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Influence of experience level on determining weld diameter in resistance spot welding
Christian Mathiszik, Benedikt Nopper, Johannes Koal, Uwe Füssel and Hans Christian Schmale Welding in the World 69(2) 483 (2025) https://doi.org/10.1007/s40194-024-01893-4
In-process prediction of weld penetration depth using machine learning-based molten pool extraction technique in tungsten arc welding
Optimization of weld penetration prediction based on weld pool image and deep learning approach in gas tungsten arc welding
Daehyun Baek, Hyeong Soon Moon and Sang-Hu Park The International Journal of Advanced Manufacturing Technology 130(5-6) 2617 (2024) https://doi.org/10.1007/s00170-023-12855-3
Study on precise weld diameter validations by comparing destructive testing methods in resistance spot welding
Data-driven cyber-physical system framework for connected resistance spot welding weldability certification
Fahim Ahmed, Noor-E Jannat, Daniel Schmidt and Kyoung-Yun Kim Robotics and Computer-Integrated Manufacturing 67 102036 (2021) https://doi.org/10.1016/j.rcim.2020.102036
A novel real-time measurement method for dynamic resistance signal in medium-frequency DC resistance spot welding
Performance analysis and comparison of machine learning algorithms for predicting nugget width of resistance spot welding joints
Saeed Zamanzad Gavidel, Shiyong Lu and Jeremy L. Rickli The International Journal of Advanced Manufacturing Technology 105(9) 3779 (2019) https://doi.org/10.1007/s00170-019-03821-z
A Conceptual Framework for Cyber-physical System in Connected RSW Weldability Certification