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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

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Paper Title:	MACHINE LEARNING AND DEEP LEARNING: THE FRICTION STIR WELDING AND PLASMA ARC WELDING PROCESS
Authors Name:	Anil Kumar , P. Dhilip Kumar , N.Tamiloli , V. Sountharasu
Unique Id:	IJSDR2312116
Published In:	Volume 8 Issue 12, December-2023
Abstract:	This paper examines how artificial intelligence systems can be applied in the welding Procedures. AI and profound learning techniques could be utilized to work on the productivity of different welding processes by tracking down answers for their issues. Utilizing AI calculations has been shown to significantly improve welding cycle proficiency and precision. Modern robots equipped with artificial intelligence are able to resolve a number of puzzling issues affecting the assembling industry. Several welding processes rely upon human capacity while picking ideal limits that are extremely feeble to human botch and less useful. To diminish this faith, robots and modified systems are arranged using mind networks fit for conveying unsurprising weld quality and further created efficiency. Artificial intelligence is similarly used to picture welding given that the visual audit is essential to choose weld quality. These procedures can moreover be worn to weigh up the explanations behind various prosperity risks using backslide assessment.
Keywords:	Artificial, Applied, Welding, Quality, etc.
Cite Article:	"MACHINE LEARNING AND DEEP LEARNING: THE FRICTION STIR WELDING AND PLASMA ARC WELDING PROCESS", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 12, page no.878 - 883, December-2023, Available :http://www.ijsdr.org/papers/IJSDR2312116.pdf
Downloads:	000338719
Publication Details:	Published Paper ID: IJSDR2312116 Registration ID:209697 Published In: Volume 8 Issue 12, December-2023 DOI (Digital Object Identifier): Page No: 878 - 883 Publisher: IJSDR \| www.ijsdr.org ISSN Number: 2455-2631

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