Progress and Opportunities for Machine Learning in Materials and Processes of Additive Manufacturing

In recent years, there has been widespread adoption of machine learning (ML) technologies to unravel intricate relationships among diverse parameters in various additive manufacturing (AM) techniques. These ML models excel at recognizing complex patterns from extensive, well-curated datasets, thereby unveiling latent knowledge crucial for informed decision-making during the AM process. The collaborative synergy between ML and AM holds the potential to revolutionize the design and production of AM-printed parts. This review delves into the challenges and opportunities emerging at the intersection of these two dynamic fields. It provides a comprehensive analysis of the publication landscape for ML-related…

• NR
  National Research Foundation

  Award: NRF‐NRFI07‐2021‐0007
• AF
  Agency for Science, Technology and Research

  Award: 202D800024