Transfer Learning and Incremental Learning Applied to Energy Consumption Prediction in Directed Energy Deposition Manufacturing

Summary

Researchers from multiple institutions published a paper in npj Advanced Manufacturing describing a method that combines incremental learning with transfer learning to predict energy consumption in directed energy deposition (DED), an additive manufacturing process. The study was led by Chenglong Duan and Dazhong Wu, with experiments conducted by Fan Zhou and contributions from Zhichao Liu and Bhaskaran Gopalakrishnan. The work sits at the intersection of machine learning and advanced manufactu