Ultrasonic Welding, Cutting & Intelligent Manufacturing

Ultrasonic manufacturing is widely used for welding, cutting, and processing metals, polymers, composites, and dissimilar materials, offering advantages in efficiency, energy use, and joint quality. However, variations in material properties, tool conditions, and process parameters can cause defects and inconsistent product quality. While physics-based models and experimental methods have improved the understanding of ultrasonic processes, challenges remain in achieving reliable real-time monitoring, accurate defect prediction, and automated process control. Recent advances in deep learning, including convolutional and recurrent neural networks, offer new opportunities for automated flaw detection, quality classification, and process assessment, yet the integration of physics-based modeling with data-driven methods remains underdeveloped.This Research Topic aims to bring together cutting-edge research on physics-based ultrasonic modeling and AI-driven quality assessment. By bridging experimental ultrasonics with data-driven methodologies, it seeks to advance both fundamental understanding and industrial application of ultrasonic welding, cutting, and intelligent manufacturing. Contributions from academia and industry are welcome to address challenges in multi-material joining and cutting, tool condition monitoring, and process parameter optimization. Studies on materials characterization and microstructure–property correlations are also encouraged to establish structure–process–performance relationships.To gather further insights into ultrasonic welding, cutting, and intelligent manufacturing, we welcome contributions addressing, but not limited to, the following themes:• Ultrasonic welding of metals, polymers, and dissimilar materials• Ultrasonic cutting and machining of advanced composites• Real-time process monitoring and control using ultrasonic signals• Deep learning for defect detection and weld quality classification• Numerical simulation and finite element modeling of ultrasonic welding processes• Online parameter optimization using AI and machine learning• Materials characterization using SEM, EDS, EBSD, XRD, and TEM• Mechanical testing (tensile, hardness, fatigue, and fracture analysis)• Microstructure evolution and structure–property relationships in ultrasonic processes• Industrial case studies and scale-up of ultrasonic joining technologies Topic editors: Md Shafiqul Islam, Zeshan Abbas, Zhao Lun Source: https://www.frontiersin.org/research-topics/85428/ultrasonic-welding-cutting-intelligent-manufacturing