IEEE/ICACT20250115 Slide.14        [Big Slide]       [YouTube] Oral Presentation
Conclusion We developed an effective machine-learning framework for optimizing welding processes, with a Decision Tree model showing superior predictive capability Strong correlation between power and thermal features provides valuable insights for parameter selection in industrial applications. Framework enhances quality control and establishes a foundation for automated decision-making in manufacturing. Systematic approach improves efficiency and reliability in industrial welding operations

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