Artificial Intelligence in Additive Manufacturing:Enhancing Process Control and Quality

This study explores the integration of artificial intelligence (AI) and machine learning (ML) inadditive manufacturing (AM) to enhance process control and quality assurance in all three phasesof manufacturing processes. By employing ML algorithms for real-time monitoring andoptimization of process parameters, we achieve unprecedented precision and consistency in AMoutputs. The research leverages advanced thermal and defect prediction models to mitigatecommon issues such as warping and porosity. Our findings underscore AI and ML's transformativeimpact on AM, significantly reducing defects and post-processing requirements, while enablinghigh-precision, efficient, and scalable manufacturing solutions

کلیدواژه ها:

Artificial Intelligence ، Machine Learning ، Additive Manufacturing ، IWAAM ، Deep Learning