Correlation of SWIR imaging with LPBF 304L stainless steel part properties

Lough, Cody S.; Wang, Xin; Smith, Christopher C.; Landers, Robert G.; Bristow, Douglas A.; Drallmeier, J. A.; Brown, Ben; Kinzel, Edward C.

doi:10.1016/j.addma.2020.101359

Cited by 18 publications

(15 citation statements)

References 27 publications

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“…A laser PRF of f 0 = 10 kHz and a point distance of PD = 1 µm, corresponding to a scan speed of V = 10 mm/s, are used. This scan speed is well below the range typical for 304L stainless steel 13,31 ; however, it was selected to gather sufficient data when processing a single line (i.e., the laser did not need to reverse its direction of travel). Figure 4 shows experimental results for Tuning Fork #16 using various laser powers.…”

Section: Resultsmentioning

confidence: 99%

“…The increase in recoil force is due to the fact that as the laser power increases a greater amount of material will be vaporized. Figure 6 shows the recoil force for a range of characteristic process parameters for 304L stainless steel 34 . Powder was spread across the surface of the tuning forks using two 50 µm thick metal shims to create a uniform layer.…”

Section: Resultsmentioning

confidence: 99%

“…However, the recoil force magnitude is significantly greater than the other forces acting on the melt pool once it starts to vaporize. For example, using the definitions of these forces described in Heeling et al 12 and typical processing parameters for 304L stainless steel 13 , the recoil force is at least an order of magnitude larger than the net Marangoni force, and more than eight orders of magnitude larger than the capillary and buoyancy forces.…”

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confidence: 99%

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Frequency Domain Measurements of Melt Pool Recoil Force Using Modal Analysis

Cullom

Lough

Altese

et al. 2020

Preprint

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Recoil pressure is a critical factor affecting the melt pool dynamics during Laser Powder Bed Fusion (LPBF) processes. Recoil pressure depresses the melt pool, providing layer-to-layer fusion without introducing porosity. If the recoil pressure is too low, the process operates in a conduction mode where layers will not properly fuse, while excessive recoil pressure leads to a keyhole mode, which results in gas porosity. Direct recoil pressure measurements are challenging because it is localized over an area proportionate to the laser spot size producing a force in the mN range. This paper reports a vibration-based approach to quantify the recoil force exerted on a part in a commercial LPBF machine. The measured recoil force is consistent with estimates from high speed synchrotron imaging of entrained particles, and the results show that the recoil force scales with applied laser power and is inversely related to the laser scan speed. These results facilitate further studies of melt pool dynamics and have the potential to aid process development for new materials.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

mentioning

confidence: 99%

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Frequency Domain Measurements of Melt Pool Recoil Force Using Modal Analysis

Cullom

Lough

Altese

et al. 2020

Preprint

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“…Finally, the results of threedimensional reconstruction were compared with the mechanical properties and micro-defects to establish the correlation between local properties and defects. It was found that the thermal characteristics of "exceeding threshold time" had the strongest correlation with the local performance and defects of the part, which provides the basis for the prediction of the quality of the parts during the SLM process [73] . The essence of the threedimensional reconstruction of the heat history during SLM is to extract the pixel-level information and then combine the information in the same layer into an image, which is then employed to predict the quality.…”

Section: In Situ Monitoring Of Scanned Layer and Powderspread-layer Based On Infrared Imagingmentioning

confidence: 99%

In situ monitoring methods for selective laser melting additive manufacturing process based on images — A review

Zhou

et al. 2021

China Foundry

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Selective laser melting (SLM) has been widely used in the fields of aviation, aerospace and die manufacturing due to its ability to produce metal components with arbitrarily complex shapes. However, the instability of SLM process often leads to quality fluctuation of the formed component, which hinders the further development and application of SLM. In situ quality control during SLM process is an effective solution to the quality fluctuation of formed components. However, the basic premise of feedback control during SLM process is the rapid and accurate diagnosis of the quality. Therefore, an in situ monitoring method of SLM process, which provides quality diagnosis information for feedback control, became one of the research hotspots in this field in recent years. In this paper, the research progress of in situ monitoring during SLM process based on images is reviewed. Firstly, the significance of in situ monitoring during SLM process is analyzed. Then, the image information source of SLM process, the image acquisition systems for different detection objects (the molten pool region, the scanned layer and the powder spread layer) and the methods of the image information analysis, detection and recognition are reviewed and analyzed. Through review and analysis, it is found that the existing image analysis and detection methods during SLM process are mainly based on traditional image processing methods combined with traditional machine learning models. Finally, the main development direction of in situ monitoring during SLM process is proposed by combining with the frontier technology of image-based computer vision.

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“…The LPBF process is industrially used for applications where usually high-cost material and complex structures are necessary to be produced. The LPBF process enables the production of high-quality parts using several powder materials, including Ni [1,2], Fe- [3] and Ti-alloys [4]. In addition, certain aluminium alloys are more widely used in LPBF, showing advantages in part performances due to lightweight design possibilities [5].…”

Section: Introductionmentioning

confidence: 99%

Fluctuations of Tracks and Layers during Aluminium Laser Powder-Bed Fusion

2021

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Laser Powder-Bed Fusion (LPBF) is one method in Additive Manufacturing where layer-wise complex structures can be built. However, although the LPBF machines produce promising parts, the efficiency and process speed are typically still low, which can make the process expensive and uneconomical. Recent research showed that volume elements in the parts can be melted several times, while only a small material volume is added, which indicates a high loss of energy. In order to understand the process better, in this work, theoretical modeling and smart powder-bed experiments were designed to explain the impact on the track dimensions based on the previously built tracks and layers. It was found that the powder availability varies for each track and has an alternating character within and between layers. The comparison of the simulation and experimental results indicates that the powder pick-up from neighboring powder volumes is the main reason for the variations of the powder availability.

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Correlation of SWIR imaging with LPBF 304L stainless steel part properties

Cited by 18 publications

References 27 publications

Frequency Domain Measurements of Melt Pool Recoil Force Using Modal Analysis

Frequency Domain Measurements of Melt Pool Recoil Force Using Modal Analysis

In situ monitoring methods for selective laser melting additive manufacturing process based on images — A review

Fluctuations of Tracks and Layers during Aluminium Laser Powder-Bed Fusion

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