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Advances in Directed Energy Deposition Additive Manufacturing
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Advances in Directed Energy Deposition Additive Manufacturing

A special issue of Journal of Manufacturing and Materials Processing (ISSN 2504-4494).

Deadline for manuscript submissions: 30 June 2024 | Viewed by 2121

Special Issue Editors

Dr. Zhichao Liu

E-Mail Website
Guest Editor
Department of Industrial and Management Systems Engineering, West Virginia University, 1306 Evansdale Drive, Morgantown, WV 26506, USA.
Interests: additive manufacturing; material science; sustainable manufacturing
Dr. Yingbin Hu

E-Mail Website
Guest Editor
Department of Mechanical and Manufacturing Engineering, Miami University, 650 E High St. Oxford, OH 45056, USA
Interests: additive manufacturing; 4D printing; acoustic field-assisted AM
Special Issues, Collections and Topics in MDPI journals
Dr. Dazhong Wu

E-Mail Website
Guest Editor
Department of Mechanical and Aerospace Engineering, University of Central Florida, 12760 Pegasus Drive, Orlando, FL 32816, USA
Interests: smart manufacturing; additive manufacturing; engineering design
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Directed energy deposition (DED) additive manufacturing (AM) has been recognized as an efficient and sustainable technology in advanced manufacturing. Over the past few years, considerable discussion has been made to promote DED AM for better performance in manufacturing. The discussions focus on basic theoretical research, process optimization and control, technology innovation and industrial applications. Although DED technology is growing rapidly worldwide, many scientific and technical challenges need attention to make this technology platform more versatile. The challenges include complex phase transformations and microstructural changes, non-uniform residual stresses and distortions, porosity, lack of fusion and cracking, etc.

In this Special Issue of JMMP, we are looking for recent advances in DED technology, including material development, process design and optimization, physical characteristics, defects, challenges and applications. We are interested in contributions that focus on topics such as:

  • Laser–material interaction mechanisms;
  • Melt pool thermal behavior modeling and simulation;
  • Process optimization, in situ process monitoring and feedback control;
  • Mechanical characteristics and behaviors;
  • Defect formation mechanisms and characterization;
  • DED-based hybrid additive manufacturing.

Dr. Zhichao Liu
Dr. Yingbin Hu
Dr. Dazhong Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Manufacturing and Materials Processing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • directed energy deposition
  • process optimization
  • characterization
  • hybrid manufacturing
  • interaction mechanisms

Published Papers (5 papers)

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Research

16 pages, 2122 KiB  
Article
Ensuring Melt Track Width Consistency and Crack-Free Conditions Using Interpass-Temperature-Dependent Process Parameters for Wire-Arc-Directed Energy-Deposited Inconel 718
by Xavier A. Jimenez, Jie Song, Yao Fu and Albert C. To
J. Manuf. Mater. Process. 2024, 8(4), 140; https://doi.org/10.3390/jmmp8040140 (registering DOI) - 28 Jun 2024
Viewed by 100
Abstract
Melt track width can vary in a wire-arc-directed energy-deposited material (DED) using a constant set of process parameters, leading to a lower-quality build. In this work, a novel framework is proposed that uses the data from the process parameter development stage to create [...] Read more.
Melt track width can vary in a wire-arc-directed energy-deposited material (DED) using a constant set of process parameters, leading to a lower-quality build. In this work, a novel framework is proposed that uses the data from the process parameter development stage to create optimized process parameters for a target layer width at different interpass temperatures without hot cracking. Inconel 718 is used as the model material since it is known to suffer from hot cracking during DED processing. In the proposed framework, a process window containing a few sets of process parameters (torch travel speed and wire feed rate) is established for crack-free deposition of Inconel 718, and these parameters are used to create a small database. A linear regression model is then employed to generate interpass-temperature-specific optimized process parameters for a target melt track width. The results demonstrate that the proposed approach can reduce the melt track width variation in the deposited walls from 12% to 3% error on average under different printing conditions. It also demonstrates that interpass temperature (IPT) can be used as a controlled variable and the optimized process parameters as initial values when applying control techniques to the process. Full article
(This article belongs to the Special Issue Advances in Directed Energy Deposition Additive Manufacturing)
17 pages, 10529 KiB  
Article
Heat Input Control Strategies in DED
by Sergei Egorov, Fabian Soffel, Timo Schudeleit, Markus Bambach and Konrad Wegener
J. Manuf. Mater. Process. 2024, 8(4), 136; https://doi.org/10.3390/jmmp8040136 - 27 Jun 2024
Viewed by 235
Abstract
In the context of directed energy deposition (DED), the production of complex components necessitates precise control of all processing parameters while mitigating undesirable factors like heat accumulation. This research seeks to explore and validate with various materials the impact of a geometry-based analytical [...] Read more.
In the context of directed energy deposition (DED), the production of complex components necessitates precise control of all processing parameters while mitigating undesirable factors like heat accumulation. This research seeks to explore and validate with various materials the impact of a geometry-based analytical model for minimizing heat input on the characteristics and structure of the resultant DED components. Furthermore, it aims to compare this approach with other established methods employed to avoid heat accumulation during production. The geometry of the fabricated specimens was assessed using a linear laser scanner, cross-sections were analyzed through optical microscopy, and the effect on mechanical properties was determined via microhardness measurements. The specimens manufactured using the developed analytical model exhibited superior geometric precision with lower energy consumption without compromising mechanical properties. Full article
(This article belongs to the Special Issue Advances in Directed Energy Deposition Additive Manufacturing)
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21 pages, 44243 KiB  
Article
Evaluation of Porosity in AISI 316L Samples Processed by Laser Powder Directed Energy Deposition
by Alessandro Salmi, Gabriele Piscopo, Adriano Nicola Pilagatti and Eleonora Atzeni
J. Manuf. Mater. Process. 2024, 8(4), 129; https://doi.org/10.3390/jmmp8040129 - 24 Jun 2024
Viewed by 236
Abstract
Directed energy deposition-laser beam/powder (DED-LB/Powder) is an additive manufacturing process that is gaining popularity in the manufacturing industry due to its numerous advantages, particularly in repairing operations. However, its application is often limited to case studies due to some critical issues that need [...] Read more.
Directed energy deposition-laser beam/powder (DED-LB/Powder) is an additive manufacturing process that is gaining popularity in the manufacturing industry due to its numerous advantages, particularly in repairing operations. However, its application is often limited to case studies due to some critical issues that need to be addressed, such as the degree of internal porosity. This paper investigates the effect of the most relevant process parameters of the DED-LB/Powder process on the level and distribution of porosity. Results indicate that, among the process parameters examined, porosity is less affected by travel speed and more influenced by powder mass flow rate and laser power. Additionally, a three-dimensional finite element transient model was introduced, which was able to predict the development and location of lack-of-fusion pores along the building direction. Full article
(This article belongs to the Special Issue Advances in Directed Energy Deposition Additive Manufacturing)
19 pages, 9216 KiB  
Article
Monitoring Variability in Melt Pool Spatiotemporal Dynamics (VIMPS): Towards Proactive Humping Detection in Additive Manufacturing
by Mohamed Abubakr Hassan, Mahmoud Hassan, Chi-Guhn Lee and Ahmad Sadek
J. Manuf. Mater. Process. 2024, 8(3), 114; https://doi.org/10.3390/jmmp8030114 - 29 May 2024
Viewed by 519
Abstract
Humping is a common defect in direct energy deposition processes that reduces the geometric integrity of printed products. The available literature on humping detection is deemed reactive, as they focus on detecting late-stage melt pool spatial abnormalities. Therefore, this work introduces a novel, [...] Read more.
Humping is a common defect in direct energy deposition processes that reduces the geometric integrity of printed products. The available literature on humping detection is deemed reactive, as they focus on detecting late-stage melt pool spatial abnormalities. Therefore, this work introduces a novel, proactive indicator designed to detect early-stage spatiotemporal abnormalities. Specifically, the proposed indicator monitors the variability of instantaneous melt pool solidification-front speed (VIMPS). The solidification front dynamics quantify the intensity of cyclic melt pool elongation induced by early-stage humping. VIMPS tracks the solidification front dynamics based on the variance in the melt pool infrared radiations. Qualitative and quantitive analysis of the collected infrared data confirms VIMPS’s utility in reflecting the intricate humping-induced dynamics and defects. Experimental results proved VIMPS’ proactivity. By capturing early spatiotemporal abnormalities, VIMPS predicted humping by up to 10 s before any significant geometric defects. In contrast, current spatial abnormality-based methods failed to detect humping until 20 s after significant geometric defects had occurred. VIMPS’ proactive detection capabilities enable effective direct energy deposition control, boosting the process’s productivity and quality. Full article
(This article belongs to the Special Issue Advances in Directed Energy Deposition Additive Manufacturing)
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14 pages, 4717 KiB  
Article
Exploring Multi-Armed Bandit (MAB) as an AI Tool for Optimising GMA-WAAM Path Planning
by Rafael Pereira Ferreira, Emil Schubert and Américo Scotti
J. Manuf. Mater. Process. 2024, 8(3), 99; https://doi.org/10.3390/jmmp8030099 - 15 May 2024
Viewed by 601
Abstract
Conventional path-planning strategies for GMA-WAAM may encounter challenges related to geometrical features when printing complex-shaped builds. One alternative to mitigate geometry-related flaws is to use algorithms that optimise trajectory choices—for instance, using heuristics to find the most efficient trajectory. The algorithm can assess [...] Read more.
Conventional path-planning strategies for GMA-WAAM may encounter challenges related to geometrical features when printing complex-shaped builds. One alternative to mitigate geometry-related flaws is to use algorithms that optimise trajectory choices—for instance, using heuristics to find the most efficient trajectory. The algorithm can assess several trajectory strategies, such as contour, zigzag, raster, and even space-filling, to search for the best strategy according to the case. However, handling complex geometries by this means poses computational efficiency concerns. This research aimed to explore the potential of machine learning techniques as a solution to increase the computational efficiency of such algorithms. First, reinforcement learning (RL) concepts are introduced and compared with supervised machining learning concepts. The Multi-Armed Bandit (MAB) problem is explained and justified as a choice within the RL techniques. As a case study, a space-filling strategy was chosen to have this machining learning optimisation artifice in its algorithm for GMA-AM printing. Computational and experimental validations were conducted, demonstrating that adding MAB in the algorithm helped to achieve shorter trajectories, using fewer iterations than the original algorithm, potentially reducing printing time. These findings position the RL techniques, particularly MAB, as a promising machining learning solution to address setbacks in the space-filling strategy applied. Full article
(This article belongs to the Special Issue Advances in Directed Energy Deposition Additive Manufacturing)
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