbf) Re...mentioning

confidence: 99%

Section: Measurement Of Process By-productsmentioning

confidence: 99%

Section: Measurement Of Process By-productsmentioning

confidence: 99%

See 1 more Smart Citation

In-situ measurement and monitoring methods for metal powder bed fusion: an updated review

Grasso

Remani

Dickins

et al. 2021

Meas. Sci. Technol.

138

View full text Add to dashboard Cite

show abstract

“…The spatters move in three dimensions, but in this work, we can only observe spatter particle motion and trajectory in the projection on the XY plane parallel to the sensor of the camera. Some studies showed the feasibility of spatter tracking using a high-speed stereo vision and 3D particle tracking velocimetry [38,39].…”

Section: Spatter Feature Analysis From Monitoring Datamentioning

confidence: 99%

Off-axis high-speed camera-based real-time monitoring and simulation study for laser powder bed fusion of 316L stainless steel

Thanki

Jordan

Booth

et al. 2023

Int J Adv Manuf Technol

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In-situ monitoring and post-process metrology form a basis to better understand the fundamental physics involved in the Laser Powder Bed Fusion (LPBF) process and ultimately to determine its stability. By utilizing high-speed imaging, various process signatures are produced during single track formation of 316L stainless steel with various combinations of laser power and scan speed. In this study, we evaluate whether these signatures can be used to detect the onset of potential defects. To identify process signatures, image segmentation and feature detection are applied to the monitoring data along the line scans. The process signatures determined in the current study are mainly related to the features like the process zone length-to-width ratio, process zone area, process zone mean intensity, spatter speed and number of spatters. It is shown that the scan speed has a signi cant impact on the process stability and spatter formation during single track fusion. Simulations with similar processing conditions were also performed to predict melt pool geometric features. Post-process characterization techniques such as Xray computed tomography and 2.5-D surface topography measurement were carried out for a quality check of the line track. An attempt was made to correlate physics-based features with process-related defects and a correlation between the number of keyhole porosities and the number of spatters was observed for the line tracks.

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“…It is assumed that the ejecta exhibiting incandescence contribute to the majority of powder oxidation. Finally, the segmentation of the collected images is based on the geometry of the part using the STL design files as the guidance to separate the pixels for laser-irradiated area and spatter regions, which does not involve image thresholding techniques used in [34][35][36].…”

Section: Use Of Ot Images For Tracking Powder Degradationmentioning

confidence: 99%

Influence of part geometry on spatter formation in laser powder bed fusion of Inconel 718 alloy revealed by optical tomography

Chen

Raza

Hryha

2022

Journal of Manufacturing Processes

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Statistical analysis of spatter velocity with high-speed stereovision in laser powder bed fusion

Cited by 31 publications

References 29 publications

In-situ measurement and monitoring methods for metal powder bed fusion: an updated review

In-situ measurement and monitoring methods for metal powder bed fusion: an updated review

Off-axis high-speed camera-based real-time monitoring and simulation study for laser powder bed fusion of 316L stainless steel

Influence of part geometry on spatter formation in laser powder bed fusion of Inconel 718 alloy revealed by optical tomography

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