Process Mapping and In-Process Monitoring of Porosity in Laser Powder Bed Fusion Using Layerwise Optical Imaging

2018 ◽  
Vol 140 (10) ◽  
Author(s):  
Farhad Imani ◽  
Aniruddha Gaikwad ◽  
Mohammad Montazeri ◽  
Prahalada Rao ◽  
Hui Yang ◽  
...  
Keyword(s):  
Process Parameters ◽  
Process Conditions ◽  
Layer By Layer ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Graph Theoretic ◽  
Lack Of Fusion ◽  
Spectral Graph ◽  
Optical Images

The goal of this work is to understand the effect of process conditions on lack of fusion porosity in parts made using laser powder bed fusion (LPBF) additive manufacturing (AM) process, and subsequently, to detect the onset of process conditions that lead to lack of fusion-related porosity from in-process sensor data. In pursuit of this goal, the objectives of this work are twofold: (1) quantify the count (number), size and location of pores as a function of three LPBF process parameters, namely, the hatch spacing (H), laser velocity (V), and laser power (P); and (2) monitor and identify process conditions that are liable to cause porosity through analysis of in-process layer-by-layer optical images of the build invoking multifractal and spectral graph theoretic features. These objectives are important because porosity has a significant impact on the functional integrity of LPBF parts, such as fatigue life. Furthermore, linking process conditions to defects via sensor signatures is the first step toward in-process quality assurance in LPBF. To achieve the first objective, titanium alloy (Ti–6Al–4V) test cylinders of 10 mm diameter × 25 mm height were built under differing H, V, and P settings on a commercial LPBF machine (EOS M280). The effect of these process parameters on count, size, and location of pores was quantified based on X-ray computed tomography (XCT) images. To achieve the second objective, layerwise optical images of the powder bed were acquired as the parts were being built. Spectral graph theoretic and multifractal features were extracted from the layer-by-layer images for each test part. Subsequently, these features were linked to the process parameters using machine learning approaches. Through these image-based features, process conditions under which the parts were built were identified with the statistical fidelity over 80% (F-score).

Layerwise In-Process Quality Monitoring in Laser Powder Bed Fusion

2018 ◽  
Author(s):  
Farhad Imani ◽  
Aniruddha Gaikwad ◽  
Mohammad Montazeri ◽  
Prahalada Rao ◽  
Hui Yang ◽  
...  
Keyword(s):  
Process Parameters ◽  
Process Quality ◽  
Process Conditions ◽  
Layer By Layer ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Graph Theoretic ◽  
Spectral Graph ◽  
Optical Images

The goal of this work is to understand the effect of process conditions on part porosity in laser powder bed fusion (LPBF) Additive Manufacturing (AM) process, and subsequently, detect the onset of process conditions that lead to porosity from in-process sensor data. In pursuit of this goal, the objectives of this work are two-fold: (1) Quantify the count (number), size and location of pores as a function of three LPBF process parameters, namely, the hatch spacing (H), laser velocity (V), and laser power (P). (2) Monitor and identify process conditions that are liable to cause porosity through analysis of in-process layer-by-layer optical images of the build invoking multifractal and spectral graph theoretic features. This is important because porosity has a significant impact on the functional integrity of LPBF parts, such as fatigue life. Furthermore, linking process conditions to sensor signatures and defects is the first-step towards in-process quality assurance in LPBF. To achieve the first objective, titanium alloy (Ti-6Al-4V) test cylinders of 10 mm diameter × 25 mm height were built under differing H, V, and P settings on a commercial LPBF machine (EOS M280). The effect of these parameters on count, size and location of pores was quantified based on X-ray computed tomography (XCT) images. To achieve the second objective, layerwise optical images of the powder bed were acquired as the parts were being built. Spectral graph theoretic and multifractal features were extracted from the layer-by-layer images for each test part. Subsequently, these features were linked to the process parameters using machine learning approaches. Through these image-based features, process conditions under which the parts were built was identified with the statistical fidelity over 80% (F-score).

scholarly journals Analytical Prediction of Balling, Lack-of-Fusion and Keyholing Thresholds in Powder Bed Fusion

2021 ◽  
Vol 11 (24) ◽  
pp. 12053
Author(s):  
Wenjia Wang ◽  
Jinqiang Ning ◽  
Steven Y. Liang
Keyword(s):  
Molten Pool ◽  
Laser Power ◽  
Computational Time ◽  
Process Conditions ◽  
Analytical Prediction ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Lack Of Fusion ◽  
Analytical Thermal Model

This paper proposes analytical modeling methods for the prediction of balling, lack-of-fusion and keyholing thresholds in the laser powder bed fusion (LPBF) additive manufacturing. The molten pool dimensions were first predicted by a closed-form analytical thermal model. The effects of laser power input, boundary heat loss, powder size distribution and powder packing pattern were considered in the calculation process. The predicted molten pool dimensions were then employed in the calculation of analytical thresholds for these defects. Reported experimental data with different materials were compared to predictions to validate the presented analytical models. The predicted thresholds of these defects under various process conditions have good agreement with the experimental results. The computation time for the presented models is less than 5 min on a personal computer. The optimized process window for Ti6Al4V was obtained based on the analytical predictions of these defects. The sensitivity analyses of the value of threshold to the laser power and scanning speed were also conducted. The proposed analytical methods show higher computational efficiency than finite element methods, without including any iteration-based computations. The acceptable predictive accuracy and low computational time will make the proposed analytical strategy be a good tool for the optimization of process conditions for the fabrication of defects-free complex products in laser powder bed fusion.

Sensor-Based Build Condition Monitoring in Laser Powder Bed Fusion Additive Manufacturing Process Using a Spectral Graph Theoretic Approach

2018 ◽  
Vol 140 (9) ◽  
Author(s):  
Mohammad Montazeri ◽  
Prahalada Rao
Keyword(s):  
High Speed ◽  
Sensor Data ◽  
Theoretic Approach ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Thermal Camera ◽  
Powder Bed ◽  
Graph Theoretic ◽  
Spectral Graph ◽  
Graph Theoretic Approach

The goal of this work is to monitor the laser powder bed fusion (LPBF) process using an array of sensors so that a record may be made of those temporal and spatial build locations where there is a high probability of defect formation. In pursuit of this goal, a commercial LPBF machine at the National Institute of Standards and Technology (NIST) was integrated with three types of sensors, namely, a photodetector, high-speed visible camera, and short wave infrared (SWIR) thermal camera with the following objectives: (1) to develop and apply a spectral graph theoretic approach to monitor the LPBF build condition from the data acquired by the three sensors; (2) to compare results from the three different sensors in terms of their statistical fidelity in distinguishing between different build conditions. The first objective will lead to early identification of incipient defects from in-process sensor data. The second objective will ascertain the monitoring fidelity tradeoff involved in replacing an expensive sensor, such as a thermal camera, with a relatively inexpensive, low resolution sensor, e.g., a photodetector. As a first-step toward detection of defects and process irregularities that occur in practical LPBF scenarios, this work focuses on capturing and differentiating the distinctive thermal signatures that manifest in parts with overhang features. Overhang features can significantly decrease the ability of laser heat to diffuse from the heat source. This constrained heat flux may lead to issues such as poor surface finish, distortion, and microstructure inhomogeneity. In this work, experimental sensor data are acquired during LPBF of a simple test part having an overhang angle of 40.5 deg. Extracting and detecting the difference in sensor signatures for such a simple case is the first-step toward in situ defect detection in additive manufacturing (AM). The proposed approach uses the Eigen spectrum of the spectral graph Laplacian matrix as a derived signature from the three different sensors to discriminate the thermal history of overhang features from that of the bulk areas of the part. The statistical accuracy for isolating the thermal patterns belonging to bulk and overhang features in terms of the F-score is as follows: (a) F-score of 95% from the SWIR thermal camera signatures; (b) 83% with the high-speed visible camera; (c) 79% with the photodetector. In comparison, conventional signal analysis techniques—e.g., neural networks, support vector machines, linear discriminant analysis were evaluated with F-score in the range of 40–60%.

scholarly journals On the Relevance of Volumetric Energy Density in the Investigation of Inconel 718 Laser Powder Bed Fusion

Materials ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 538 ◽  
Author(s):  
Fabrizia Caiazzo ◽  
Vittorio Alfieri ◽  
Giuseppe Casalino
Keyword(s):  
Surface Roughness ◽  
Energy Density ◽  
Process Parameters ◽  
Vickers Hardness ◽  
Powder Bed Fusion ◽  
Processing Conditions ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Fractional Density ◽  
Experimental Variation

Laser powder bed fusion (LPBF) can fabricate products with tailored mechanical and surface properties. In fact, surface texture, roughness, pore size, the resulting fractional density, and microhardness highly depend on the processing conditions, which are very difficult to deal with. Therefore, this paper aims at investigating the relevance of the volumetric energy density (VED) that is a concise index of some governing factors with a potential operational use. This paper proves the fact that the observed experimental variation in the surface roughness, number and size of pores, the fractional density, and Vickers hardness can be explained in terms of VED that can help the investigator in dealing with several process parameters at once.

scholarly journals Comparison of Phase Characteristics and Residual Stresses in Ti-6Al-4V Alloy Manufactured by Laser Powder Bed Fusion (L-PBF) and Electron Beam Powder Bed Fusion (EB-PBF) Techniques

Crystals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 796
Author(s):  
Aya Takase ◽  
Takuya Ishimoto ◽  
Naotaka Morita ◽  
Naoko Ikeo ◽  
Takayoshi Nakano
Keyword(s):  
Electron Beam ◽  
Residual Stresses ◽  
Cooling Rate ◽  
Process Parameters ◽  
Phase Evolution ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Solidification Temperature ◽  
Powder Bed ◽  
Β Phase

Ti-6Al-4V alloy fabricated by laser powder bed fusion (L-PBF) and electron beam powder bed fusion (EB-PBF) techniques have been studied for applications ranging from medicine to aviation. The fabrication technique is often selected based on the part size and fabrication speed, while less attention is paid to the differences in the physicochemical properties. Especially, the relationship between the evolution of α, α’, and β phases in as-grown parts and the fabrication techniques is unclear. This work systematically and quantitatively investigates how L-PBF and EB-PBF and their process parameters affect the phase evolution of Ti-6Al-4V and residual stresses in the final parts. This is the first report demonstrating the correlations among measured parameters, indicating the lattice strain reduces, and c/a increases, shifting from an α’ to α+β or α structure as the crystallite size of the α or α’ phase increases. The experimental results combined with heat-transfer simulation indicate the cooling rate near the β transus temperature dictates the resulting phase characteristics, whereas the residual stress depends on the cooling rate immediately below the solidification temperature. This study provides new insights into the previously unknown differences in the α, α’, and β phase evolution between L-PBF and EB-PBF and their process parameters.

scholarly journals Role of laser powder bed fusion process parameters in crystallographic texture of additive manufactured Nb-48Ti alloy

2021 ◽  
Author(s):  
Rafael de Moura Nobre ◽  
Willy Ank de Morais ◽  
Matheus Tavares Vasques ◽  
Jhoan Guzmán ◽  
Daniel Luiz Rodrigues Junior ◽  
...  
Keyword(s):  
Process Parameters ◽  
Crystallographic Texture ◽  
Fusion Process ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed

scholarly journals Optimizing Laser Powder Bed Fusion Parameters for IN-738LC by Response Surface Method

Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 4879
Author(s):  
Mireia Vilanova ◽  
Rubén Escribano-García ◽  
Teresa Guraya ◽  
Maria San Sebastian
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Process Parameters ◽  
Crack Density ◽  
Processing Parameters ◽  
Optimum Process ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Surface Method

A method to find the optimum process parameters for manufacturing nickel-based superalloy Inconel 738LC by laser powder bed fusion (LPBF) technology is presented. This material is known to form cracks during its processing by LPBF technology; thus, process parameters have to be optimized to get a high quality product. In this work, the objective of the optimization was to obtain samples with fewer pores and cracks. A design of experiments (DoE) technique was implemented to define the reduced set of samples. Each sample was manufactured by LPBF with a specific combination of laser power, laser scan speed, hatch distance and scan strategy parameters. Using the porosity and crack density results obtained from the DoE samples, quadratic models were fitted, which allowed identifying the optimal working point by applying the response surface method (RSM). Finally, five samples with the predicted optimal processing parameters were fabricated. The examination of these samples showed that it was possible to manufacture IN738LC samples free of cracks and with a porosity percentage below 0.1%. Therefore, it was demonstrated that RSM is suitable for obtaining optimum process parameters for IN738LC alloy manufacturing by LPBF technology.

scholarly journals A study on surface morphology and tension in laser powder bed fusion of Ti-6Al-4V

2020 ◽  
Vol 111 (9-10) ◽  
pp. 2891-2909
Author(s):  
Mahyar Khorasani ◽  
AmirHossein Ghasemi ◽  
Umar Shafique Awan ◽  
Elahe Hadavi ◽  
Martin Leary ◽  
...  
Keyword(s):  
Surface Tension ◽  
Process Parameters ◽  
Surface Profile ◽  
Test Case ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Data Set ◽  
Powder Bed ◽  
Case Morphology ◽  
Melting Pool

Abstract When reporting surface quality, the roughest surface is a reference for the measurements. In LPBF due to recoil pressure and scan movement, asymmetric surface is shaped, and surface roughness has different values in different measurement orientations. In this research, the influence of the laser powder bed fusion (LPBF) process parameters on surface tension and roughness of Ti-6AI-4 V parts in three orientations are investigated. To improve the mechanical properties, heat treatment was carried out and added to the designed matrix to generate a comprehensive data set. Taguchi design of experiment was employed to print 25 samples with five process parameters and post-processing. The effect and interaction of the parameters on the formation of surface profile comprising tension, morphology and roughness in various directions have been analysed. The main contribution of this paper is developing a model to approximate the melting pool temperature and surface tension based on the process parameters. Other contributions are an analysis of process parameters to determine the formation and variation of surface tension and roughness and explain the governing mechanisms through rheological phenomena. Results showed that the main driving factors in the variation of surface tension and formation of the surface profile are thermophysical properties of the feedstock, rheology and the temperature of the melting pool. Also, the results showed that while the value of surface tension is the same for each test case, morphology and the value of roughness are different when analysing the surface in perpendicular, parallel and angled directions to laser movement.

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