Optimization of Weld Qualities in Various Welding Operations Using Advanced Computational Techniques: A Comprehensive Review

This study explores various computational methodologies for optimizing the weld-bead geometry and parameters in different welding processes. It encompasses a range of techniques, including linear progression, response surface methodology, artificial neural networks, Taguchi techniques, and genetic algorithms. The optimization of process parameters significantly impacts productivity, quality, and production costs. This review highlights the profound effects of these optimization methodologies on manufacturing processes and demonstrates their integral role in welding. Detailed insights into each method are provided, forming a robust foundation for further research and development in welding procedure optimization.