The influence of laser directed energy deposition (DED) processing parameters for Al5083 studied by central composite design

Svetlizky, David; Zheng, Baolong; Steinberg, David M.; Schoenung, Julie M.; Lavernia, Enrique J.; Eliaz, Noam

doi:10.1016/j.jmrt.2022.02.042

Cited by 36 publications

(16 citation statements)

References 61 publications

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“…Their investigation has concluded that the implementation of CCD was instrumental in predicting burr height, thrust and surface roughness with the help of mathematical models. A similar conclusion was drawn by the study conducted by David et al [23]. However, this investigation employed an RSM with a four-factor CCD based experimental design.…”

Section: Introductionsupporting

confidence: 80%

Machinability Study on AA6061/2 SiC / Graphite Hybrid Nanocomposites Fabricated through Ultrasonic Assisted Stir Casting

Lagisetti

A.²,

Sukjamsri³

et al. 2022

Int. J. Automot. Mech. Eng.

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Aluminium-based hybrid metal matrix nanocomposites (AA-HMNCs) have numerous applications due to their higher strength-to-weight ratio and good mechanical and tribological properties. However, the machinability aspect of these materials must be carefully explored before employing them in various engineering applications. The present study involves the fabrication of AA6061/2 wt.% SiC/x wt.% graphite (x= 1, 2, 3) hybrid nanocomposites and subsequently subjecting them to machinability investigation. All the hybrid nanocomposite samples are fabricated through ultrasonic assisted stir casting technique. The effect of machining parameters and graphite content of the sample on cutting force and surface roughness is discussed based on experimental data. Experiments are performed based on the central composite design of response surface methodology, and the corresponding output responses are recorded. ANOVA analysis revealed that the graphite content has the highest authority over surface roughness and cutting force. High cutting speeds accompanied by low feed and depth of cut have resulted in reduced cutting forces and better surface finish. Chip morphology studies have also subsequently indicated better machinability with increased graphite content.

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Section: Introductionsupporting

confidence: 80%

Machinability Study on AA6061/2 SiC / Graphite Hybrid Nanocomposites Fabricated through Ultrasonic Assisted Stir Casting

Lagisetti

A.²,

Sukjamsri³

et al. 2022

Int. J. Automot. Mech. Eng.

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“…Al alloys are indispensable materials used for industrial structural parts [52][53][54][55][56], but Al alloys are highly difficult to process with LDED due to the inherent characteristics of Al alloys [31][32][33]57], which will be discussed in detail below. [58].…”

Section: Challenges Associated With Intrinsic Characters Of Al Alloysmentioning

confidence: 99%

“…Porosities. The primary causes of porosities in LDED Al alloys involve (i) keyhole pores caused by excessive laser energy input; (ii) irregular-shaped lack-of-fusion pores due to insufficient laser energy input; (iii) metallurgical pores originated from gas entrapment into the melt pool; and (iv) porosities inherited from the feedstock [57,68,[82][83][84].…”

Section: 31mentioning

confidence: 99%

“…As for the Al-Zn, Al-Cu, and Al-Mg alloys, alloying elements with low boiling points, such as Zn and Mg, may quickly vaporize under the high energy input during the LDED process [39,57,82]. Svetlizky et al [39] have found that Al5083 powders acquired by gas atomization were transformed into Al5754 in composition due to the selective vaporization of elements during the LDED process.…”

Section: 31mentioning

confidence: 99%

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Review on laser directed energy deposited aluminum alloys

Liu,

Chen,

Qiu

et al. 2024

Int. J. Extrem. Manuf.

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The lightweight aluminum (Al) alloys have been widely used in frontier fields like aerospace and automotive industries, which attracts great interest in additive manufacturing to process high-value Al parts. As a mainstream additive manufacturing technique, laser directed energy deposition (LDED) shows good scalability to meet requirements for large-format components manufacturing and repairing. However, LDED Al alloys are highly challenging due to the inherent poor printability (e.g., low laser absorption, high oxidation sensitivity and cracking tendency). To further promote the development of LDED high-performance Al alloys, this review gains a deep understanding of the challenges and strategies to improve printability in LDED Al alloys. The porosity, cracking, distortion, inclusions, elements evaporation and resultant inferior mechanical properties (than laser powder bed fusion) are the key challenges in LDED Al alloys. Processing parameter optimizations, in-situ alloy design, reinforcing particle addition and field assistance are the efficient approaches to improve the printability and performance of LDED Al alloys. The underlying correlations between processes, alloy innovation, characteristic microstructures, and achievable performances in LDED Al alloys are discussed. The benchmarking mechanical properties and primary strengthening mechanism of LDED Al alloys are summarized. This review aims to provide a critical and in-depth evaluation of current progress in LDED Al alloys. The future opportunities and perspectives in LDED high-performance Al alloys are also outlooked.

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“…To improve the quality of 3D-printed parts, the processing parameters, affecting the melt pool dimensions and defects formation mechanisms are required to analyze [17][18][19][20][21][22]. Simonds et al [23] quantified the relationship between the laser power absorption and melt pool geometry of the samples made of Ti-6Al-4V powder.…”

Section: Introductionmentioning

confidence: 99%

A new data-driven framework for prediction of molten pool evolution and lack of fusion defects in multi-track multi-layer laser powder bed fusion processes

Parsazadeh

Wu²,

Sharma³

et al. 2022

Int J Adv Manuf Technol

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This study proposes a new data-driven approach to predict the area fraction of lack of fusion and morphology of 3D-printed parts produced using the laser powder bed fusion process. Different processing parameters were considered to develop this methodology, such as laser power, laser speed, hatch spacing, and layer thickness. Melt pool geometrical parameters were numerically predicted using a mathematical model optimized using the Nelder-Mead optimization method and a machine learning model. The Gaussian process was later employed to further modify the layerwise deposition. The accuracy of the proposed methodology was then extended to predictions of the area fraction of lack of fusion and the morphological aspects of the melt pools in 3D-printed parts by comparing them with the experimental observations. The results revealed that this data-driven approach, which is independent of the thermophysical properties of the material, is capable of reasonably predicting the area fraction of lack-of-fusion formed during materials deposition using the laser powder bed fusion process.

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The influence of laser directed energy deposition (DED) processing parameters for Al5083 studied by central composite design

Cited by 36 publications

References 61 publications

Machinability Study on AA6061/2 SiC / Graphite Hybrid Nanocomposites Fabricated through Ultrasonic Assisted Stir Casting

Machinability Study on AA6061/2 SiC / Graphite Hybrid Nanocomposites Fabricated through Ultrasonic Assisted Stir Casting

Review on laser directed energy deposited aluminum alloys

A new data-driven framework for prediction of molten pool evolution and lack of fusion defects in multi-track multi-layer laser powder bed fusion processes

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