چکیده مقاله
In recent years, the application of artificial intelligence AI in welding processes has emerged as one of the most effective approaches for improving quality and industrial productivity The purpose of this study is to provide a comprehensive review of recent advancements in the use of AI algorithms for monitoring, controlling, and optimizing various welding processes, including robotic welding and friction stir welding FSW This paper examines the role of artificial neural networks, adaptive neuro fuzzy systems, genetic algorithms, deep learning architectures, and hybrid intelligent models in weld quality prediction, defect detection, and optimal parameter adjustment The literature review indicates that integrating machine learning models with advanced sensing technologies significantly enhances the accuracy of mechanical property prediction, reduces defect occurrence, and improves process stability Nevertheless, challenges such as the shortage of real world data, the need for generalizable models, and computational complexity remain major obstacles to large scale industrial adoption Finally, future opportunities such as the implementation of digital twin technology and embedded AI in intelligent robotic welding systems—are discussed as promising directions for next generation smart welding
کلیدواژهها
نویسندگان
شیوه ارجاع
Sadeghi, Mojtaba,1404,Application of Artificial Intelligence in Optimization and Quality Control of Welding Processes: A Review of Recent Advances and Challenges,8th International Conference on Welding and Non Destructive Testing & 26th National Conference on Welding & Inspection & 15th National Conference on NDT & 4th National Conference on Additive Manufacturing,Tehran
ارائهشده در
مجموعه مقالات هشتمین کنفرانس بین المللی جوشکاری و آزمایش های غیرمخرب، بیست و ششمین کنفرانس ملی جوش و بازرسی، پانزدهمین کنفرانس ملی آزمایش های غیرمخرب و چهارمین کنفرانس ملی ساخت افزایشی20 بهمن 1404 · تهران