A systematic review of AI-assisted residual stress control in WAAM: real-time defect management and industrial implementation

The growing demands of the energy, automotive, oil and gas, chemical, steam power plant, and aerospace industries have precipitated a significant increase in the need for sophisticated manufacturing processes capable of fabricating high-quality components from materials susceptible to degradation at elevated temperatures. Wire-arc additive manufacturing (WAAM) has emerged as a promising technology to address these demands. This review paper provides a comprehensive analysis of the current state of WAAM, with a specific focus on its application in high-temperature material defect mitigation and repair. Initially, the fundamental principles of the WAAM process are delineated. Subsequently, recent advancements in WAAM technology are explored, encompassing multi-material deposition capabilities, strategies for managing residual stresses and defects, and the integration of artificial intelligence (AI-WAAM). This study discusses the challenges and limitations of WAAM, investigates potential solutions, and examines the enhancement of WAAM process quality through hybrid approaches that incorporate in-process monitoring and artificial intelligence. This review serves as a valuable resource for educators, engineers, and industry leaders seeking to optimise the utilisation of this rapidly evolving manufacturing technology.