Comparison of the EHLA and LPBF Process in Context of New Alloy Design Methods for LPBF

2021 ◽  
Vol 1161 ◽  
pp. 13-25
Author(s):  
Stephan Koß ◽  
Simon Ewald ◽  
Marie-Noemi Bold ◽  
Jan Hendrik Koch ◽  
Maximilian Voshage ◽  
...  

Additive Manufacturing (AM) processes are becoming more and more important for production of parts with increasing geometrical complexity and functionality. However, to draw on the full potential of AM technologies, alloys that exploit process inherent particularities such as extremely high cooling rates (ca. 106 K/s) have to be developed. One of most important AM-processes is Laser Powder Bed Fusion (LPBF), a batch-wise process. This complicates experimental alloy development and increases the use of powder resources since only one chemical composition can be tested within one test job and the process chamber has to be cleaned carefully in between. The process Extreme High-Speed Laser Material Deposition (EHLA) has been found to have similar cooling rates as LPBF, however it uses an in situ supply of powders which allows an easy switching between materials and has potential for rapid alloy development methods. Since the mechanical properties of materials primarily depend on chemical composition and microstructure, which in turn depends heavily on the cooling rates in the production process, the EHLA-process could be used as a means for an accelerated alloy development for LPBF. However, to explore this possibility, a thorough comparison of the two processes has to be performed.In this work, EHLA and LPBF processes are compared and evaluated regarding the following characteristics: process parameters, laser intensities and volume energy densities, resulting microstructure (primary dendrite arm spacing, DAS), melt pool size and shape. The reference samples were manufactured using one set of LPBF process parameters and EHLA samples were manufactured using three different sets of process parameters.The volume energy densities Ev [J/mm³] of the processes were found to differ by a factor 2.4 with higher Ev observed in LPBF. However, considering that approximately 2 to 3 layers are remelted with each pass of the laser beam, the introduced Ev per pass approximates the Ev introduced in the EHLA process. The melt pool size as seen in a cross section in the EHLA-manufactured samples is approximately 25 times larger than in the LPBF-manufactured samples and its depth to width ratio (d/w ratio) can be attributed to a heat conduction welding process while the d/w ratio observed in the LPBF-manufactured sample suggests a transition process between heat conduction welding and deep welding. The observed DAS is in the same order of magnitude for both processes ranging from 0.55 to 1.15 µm in EHLA-manufactured samples and 0.73 µm in the LPBF-manufactured reference sample. Since the resulting microstructures of samples manufactured with both processes show this common feature and EHLA process parameters can be adjusted to control the cooling rates, the transferability between EHLA- and LPBF-processes is supported in this first investigation. Research for a more efficient alloy development for LPBF using EHLA will be continued by e.g. examining chemical compositions and performing mechanical testing.

Metals ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 87
Author(s):  
Faiyaz Ahsan ◽  
Jafar Razmi ◽  
Leila Ladani

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.


Author(s):  
Yong Ren ◽  
Qian Wang ◽  
Panagiotis (Pan) Michaleris

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.


Author(s):  
Brian T. Gibson ◽  
Paritosh Mhatre ◽  
Michael C. Borish ◽  
Justin L. West ◽  
Emma D. Betters ◽  
...  

Abstract This article highlights work at Oak Ridge National Laboratory’s Manufacturing Demonstration Facility to develop closed-loop, feedback control for laser-wire based Directed Energy Deposition, a form of metal Big Area Additive Manufacturing (m-BAAM), a process being developed in partnership with GKN Aerospace specifically for the production of Ti-6Al-4V pre-forms for aerospace components. A large-scale structural demonstrator component is presented as a case-study in which not just control, but the entire 3D printing workflow for m-BAAM is discussed in detail, including design principles for large-format metal AM, toolpath generation, parameter development, process control, and system operation, as well as post-print net-shape geometric analysis and finish machining. In terms of control, a multi-sensor approach has been utilized to measure both layer height and melt pool size, and multiple modes of closed-loop control have been developed to manipulate process parameters (laser power, print speed, deposition rate) to control these variables. Layer height control and melt pool size control have yielded excellent local (intralayer) and global (component-level) geometry control, and the impact of melt pool size control in particular on thermal gradients and material properties is the subject of continuing research. Further, these modes of control have allowed the process to advance to higher deposition rates (exceeding 7.5 lb/hr), larger parts (1-meter scale), shorter build times, and higher overall efficiency. The control modes are examined individually, highlighting their development, demonstration, and lessons learned, and it is shown how they operate concurrently to enable the printing of a large-scale, near net shape Ti-6Al-4V component.


Author(s):  
Bo Cheng ◽  
Steven Price ◽  
James Lydon ◽  
Kenneth Cooper ◽  
Kevin Chou

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.


2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Chengjian Zheng ◽  
John T. Wen ◽  
Mamadou Diagne

Abstract Temperature control is essential for regulating material properties in laser-based manufacturing. Motion and power of the scanning laser affect local temperature evolution, which in turn determines the a posteriori microstructure. This paper addresses the problem of adjusting the laser speed and power to achieve the desired values of key process parameters: cooling rate and melt pool size. The dynamics of a scanning laser system is modeled by a one-dimensional (1D) heat conduction equation, with laser power as the heat input and heat dissipation to the ambient. Since the model is 1D, length and size are essentially the same. We pose the problem as a regulation problem in the (moving) laser frame. The first step is to obtain the steady-state temperature distribution and the corresponding input based on the desired cooling rate and melt pool size. The controller adjusts the input around the steady-state feedforward based on the deviation of the measured temperature field from the steady-state distribution. We show that with suitably defined outputs, the system is strictly passive from the laser motion and power. To avoid over-reliance on the model, the steady-state laser speed and power are adaptively updated, resulting in an integral-like update law for the feedforward. Moreover, the heat transfer coefficient to the ambient may be uncertain, and can also be adaptively updated. The final form of the control law combines passive error temperature field feedback with adaptive feedforward and parameter estimation. The closed-loop asymptotical stability is shown using the Lyapunov arguments, and the controller performance is demonstrated in a simulation.


2020 ◽  
Vol 143 (5) ◽  
Author(s):  
Fuda Ning ◽  
Dayue Jiang ◽  
Zhichao Liu ◽  
Hui Wang ◽  
Weilong Cong

Abstract Ultrasonic vibration-assisted (UV-A) directed energy deposition (DED) has become a promising technology to improve the as-built quality and mechanical performance of metal parts. Ultrasonic frequency, a critical parameter of the ultrasonic vibration, can remarkably affect the ultrasonic vibration behaviors in assisting DED processes. However, leveraging varied ultrasonic frequencies in UV-A DED attracts little attention, and the effects of ultrasonic frequency have been thus overlooked. Linking ultrasonic frequency and part performance emphasizes the need for an understanding of the underlying thermodynamics in the melt pool due to the key role of thermal history in the DED process. In this work, we fabricated Inconel 718 (IN718) parts using the UV-A DED process under different levels of ultrasonic vibration frequency (including 0, 25 kHz, 33 kHz, and 41 kHz). For the first time, melt pool size, temperature distribution, and peak temperature within the melt pool, as well as the peak temperature fluctuation within a layer deposition, were studied. Porosity and thermal-dependent properties including grain size and microhardness were also investigated. The results indicated that the increase in ultrasonic frequency led to an increase in both melt pool size and peak temperature. Moreover, the lowest porosity was obtained at an ultrasonic frequency of 25 kHz, while grain refinement and microhardness enhancement were achieved at the highest frequency of 41 kHz. This investigation provides great insights into the link among ultrasonic frequency, melt pool formation, temperature field, porosity, and thermal-dependent properties in the UV-A DED-built IN718 parts.


2019 ◽  
Vol 31 (2) ◽  
pp. 022305 ◽  
Author(s):  
Matteo Pacher ◽  
Luca Mazzoleni ◽  
Leonardo Caprio ◽  
Ali Gökhan Demir ◽  
Barbara Previtali

Author(s):  
Brian T. Gibson ◽  
Brad S. Richardson ◽  
Taylor W. Sundermann ◽  
Lonnie J. Love

A variety of techniques have been utilized in metal additive manufacturing (AM) for melt pool size management, including modeling and feed-forward approaches. In a few cases, closed-loop control has been demonstrated. In this research, closed-loop melt pool size control for large-scale, laser-wire based Directed Energy Deposition is demonstrated with a novel modification: site-specific changes to the controller set-point were commanded at trigger points, the locations of which were generated by the projection of a secondary geometry onto the primary 3D-printed component geometry. The present work shows that, through this technique, it is possible to print a specific geometry that occurs beyond the actual toolpath of the print head. This is denoted as an extra-toolpath geometry and is fundamentally different from other methods of generating component features in metal AM. A proof-of-principle experiment is presented in which a complex oak leaf geometry was embossed on an otherwise ordinary double-bead wall made from Ti-6Al-4V. The process is introduced and characterized primarily from a controls perspective with reports on the performance of the control system, the melt pool size response, and the resulting geometry. The implications of this capability, which extend beyond localized control of bead geometry to the potential mitigations of defects and functional grading of component properties, are discussed.


2008 ◽  
Vol 384 ◽  
pp. 213-227 ◽  
Author(s):  
Shou Jin Sun ◽  
Milan Brandt

The melt pool size of a single-track clad in the laser cladding of Hastelloy C, a Nickel based alloy, on mild steel substrate has been investigated. The effect of laser processing parameters, such as laser power density, scan rate and powder mass flow rate on the melt pool size has been examined. It was found that the melt pool size is strictly controlled by the melt pool temperature which increases with laser power but decreases with increasing scan rate and powder mass flow rate. The melt pool size is critical for the clad formation in terms of clad height and dilution with the substrate. The clad height increases linearly with the ratio of melt pool size to powder stream diameter while the dilution is an exponential function of the ratio of melt pool size to laser spot size.


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