Artificial Intelligence in Aerospace Engineering: Analysing the integration of AI in design, manufacturing, and maintenance processes

Artificial Intelligence (AI) is increasingly transforming the aerospace engineering sector, influencing design, manufac- turing, and maintenance processes. In aerospace design, AI algorithms enable generative design and optimization, allowing for innovative and efficient solutions that were previously unfeasible. Machine learning (ML) techniques play a significant role in enhancing aerodynamic analysis and material selection, reducing time and costs associated with traditional design methods. In manufacturing, AI facilitates automation, improves quality control, and aids in predictive maintenance, contributing to more efficient production cycles and fewer errors. Moreover, AI’s application in additive manufacturing (3D printing) has revolutionized the cre- ation of complex parts, contributing to lighter and stronger components. Predictive maintenance powered by AI algorithms helps anticipate system failures, optimize fleet management, and reduce downtime by accurately predicting the lifespan of aircraft com- ponents. Despite the promising benefits, the integration of AI in aerospace engineering faces challenges, such as data privacy concerns, technological limitations, and the need for specialized skills. This paper explores these developments, reviews case studies of AI applications in the aerospace industry, and looks ahead to future trends, such as autonomous aircraft and AI-driven space exploration, positioning AI as a cornerstone for the future of aerospace engineering.