scholarly journals Process Parameter Optimization in Metal Laser-Based Powder Bed Fusion Using Image Processing and Statistical Analyses

Metals ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 87
Author(s):  
Faiyaz Ahsan ◽  
Jafar Razmi ◽  
Leila Ladani
Keyword(s):  
Contact Angle ◽  
Process Parameters ◽  
Laser Power ◽  
Pool Size ◽  
Scale Production ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Scan Speed ◽  
Melt Pool Size

The powder bed fusion additive manufacturing process has received widespread interest because of its capability to manufacture components with a complicated design and better surface finish compared to other additive techniques. Process optimization to obtain high quality parts is still a concern, which is impeding the full-scale production of materials. Therefore, it is of paramount importance to identify the best combination of process parameters that produces parts with the least defects and best features. This work focuses on gaining useful information about several features of the bead area, such as contact angle, porosity, voids, melt pool size and keyhole that were achieved using several combinations of laser power and scan speed to produce single scan lines. These features are identified and quantified using process learning, which is then used to conduct a comprehensive statistical analysis that allows to estimate the effect of the process parameters, such as laser power and scan speed on the output features. Both single and multi-response analyses are applied to analyze the response parameters, such as contact angle, porosity and melt pool size individually as well as in a collective manner. Laser power has been observed to have a more influential effect on all the features. A multi-response analysis showed that 150 W of laser power and 200 mm/s produced a bead with the best possible features.

A Physics-Informed Two-Level Machine Learning Model for Predicting Melt-Pool Size in Laser Powder Bed Fusion

2021 ◽  
Author(s):  
Yong Ren ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris
Keyword(s):  
Machine Learning ◽  
Initial Temperature ◽  
Pool Size ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Input Feature ◽  
Melt Pool Size ◽  
Melt Pool Characteristics

Abstract Laser powder bed fusion (L-PBF) additive manufacturing (AM) is one type of metal-based AM process that is capable of producing high-value complex components with a fine geometric resolution. As melt-pool characteristics such as melt-pool size and dimensions are highly correlated with porosity and defects in the fabricated parts, it is crucial to predict how process parameters would affect the melt-pool size and dimensions during the build process to ensure the build quality. This paper presents a two-level machine learning (ML) model to predict the melt-pool size during the scanning of a multi-track build. To account for the effect of thermal history on melt-pool size, a so-called (pre-scan) initial temperature is predicted at the lower-level of the modeling architecture, and then used as a physics-informed input feature at the upper-level for the prediction of melt-pool size. Simulated data sets generated from the Autodesk's Netfabb Simulation are used for model training and validation. Through numerical simulations, the proposed two-level ML model has demonstrated a high prediction performance and its prediction accuracy improves significantly compared to a naive one-level ML without using the initial temperature as an input feature.

Measurement of the Melt Pool Length During Single Scan Tracks in a Commercial Laser Powder Bed Fusion Process

2017 ◽  
Author(s):  
J. C. Heigel ◽  
B. M. Lane
Keyword(s):  
Laser Power ◽  
High Speed ◽  
Infrared Camera ◽  
Powder Bed Fusion ◽  
Single Track ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Significant Difference ◽  
Scan Speed

This work presents high speed thermographic measurements of the melt pool length during single track laser scans on nickel alloy 625 substrates. Scans are made using a commercial laser powder bed fusion machine while measurements of the radiation from the surface are made using a high speed (1800 frames per second) infrared camera. The melt pool length measurement is based on the detection of the liquidus-solidus transition that is evident in the temperature profile. Seven different combinations of programmed laser power (49 W to 195 W) and scan speed (200 mm/s to 800 mm/s) are investigated and numerous replications using a variety of scan lengths (4 mm to 12 mm) are performed. Results show that the melt pool length reaches steady state within 2 mm of the start of each scan. Melt pool length increases with laser power, but its relationship with scan speed is less obvious because there is no significant difference between cases performed at the highest laser power of 195 W. Although keyholing appears to affect the anticipated trends in melt pool length, further research is required.

scholarly journals Influences of Process Parameters on the Microstructure and Mechanical Properties of CoCrFeNiTi Based High-Entropy Alloy in a Laser Powder Bed Fusion Process

Crystals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 549
Author(s):  
Takafumi Ikeda ◽  
Makiko Yonehara ◽  
Toshi-Taka Ikeshoji ◽  
Tohru Nobuki ◽  
Minoru Hatate ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Surface Roughness ◽  
Process Parameters ◽  
Laser Power ◽  
Powder Bed Fusion ◽  
Process Map ◽  
Powder Bed ◽  
High Entropy ◽  
Scan Speed ◽  
Fabrication Condition

Recently, high-entropy alloys (HEAs) have attracted much attention because of their superior properties, such as high strength and corrosion resistance. This study aimed to investigate the influences of process parameters on the microstructure and mechanical properties of CoCrFe NiTiMo HEAs using a laser-based powder bed fusion (LPBF) process. In terms of laser power and scan speed, a process map was constructed by evaluating the density and surface roughness of the as-built specimen to optimize the process parameters of the products. The mechanical properties of the as-built specimens fabricated at the optimum fabrication condition derived from the process map were evaluated. Consequently, the optimum laser power and scan speed could be obtained using the process map evaluated by density and surface roughness. The as-built specimen fabricated at the optimum fabrication condition presented a relative density of more than 99.8%. The microstructure of the as-built specimen exhibited anisotropy along the build direction. The tensile strength and elongation of the as-built specimen were around 1150 MPa and more than 20%, respectively.

Measurement of the Melt Pool Length During Single Scan Tracks in a Commercial Laser Powder Bed Fusion Process

2018 ◽  
Vol 140 (5) ◽  
Author(s):  
J. C. Heigel ◽  
B. M. Lane
Keyword(s):  
Laser Power ◽  
High Speed ◽  
Infrared Camera ◽  
Powder Bed Fusion ◽  
Single Track ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Melt Pool ◽  
Significant Difference ◽  
Scan Speed

This work presents high-speed thermographic measurements of the melt pool length during single track laser scans on nickel alloy 625 substrates. Scans are made using a commercial laser powder bed fusion (PBF) machine while measurements of the radiation from the surface are made using a high speed (1800 frames per second) infrared camera. The melt pool length measurement is based on the detection of the liquidus–solidus transition that is evident in the temperature profile. Seven different combinations of programmed laser power (49–195 W) and scan speed (200–800 mm/s) are investigated, and numerous replications using a variety of scan lengths (4–12 mm) are performed. Results show that the melt pool length reaches steady-state within 2 mm of the start of each scan. Melt pool length increases with laser power, but its relationship with scan speed is less obvious because there is no significant difference between cases performed at the highest laser power of 195 W. Although keyholing appears to affect the anticipated trends in melt pool length, further research is required.

scholarly journals Melt Pool Features Analysis Using a High Speed Coaxial Monitoring System for Laser Powder Bed Fusion of Ti-6Al-4V Grade 23

2021 ◽  
Author(s):  
Aditi Thanki ◽  
Louca Goossens ◽  
Agusmian Partogi Ompusunggu ◽  
Mohamad Bayat ◽  
Abdellatif Bey-Temsamani ◽  
...  
Keyword(s):  
Energy Density ◽  
Laser Power ◽  
High Speed ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Porosity Formation ◽  
Powder Bed ◽  
Binary Images ◽  
Melt Pool ◽  
Scan Speed

Abstract In laser powder bed fusion (LPBF), defects such as pores or cracks can seriously affect the final part quality and lifetime. Keyhole porosity, being one type of porosity defects in LPBF, results from excessive energy density which may be due to changes in process parameters (laser power and scan speed) and/or result from the part’s geometry and/or hatching strategies. To study the possible occurrence of keyhole pores, experimental work as well as simulations were carried out for optimum and high volumetric energy density conditions in Ti-6Al-4V grade 23. By decreasing the scanning speed from 1000 mm/s to 500 mm/s for a fixed laser power of 170 W, keyhole porosities are formed and later observed by X-ray computed tomography. Melt pool images are recorded in real-time during the LPBF process by using a high speed coaxial Near-Infrared (NIR) camera monitoring system. The recorded images are then pre-processed using a set of image processing steps to generate binary images. From the binary images, geometrical features of the melt pool and features that characterize the spatter particles formation and ejection from the melt pool are calculated. The experimental data clearly show spatter patterns in case of keyhole porosity formation at low scan speed. A correlation between the number of pores and the amount of spatter is observed. Besides the experimental work, a previously developed, high fidelity finite volume numerical model was used to simulate the melt pool dynamics with similar process parameters as in the experiment. Simulation results illustrate and confirm the keyhole porosity formation by decreasing laser scan speed.

3D Build Melt Pool Predictive Modeling for Powder Bed Fusion Additive Manufacturing

2020 ◽  
Author(s):  
Zhuo Yang ◽  
Yan Lu ◽  
Ho Yeung ◽  
Sundar Kirshnamurty
Keyword(s):  
Neural Network ◽  
Additive Manufacturing ◽  
Pool Size ◽  
Powder Bed Fusion ◽  
Neural Network Approach ◽  
Validation Data ◽  
Powder Bed ◽  
Melt Pool ◽  
Scan Pattern ◽  
Melt Pool Size

Abstract Melt pool size is a critical intermediate measure that reflects the outcome of a laser powder bed fusion process setting. Reliable melt pool predictions prior to builds can help users to evaluate potential part defects such as lack of fusion and over melting. This paper develops a layer-wise Neighboring-Effect Modeling (L-NBEM) method to predict melt pool size for 3D builds. The proposed method employs a feedforward neural network model with ten layer-wise and track-wise input variables. An experimental build using a spiral concentrating scan pattern with varying laser power was conducted on the Additive Manufacturing Metrology Testbed at the National Institute of Standards and Technology. Training and validation data were collected from 21 completed layers of the build, with 6,192,495 digital commands and 118,928 in-situ melt pool coaxial images. The L-NBEM model using the neural network approach demonstrates a better performance of average predictive error (12.12%) by leave-one-out cross-validation method, which is lower than the benchmark NBEM model (15.23%), and the traditional power-velocity model (19.41%).

scholarly journals Virtual Development of Process Parameters for Bulk Metallic Glass Formation in Laser-Based Powder Bed Fusion

Materials ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 450
Author(s):  
Johan Lindwall ◽  
Andreas Lundbäck ◽  
Jithin James Marattukalam ◽  
Anders Ericsson
Keyword(s):  
Additive Manufacturing ◽  
Metallic Glass ◽  
Bulk Metallic Glass ◽  
Process Parameters ◽  
Glass Formation ◽  
Laser Power ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Scanning Strategies ◽  
Hatch Spacing

The development of process parameters and scanning strategies for bulk metallic glass formation during additive manufacturing is time-consuming and costly. It typically involves trials with varying settings and destructive testing to evaluate the final phase structure of the experimental samples. In this study, we present an alternative method by modelling to predict the influence of the process parameters on the crystalline phase evolution during laser-based powder bed fusion (PBF-LB). The methodology is demonstrated by performing simulations, varying the following parameters: laser power, hatch spacing and hatch length. The results are compared in terms of crystalline volume fraction, crystal number density and mean crystal radius after scanning five consecutive layers. The result from the simulation shows an identical trend for the predicted crystalline phase fraction compared to the experimental estimates. It is shown that a low laser power, large hatch spacing and long hatch lengths are beneficial for glass formation during PBF-LB. The absolute values show an offset though, over-predicted by the numerical model. The method can indicate favourable parameter settings and be a complementary tool in the development of scanning strategies and processing parameters for additive manufacturing of bulk metallic glass.

scholarly journals Manufacturing Aluminum/Multiwalled Carbon Nanotube Composites via Laser Powder Bed Fusion

Materials ◽  
2020 ◽  
Vol 13 (18) ◽  
pp. 3927
Author(s):  
Eo Ryeong Lee ◽  
Se Eun Shin ◽  
Naoki Takata ◽  
Makoto Kobashi ◽  
Masaki Kato
Keyword(s):  
Elastic Modulus ◽  
Carbon Nanotube ◽  
Energy Density ◽  
Laser Power ◽  
Multiwalled Carbon Nanotube ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Multiwalled Carbon ◽  
Powder Bed ◽  
Scan Speed

This study provides a novel approach to fabricating Al/C composites using laser powder bed fusion (LPBF) for a wide range of structural applications utilizing Al-matrix composites in additive manufacturing. We investigated the effects of LPBF on the fabrication of aluminum/multiwalled carbon nanotube (Al/MWCNT) composites under 25 different conditions, using varying laser power levels and scan speeds. The microstructures and mechanical properties of the specimens, such as elastic modulus and nanohardness, were analyzed, and trends were identified. We observed favorable sintering behavior under laser conditions with low energy density, which verified the suitability of Al/MWCNT composites for a fabrication process using LPBF. The size and number of pores increased in specimens produced under high energy density conditions, suggesting that they are more influenced by laser power than scan speed. Similarly, the elastic modulus of a specimen was also more affected by laser power than scan speed. In contrast, scan speed had a greater influence on the final nanohardness. Depending on the laser power used, we observed a difference in the crystallographic orientation of the specimens by a laser power during LPBF. When energy density is high, texture development of all samples tended to be more pronounced.

On Process Temperature in Powder-Bed Electron Beam Additive Manufacturing: Model Development and Validation

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Bo Cheng ◽  
Steven Price ◽  
James Lydon ◽  
Kenneth Cooper ◽  
Kevin Chou
Keyword(s):  
Thermal Conductivity ◽  
Electron Beam ◽  
Additive Manufacturing ◽  
Thermal Characteristics ◽  
Pool Size ◽  
Process Temperature ◽  
Thermal Imager ◽  
Powder Bed ◽  
Melt Pool ◽  
Melt Pool Size

Powder-bed beam-based metal additive manufacturing (AM) such as electron beam additive manufacturing (EBAM) has a potential to offer innovative solutions to many challenges and difficulties faced in the manufacturing industry. However, the complex process physics of EBAM has not been fully understood, nor has process metrology such as temperatures been thoroughly studied, hindering part quality consistency, efficient process development and process optimizations, etc., for effective EBAM usage. In this study, numerical and experimental approaches were combined to research the process temperatures and other thermal characteristics in EBAM using Ti–6Al–4V powder. The objective of this study was to develop a comprehensive thermal model, using a finite element (FE) method, to predict temperature distributions and history in the EBAM process. On the other hand, a near infrared (NIR) thermal imager, with a spectral range of 0.78 μm–1.08 μm, was employed to acquire build surface temperatures in EBAM, with subsequent data processing for temperature profile and melt pool size analysis. The major results are summarized as follows. The thermal conductivity of Ti–6Al–4V powder is porosity dependent and is one of critical factors for temperature predictions. The measured thermal conductivity of preheated powder (of 50% porosity) is 2.44 W/m K versus 10.17 W/m K for solid Ti–6Al–4V at 750 °C. For temperature measurements in EBAM by NIR thermography, a method was developed to compensate temperature profiles due to transmission loss and unknown emissivity of liquid Ti–6Al–4V. At a beam speed of about 680 mm/s, a beam current of about 7.0 mA and a diameter of 0.55 mm, the peak process temperature is on the order around 2700 °C, and the melt pools have dimensions of about 2.94 mm, 1.09 mm, and 0.12 mm, in length, width, and depth, respectively. In general, the simulations are in reasonable agreement with the experimental results with an average error of 32% for the melt pool sizes. From the simulations, the powder porosity is found critical to the thermal characteristics in EBAM. Increasing the powder porosity will elevate the peak process temperature and increase the melt pool size.

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