Recent Advances in Optimization of Additive Manufacturing Processes

Special Issue Editors


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Guest Editor
Smart Manufacturing Lab, Department of Materials Science, Metallurgical Engineering and Inorganic Chemistry, Universidad de Cádiz, 11202 Algeciras, Spain
Interests: additive manufacturing; wire arc additive manufacturing (WAAM); advanced electron microscopy techniques for engineering materials characterization; materials processing and circular economy

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Guest Editor
Mechanical Engineering and Industrial Design, School of Engineering, University of Cadiz, 11519 Puerto Real, Cádiz, Spain
Interests: advanced manufacturing processes; manufacturing technologies; materials technology; additive manufacturing; advanced laser welding processes; texturing; renewable energies
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Guest Editor
Welding Technology Lab-LTS, Joinville Technology Center (CTJ), Federal University of Santa Catarina, Joinville 89219-600, Brazil
Interests: welding technologies; welding arc additive manufacturing; process instrumentation and automation; welding physics

Special Issue Information

Dear Colleagues,

Pursuing maximum efficiency, precision, and tolerance control remains a central focus in developing manufacturing processes. The significant advancements achieved in recent years within additive manufacturing, along with the continuous evolution of technology that has expanded its capabilities and applications, have positioned AM as a transformative force in modern manufacturing, capable of meeting the demands of various industries while offering unprecedented design flexibility and efficiency.

A significant number of additive manufacturing (AM) optimization cases have benefited from the integration of advanced computing and equipment sensing strategies. This integration facilitates a more responsive design process, allowing for real-time adjustments based on feedback from the manufacturing environment. Data-driven approaches enable optimization methods that utilize historical operational data to inform decision-making in the manufacturing process.

This Special Issue aims to explore all aspects of optimization in AM to assist manufacturers in producing efficient parts that excel in their intended applications.

Dr. David Sales
Dr. Severo Raul Fernandez-Vidal
Dr. Tiago Vieira Da Cunha
Guest Editors

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Keywords

  • performance optimization
  • additive manufacturing constraints
  • smart sensing technologies
  • simulation and modeling
  • generative design
  • topology and shape optimization
  • closed-loop control systems
  • support structure optimization

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Published Papers (1 paper)

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Research

19 pages, 29170 KiB  
Article
Influence of Printing Parameters on the Morphological Characteristics of Plasma Directed Energy-Deposited Stainless Steel
by Luis Segovia-Guerrero, Antonio José Gil-Mena, Nuria Baladés, David L. Sales, Carlota Fonollá, María de la Mata and María de Nicolás-Morillas
J. Manuf. Mater. Process. 2024, 8(5), 233; https://doi.org/10.3390/jmmp8050233 - 15 Oct 2024
Viewed by 1164
Abstract
This study investigated the influence of printing parameters and strategies on the morphological characteristics of austenitic stainless steel beads deposited on carbon steel substrates, using plasma directed energy deposition (DED). The experimental setup varied the welding current, wire feed speed, and torch travel [...] Read more.
This study investigated the influence of printing parameters and strategies on the morphological characteristics of austenitic stainless steel beads deposited on carbon steel substrates, using plasma directed energy deposition (DED). The experimental setup varied the welding current, wire feed speed, and torch travel speed, and we analyzed three printing strategies: simple-linear, overlapping, and oscillating. Moreover, advanced 3D scanning and computational analysis were used to assess the key morphological features, including bead width and height. The results showed that the computational model developed by using parabolic assumptions accurately predicted the geometric outcomes of the overlapping beads. The oscillating printing strategy was the one that showed improved morphological uniformity and bead substrate wettability, so these features were used for multi-layer component manufacturing. The use of equivalent wavelength–amplitude values resulted in maximum combinations of bead height and width. Moreover, cost-effective carbon steel substrates were feasibly used in microstructural and elemental analyses, with the latter ones confirming the alignment of the bead composition with the wire-fed material. Overall, this study provides practical insights for optimizing plasma DED processes, thus enhancing the efficiency and quality of metal component manufacturing. Full article
(This article belongs to the Special Issue Recent Advances in Optimization of Additive Manufacturing Processes)
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