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IEEE/ICACT20250115 Slide.04        [Big Slide]       [YouTube]	Oral Presentation
	Introduction-> In recent years, the manufacturing industry has seen a significant shift toward automation, driven by the need for enhanced operational efficiency and rrigorous quality control measures. Traditional welding methods often face challenges in achieving uniformity and precision, leading to defects and costly rework Integration of machine learning techniques presents a compelling solution to these challenges Research has demonstrated effectiveness of SVM and Neural Networks in predicting welding outcomes Decision Tree algorithms offer interpretable models that can aid operators in making informed decisions

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