New machine learning framework enhances precision and efficiency in metal 3D printing, advancing sustainable manufacturing
Researchers are leveraging machine learning to improve additive manufacturing, also commonly known as 3D printing. The team introduces a new framework they've dubbed the Accurate Inverse process optimization framework in laser Directed Energy Deposition (AIDED). The new AIDED framework optimizes laser 3D printing to enhance the accuracy and robustness of the finished product. This advancement aims to produce higher quality metal parts for industries, such as aerospace, automotive, nuclear and health care, by predicting how the metal will melt and solidify to find optimal printing conditions.
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Researchers are leveraging machine learning to improve additive manufacturing, also commonly known as 3D printing. The team introduces a new framework they've dubbed the Accurate Inverse process optimization framework in laser Directed Energy Deposition (AIDED). The new AIDED framework optimizes laser 3D printing to enhance the accuracy and robustness of the finished product. This advancement aims to produce higher quality metal parts for industries, such as aerospace, automotive, nuclear and health care, by predicting how the metal will melt and solidify to find optimal printing conditions.
