Improving process stability of electron beam directed energy deposition by closed-loop control of molten pool

Liang, Zhiyue; Liao, Zhen‐Yu; Zhang, Haoyu; Li, Zixiang; Wang, Li; Chang, Baohua; Du, Dong

doi:10.1016/j.addma.2023.103638

Cited by 3 publications

(1 citation statement)

References 24 publications

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“…DED processes utilize wire or powder as the feedstock [10,[17][18][19] with various heat sources, including lasers, electron beams, electrical arcs, and plasma, employed for the deposition process. Depending on the type of selected heat source, DED processes can be classified into electron beam DED (EB-DED) [20], laser DED (LDED) [21], plasma DED (P-DED) [22], and wire arc DED (WAAM) [23][24][25][26]. Each type of DED process offers advantages and disadvantages, making them more suitable for distinct applications [27,28].…”

Section: Introductionmentioning

confidence: 99%

A Review on Wire-Laser Directed Energy Deposition: Parameter Control, Process Stability, and Future Research Paths

Ghanadi,

Pasebani

2024

JMMP

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Wire-laser directed energy deposition has emerged as a transformative technology in metal additive manufacturing, offering high material deposition efficiency and promoting a cleaner process environment compared to powder processes. This technique has gained attention across diverse industries due to its ability to expedite production and facilitate the repair or replication of valuable components. This work reviews the state-of-the-art in wire-laser directed energy deposition to gain a clear understanding of key process variables and identify challenges affecting process stability. Furthermore, this paper explores modeling and monitoring methods utilized in the literature to enhance the final quality of fabricated parts, thereby minimizing the need for repeated experiments, and reducing material waste. By reviewing existing literature, this paper contributes to advancing the current understanding of wire-laser directed energy deposition technology. It highlights the gaps in the literature while underscoring research needs in wire-laser directed energy deposition.

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Section: Introductionmentioning

confidence: 99%

A Review on Wire-Laser Directed Energy Deposition: Parameter Control, Process Stability, and Future Research Paths

Ghanadi,

Pasebani

2024

JMMP

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Enhancing additive manufacturing with computer vision: a comprehensive review

Yu,

Li,

et al. 2024

Int J Adv Manuf Technol

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Imaging systems and techniques for fusion-based metal additive manufacturing: a review

Balhara,

Karthikeyan,

Hanchate

et al. 2023

Front. Manuf. Technol.

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This study presents an overview and a few case studies to explicate the transformative power of diverse imaging techniques for smart manufacturing, focusing largely on various in-situ and ex-situ imaging methods for monitoring fusion-based metal additive manufacturing (AM) processes such as directed energy deposition (DED), selective laser melting (SLM), electron beam melting (EBM). In-situ imaging techniques, encompassing high-speed cameras, thermal cameras, and digital cameras, are becoming increasingly affordable, complementary, and are emerging as vital for real-time monitoring, enabling continuous assessment of build quality. For example, high-speed cameras capture dynamic laser-material interaction, swiftly detecting defects, while thermal cameras identify thermal distribution of the melt pool and potential anomalies. The data gathered from in-situ imaging are then utilized to extract pertinent features that facilitate effective control of process parameters, thereby optimizing the AM processes and minimizing defects. On the other hand, ex-situ imaging techniques play a critical role in comprehensive component analysis. Scanning electron microscopy (SEM), optical microscopy, and 3D-profilometry enable detailed characterization of microstructural features, surface roughness, porosity, and dimensional accuracy. Employing a battery of Artificial Intelligence (AI) algorithms, information from diverse imaging and other multi-modal data sources can be fused, and thereby achieve a more comprehensive understanding of a manufacturing process. This integration enables informed decision-making for process optimization and quality assurance, as AI algorithms analyze the combined data to extract relevant insights and patterns. Ultimately, the power of imaging in additive manufacturing lies in its ability to deliver real-time monitoring, precise control, and comprehensive analysis, empowering manufacturers to achieve supreme levels of precision, reliability, and productivity in the production of components.

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Improving process stability of electron beam directed energy deposition by closed-loop control of molten pool

Cited by 3 publications

References 24 publications

A Review on Wire-Laser Directed Energy Deposition: Parameter Control, Process Stability, and Future Research Paths

A Review on Wire-Laser Directed Energy Deposition: Parameter Control, Process Stability, and Future Research Paths

Enhancing additive manufacturing with computer vision: a comprehensive review

Imaging systems and techniques for fusion-based metal additive manufacturing: a review

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