The Size Effect on Forming Quality of Ti–6Al–4V Solid Struts Fabricated via Laser Powder Bed Fusion

Laser powder bed fusion (LPBF) is useful for manufacturing complex structures; however, factors affecting the forming quality have not been clearly researched. This study aimed to clarify the influence of geometric characteristic size on the forming quality of solid struts. Ti–6Al–4V struts with a square section on the side length (0.4 to 1.4 mm) were fabricated with different scan speeds. Micro-computed tomography was used to detect the struts’ profile error and defect distribution. Scanning electron microscopy and light microscopy were used to characterize the samples’ microstructure. Nanoindentation tests were conducted to evaluate the mechanical properties. The experimental results illustrated that geometric characteristic size influenced the struts’ physical characteristics by affecting the cooling condition. This size effect became obvious when the geometric characteristic size and the scan speed were both relatively small. The solid struts with smaller geometric characteristic size had more obvious size error. When the geometric characteristic size was smaller than 1 mm, the nanohardness and elastic modulus increased with the increase in scan speed, and decreased with the decline of the geometric characteristic size. Therefore, a relatively high scan speed should be selected for LPBF—the manufacturing of a porous structure, whose struts have small geometric characteristic size.

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Influence of storage conditions and reconditioning of AlSi10Mg powder on the quality of parts produced by laser powder bed fusion (LPBF)

Additive Manufacturing ◽

10.1016/j.addma.2021.101896 ◽

2021 ◽

Vol 39 ◽

pp. 101896

Author(s):

Kirstin Riener ◽

Steffen Oswald ◽

Michael Winkler ◽

Gerhard J. Leichtfried

Keyword(s):

Storage Conditions ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Powder Bed

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Effect of Particle Size Distribution on Laser Powder Bed Fusion Manufacturability of Copper

BHM Berg- und Hüttenmännische Monatshefte ◽

10.1007/s00501-021-01107-0 ◽

2021 ◽

Author(s):

Massimiliano Bonesso ◽

Pietro Rebesan ◽

Claudio Gennari ◽

Simone Mancin ◽

Razvan Dima ◽

...

Keyword(s):

Mechanical Properties ◽

Particle Size ◽

Particle Size Distribution ◽

Size Distribution ◽

Physical And Mechanical Properties ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Powder Bed ◽

Cooling Channels ◽

Scan Speed

AbstractOne of the major benefits of the Laser Powder Bed Fusion (LPBF) technology is the possibility of fabrication of complex geometries and features in only one-step of production. In the case of heat exchangers in particular, this is very convenient for the fabrication of conformal cooling channels which can improve the performance of the heat transfer capability. Yet, obtaining dense copper parts printed via LPBF presents two major problems: the high reflectivity of 1 μm (the wavelength of commonly used laser sources) and the high thermal conductivity of copper that limits the maximum local temperature that can be attained. This leads to the formation of porous parts.In this contribution, the influence of the particle size distribution of the powder on the physical and mechanical properties of parts produced via LPBF is studied. Three copper powders lots with different particle size distributions are used in this study. The effect on densification from two laser scan parameters (scan speed and hatching distance) and the influence of contours scans on the lateral surface roughness is reported. Subsequently, samples manufactured with the optimal process parameters are tested for thermal and mechanical properties evaluation.

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

Volume 2: Additive Manufacturing; Materials ◽

10.1115/msec2017-2942 ◽

2017 ◽

Cited By ~ 6

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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Improving the quality of up-facing inclined surfaces in laser powder bed fusion of metals using a dual laser setup

Procedia CIRP ◽

10.1016/j.procir.2020.09.050 ◽

2020 ◽

Vol 94 ◽

pp. 266-269 ◽

Cited By ~ 1

Author(s):

Jitka Metelkova ◽

Daniel Ordnung ◽

Yannis Kinds ◽

Ann Witvrouw ◽

Brecht Van Hooreweder

Keyword(s):

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Powder Bed ◽

Inclined Surfaces ◽

Dual Laser ◽

Laser Setup

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

Materials ◽

10.3390/ma13183927 ◽

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.

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Design Rules and In-Situ Quality Monitoring of Thin-Wall Features Made Using Laser Powder Bed Fusion

Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing ◽

10.1115/msec2019-3035 ◽

2019 ◽

Cited By ~ 1

Author(s):

Aniruddha Gaikwad ◽

Farhad Imani ◽

Prahalad Rao ◽

Hui Yang ◽

Edward Reutzel

Keyword(s):

Neural Network ◽

Aspect Ratio ◽

Convolutional Neural Network ◽

Thin Wall ◽

Powder Bed Fusion ◽

Laser Powder Bed Fusion ◽

Design Rules ◽

Powder Bed

Abstract The goal of this work is to quantify the link between the design features (geometry), in-situ process sensor signatures, and build quality of parts made using laser powder bed fusion (LPBF) additive manufacturing (AM) process. This knowledge is critical for establishing design rules for AM parts, and to detecting impending build failures using in-process sensor data. As a step towards this goal, the objectives of this work are two-fold: 1) Quantify the effect of the geometry and orientation on the build quality of thin-wall features. To explain further, the geometry-related factor is the ratio of the length of a thin-wall (l) to its thickness (t) defined as the aspect ratio (length-to-thickness ratio, l/t), and the angular orientation (θ) of the part, which is defined as the angle of the part in the X-Y plane relative to the re-coater blade of the LPBF machine. 2) Assess the thin-wall build quality by analyzing images of the part obtained at each layer from an in-situ optical camera using a convolutional neural network. To realize these objectives, we designed a test part with a set of thin-wall features (fins) with varying aspect ratio from Titanium alloy (Ti-6Al-4V) material — the aspect ratio l/t of the thin-walls ranges from 36 to 183 (11 mm long (constant), and 0.06 mm to 0.3 mm in thickness). These thin-wall test parts were built under three angular orientations of 0°, 60°, and 90°. Further, the parts were examined offline using X-ray computed tomography (XCT). Through the offline XCT data, the build quality of the thin-wall features in terms of their geometric integrity is quantified as a function of the aspect ratio and orientation angle, which suggests a set of design guidelines for building thin-wall structures with LPBF. To monitor the quality of the thin-wall, in-process images of the top surface of the powder bed were acquired at each layer during the build process. The optical images are correlated with the post build quantitative measurements of the thin-wall through a deep learning convolutional neural network (CNN). The statistical correlation (Pearson coefficient, ρ) between the offline XCT measured thin-wall quality, and CNN predicted measurement ranges from 80% to 98%. Consequently, the impending poor quality of a thin-wall is captured from in-situ process data.

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