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Authors = Ayush Pratap ORCID = 0000-0003-3852-7054

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35 pages, 2817 KiB  
Review
A Synergic Approach of Deep Learning towards Digital Additive Manufacturing: A Review
by Ayush Pratap, Neha Sardana, Sapdo Utomo, John Ayeelyan, P. Karthikeyan and Pao-Ann Hsiung
Algorithms 2022, 15(12), 466; https://doi.org/10.3390/a15120466 - 8 Dec 2022
Cited by 7 | Viewed by 5174
Abstract
Deep learning and additive manufacturing have progressed together in the previous couple of decades. Despite being one of the most promising technologies, they have several flaws that a collaborative effort may address. However, digital manufacturing has established itself in the current industrial revolution [...] Read more.
Deep learning and additive manufacturing have progressed together in the previous couple of decades. Despite being one of the most promising technologies, they have several flaws that a collaborative effort may address. However, digital manufacturing has established itself in the current industrial revolution and it has slowed down quality control and inspection due to the different defects linked with it. Industry 4.0, the most recent industrial revolution, emphasizes the integration of intelligent production systems and current information technologies. As a result, deep learning has received a lot of attention and has been shown to be quite effective at understanding image data. This review aims to provide a cutting-edge deep learning application of the AM approach and application. This article also addresses the current issues of data privacy and security and potential solutions to provide a more significant dimension to future studies. Full article
(This article belongs to the Collection Featured Reviews of Algorithms)
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