Thermal Based Process Monitoring for Laser Powder Bed Fusion (LPBF)

2021 ◽  
Vol 1161 ◽  
pp. 123-130
Author(s):  
Dieter Tyralla ◽  
Thomas Seefeld
Keyword(s):  
Process Monitoring ◽  
Cross Sections ◽  
Observation System ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Destructive Testing ◽  
Camera System ◽  
Powder Bed ◽  
Post Process ◽  
Melt Pool

Laser powder bed fusion (LPBF) is a frequently used manufacturing process due to its advantages in lightweight construction, design possibilities and functionalization of geometry. However, the printed parts will often have to undergo time and cost expensive non-destructive testing by sophisticated methods like X-CT. Thus, there is a strong demand to identify suitable online process monitoring techniques that allow to reduce or substitute post-process NDT effort. The temperature field reacts sensitively to deviations during processing, thus online temperature monitoring is a promising approach. In the present work a spatially resolved temperature measurement, based on 2-channel-pyrometry, is used for process monitoring in LPBF. The camera system is coaxially integrated into the beam guidance of the LPBF system. The coaxial observation enables a lateral resolution better than 10 μm over the whole build-up area of 250 x 250 mm2. Single tracks were welded with different parameters and observed by the camera system to identify thermal indicators. Metallographic cross-sections of the tracks were compared with the melt pool width measured by the online observation system. The deviation was ca. 3 %. In addition, cubes of 10 mm by 10 mm by 10 mm are built up. The melt pool area is identified as useful indicator for the process behavior and for the first time the assessment of part density is demonstrated in LPBF during process by the help of a thermal monitoring system.

scholarly journals Thermographic measurements of the commercial laser powder bed fusion process at NIST

2016 ◽  
Vol 22 (5) ◽  
pp. 778-787 ◽  
Author(s):  
Brandon Lane ◽  
Shawn Moylan ◽  
Eric P. Whitenton ◽  
Li Ma
Keyword(s):  
Process Monitoring ◽  
High Speed ◽  
Frame Rate ◽  
High Magnification ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Content Type ◽  
Powder Bed ◽  
Temperature Range ◽  
Melt Pool

Purpose Quantitative understanding of the temperatures, gradients and heating/cooling rates in and around the melt pool in laser powder bed fusion (L-PBF) is essential for simulation, monitoring and controls development. The research presented here aims to detail experiment design and preliminary results of high speed, high magnification, in-situ thermographic monitoring setup on a commercial L-PBF system designed to capture temperatures and dynamic process phenomena. Design/methodology/approach A custom door with angled viewport was designed for a commercial L-PBF system which allows close access of an infrared camera. Preliminary finite element simulations provided size, speed and scale requirements to design camera and optics setup to capture melt pool region temperatures at high magnification and frame rate speed. A custom thermal calibration allowed maximum measurable temperature range of 500°C to 1,025°C. Raw thermographic image data were converted to temperature assuming an emissivity of 0.5. Quantitative temperature results are provided with qualitative observations with discussion regarding the inherent challenges to future thermographic measurements and process monitoring. Findings Isotherms around the melt pool change in size depending on the relative location of the laser spot with respect to the stripe edges. Locations near the edges of a stripe are cooled to lower temperatures than the center of a stripe. Temperature gradients are highly localized because of rough or powdery surface. At a specific location, temperatures rise from below the measurable temperature range to above (<550°C to >1100°C) within two frames (<1.11 m/s). Particle ejection is a notable phenomenon with measured ejection speeds >11.7 m/s. Originality/value Several works are detailed in the Introduction of this paper that detail high-speed visible imaging (not thermal imaging) of custom or commercial LBPF processes, and lower-speed thermographic measurements for defect detection. However, no work could be found that provides calibrated, high-speed temperature data from a melt-pool monitoring configuration on a commercial L-PBF system. In addition, the paper elucidates several sources of measurement uncertainty (e.g. calibration, emissivity and time and spatial resolution), describes inherent measurement challenges based on observations of the thermal images and discusses on the implications to model validation and process monitoring and control.

scholarly journals A new approach for automated measuring of the melt pool geometry in laser-powder bed fusion

2021 ◽  
Author(s):  
Simon Schmid ◽  
Johannes Krabusch ◽  
Thomas Schromm ◽  
Shi Jieqing ◽  
Stefan Ziegelmeier ◽  
...  
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
Energy Input ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
New Approach ◽  
Powder Bed ◽  
Part Quality ◽  
Melt Pool ◽  
Process Disturbances

AbstractAdditive manufacturing (AM) offers unique possibilities in comparison to conventional manufacturing processes. For example, complex parts can be manufactured without tools. For metals, the most commonly used AM process is laser-powder bed fusion (L-PBF). The L-PBF process is prone to process disturbances, hence maintaining a consistent part quality remains an important subject within current research. An established indicator for quantifying process changes is the dimension of melt pools, which depends on the energy input and the cooling conditions. The melt pool geometry is normally measured manually in cross sections of solidified welding seams. This paper introduces a new approach for the automated visual measuring of melt pools in cross-sections of parts manufactured by L-PBF. The melt pools are first segmented in the images and are then measured. Since the melt pools have a heterogeneous appearance, segmentation with common digital image processing is difficult, deep learning was applied in this project. With the presented approach, the melt pools can be measured over the whole cross section of the specimen. Furthermore, remelted melt pools, which are only partly visible, are evaluated. With this automated approach, a high number of melt pools in each cross-section can be measured, which allows the examination of trends over the build direction in a specimen and results in better statistics. Furthermore, deviations in the energy input can be estimated via the measured melt pool dimensions.

scholarly journals Optimization of Laser Powder Bed Fusion Processing Using a Combination of Melt Pool Modeling and Design of Experiment Approaches: Density Control

2019 ◽  
Vol 3 (1) ◽  
pp. 21 ◽  
Author(s):  
Morgan Letenneur ◽  
Alena Kreitcberg ◽  
Vladimir Brailovski
Keyword(s):  
Scanning Speed ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Powder Bed ◽  
Density Prediction ◽  
Melt Pool ◽  
Density Control ◽  
Pool Model ◽  
Conventional Material ◽  
Prediction Approach

A simplified analytical model of the laser powder bed fusion (LPBF) process was used to develop a novel density prediction approach that can be adapted for any given powder feedstock and LPBF system. First, calibration coupons were built using IN625, Ti64 and Fe powders and a specific LPBF system. These coupons were manufactured using the predetermined ranges of laser power, scanning speed, hatching space, and layer thickness, and their densities were measured using conventional material characterization techniques. Next, a simplified melt pool model was used to calculate the melt pool dimensions for the selected sets of printing parameters. Both sets of data were then combined to predict the density of printed parts. This approach was additionally validated using the literature data on AlSi10Mg and 316L alloys, thus demonstrating that it can reliably be used to optimize the laser powder bed metal fusion process.

scholarly journals Optimization of the Post-Process Heat Treatment of Inconel 718 Superalloy Fabricated by Laser Powder Bed Fusion Process

Metals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 144
Author(s):  
Eslam M. Fayed ◽  
Mohammad Saadati ◽  
Davood Shahriari ◽  
Vladimir Brailovski ◽  
Mohammad Jahazi ◽  
...  
Keyword(s):  
Inconel 718 ◽  
Mechanical Performance ◽  
Solution Treatment ◽  
Heat Treatments ◽  
Powder Bed Fusion ◽  
Laser Powder Bed Fusion ◽  
Homogenization Treatment ◽  
Powder Bed ◽  
Post Process ◽  
High Fraction

In the present study, multi-objective optimization is employed to develop the optimum heat treatments that can achieve both high-mechanical performance and non-distinctive crystallographic texture of 3D printed Inconel 718 (IN718) fabricated by laser powder bed fusion (LPBF). Heat treatments including homogenization at different soaking times (2, 2.5, 3, 3.5 and 4 h) at 1080 °C, followed by a 1 h solution treatment at 980 °C and the standard aging have been employed. 2.5 h is found to be the homogenization treatment threshold after which there is a depletion of hardening precipitate constituents (Nb and Ti) from the γ-matrix. However, a significant number of columnar grains with a high fraction (37.8%) of low-angle grain boundaries (LAGBs) have still been retained after the 2.5 h homogenization treatment. After a 4 h homogenization treatment, a fully recrystallized IN718 with a high fraction of annealing twins (87.1%) is obtained. 2.5 and 4 h homogenization treatments result in tensile properties exceeding those of the wrought IN718 at both RT and 650 °C. However, considering the texture requirements, it is found that the 4 h homogenization treatment offers the optimum treatment, which can be used to produce IN718 components offering a balanced combination of high mechanical properties and adequate microstructural isotropy.

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.

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