Directed Energy Deposition via Artificial Intelligence-Enabled Approaches

Directed Energy Deposition via Artificial Intelligence-Enabled Approaches

Additive manufacturing (AM) has been gaining pace, replacing traditional manufacturing methods. Moreover, artificial intelligence and machine learning implementation has increased for further applications and advancements. This review extensively follows all the research work and the contemporary si...

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Bibliographic Details
Published in:Complexity (New York, N.Y.) Vol. 2022; no. 1
Main Authors: Chadha, Utkarsh, Selvaraj, Senthil Kumaran, Lamsal, Aakrit Sharma, Maddini, Yashwanth, Ravinuthala, Abhishek Krishna, Choudhary, Bhawana, Mishra, Anirudh, Padala, Deepesh, M, Shashank, Lahoti, Vedang, Adefris, Addisalem, S, Dhanalakshmi
Format: Journal Article
Language:English
Published: Hoboken Hindawi 2022
Hindawi Limited
Hindawi-Wiley
Subjects:
Additive manufacturing
Artificial intelligence
Costs
Decision trees
Deposition
Gaussian process
Laser sintering
Machine learning
Manufacturing
Metals
Neural networks
Polymers
Production methods
Rapid prototyping
Raw materials
Support vector machines
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Summary:Additive manufacturing (AM) has been gaining pace, replacing traditional manufacturing methods. Moreover, artificial intelligence and machine learning implementation has increased for further applications and advancements. This review extensively follows all the research work and the contemporary signs of progress in the directed energy deposition (DED) process. All types of DED systems, feed materials, energy sources, and shielding gases used in this process are also analyzed in detail. Implementing artificial intelligence (AI) in the DED process to make the process less human-dependent and control the complicated aspects has been rigorously reviewed. Various AI techniques like neural networks, gradient boosted decision trees, support vector machines, and Gaussian process techniques can achieve the desired aim. These models implemented in the DED process have been trained for high-precision products and superior quality monitoring.
ISSN:1076-2787
1099-0526
DOI:10.1155/2022/2767371