The Intersection of AI and Additive Manufacturing: A Bibliometric Analysis of Research Trends

This paper employs bibliometric analysis to investigate the changing research landscape at the intersection of artificial intelligence (AI) and additive manufacturing (AM). Our objective is to offer a thorough analysis of this interdisciplinary topic by analysing data from well-known academics, their affiliations, countries, and related literature. The analysis identifies significant contributions, including Mikolajewski D, Rojek I, and Kazimierz Wielki University, which demonstrates the wide range of skills and institutional participation in AI-driven additive manufacturing research. Moreover, countries such as the United Kingdom, Belgium, and Switzerland are prominent centres of research activity, highlighting the worldwide importance and influence of this intersection. By analysing existing literature, we have identified important areas of research, methodology, and technical breakthroughs. Specifically, we have focused on the use of artificial intelligence techniques, such as machine learning, neural networks, and computer vision, to improve additive manufacturing processes. Our analysis also clarifies emerging patterns, difficulties, and possibilities for future investigation and advancement, encompassing process enhancement and material examination, as well as design enhancement and product personalisation. This study enhances our comprehension of the ever-changing field of AI-enabled additive manufacturing and its ability to bring about significant changes in many industries. This analysis is to provide significant insights to researchers, industry experts, and policymakers. Its goal is to inform future efforts in using AI approaches to enhance additive manufacturing technology and applications.