Research Papers

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

[+] Author and Article Information
Bo Cheng, Steven Price

Department of Mechanical Engineering,
The University of Alabama,
Tuscaloosa, AL 35487

James Lydon, Kenneth Cooper

Additive Manufacturing Laboratory,
Marshall Space Flight Center,
Huntsville, AL 35812

Kevin Chou

Department of Mechanical Engineering,
The University of Alabama,
Tuscaloosa, AL 35487
e-mail: kchou@eng.ua.edu

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received April 15, 2014; final manuscript received August 30, 2014; published online October 24, 2014. Assoc. Editor: David L. Bourell.

This material is declared a work of the US Government and is not subject to copyright protection in the United States. Approved for public release; distribution is unlimited.

J. Manuf. Sci. Eng 136(6), 061018 (Oct 24, 2014) (12 pages) Paper No: MANU-14-1217; doi: 10.1115/1.4028484 History: Received April 15, 2014; Revised August 30, 2014

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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Fig. 1

Temperature dependent specific heat, density and thermal conductivity of Ti–6Al–4V [41-43]

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Fig. 2

Measured thermal conductivity of Ti–6Al–4V, solid and powder, at different temperatures

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Fig. 3

(a) Micro-CT scan image of Ti–6Al–4V specimen including preheated powder and (b) binary image for porosity analysis

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Fig. 4

Temperature dependent thermal conductivity

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Fig. 5

An illustration of thermal model and part geometry in FE simulations

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Fig. 6

Flow chart for subroutines used in FE simulations

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Fig. 7

CAD model used in EBAM fabrications and temperature measurements

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Fig. 8

SEM images of Ti–6Al–4V powder: (a) raw and (b) preheated (using the procedure designed for Ti-6Al-6V from Arcam)

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Fig. 9

Typical simulation result: (a) temperature contour with melt pool geometry, (b) temperature profile, and (c) cooling rate

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Fig. 10

Typical NIR result from EBAM: (a) temperature contour with insert showing melt pool size, (b) temperature profile, and (c) average temperature profile with standard deviation

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Fig. 11

(a) Sacrificial glass with two levels of metallization, (b) temperature difference due a transmission loss, and (c) transmission loss slope versus build height

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Fig. 12

Temperature profiles showing before and after compensations

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Fig. 13

Temperature comparisons between simulation and experiment (v = 632.6 mm/s, i = 6.7 mA, d = 0.55 mm): (a) contour and (b) profile

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Fig. 14

Model validation with another set of experiments with repeated tests (v = 728 mm/s, i = 7.2 mA, d = 0.55 mm)

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Fig. 15

Temperature contours and molten pool geometries for powder layer of various levels of porosity

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Fig. 16

Simulated melt pool sizes for different levels of powder porosity for the top layer

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Fig. 17

Simulated temperatures comparing profiles between using powder versus solid properties as the top layer




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