Efficiency in 3D Printing: The power of double-nozzle systems for large-scale, high-volume production

Machine Learning Framework Enhances AM Precision and Efficiency – Metrology and Quality News - Online Magazine

Researchers at University of Toronto Engineering are leveraging machine learning to improve additive manufacturing. In a new paper, published in the journal of Additive Manufacturing, the team introduces a new framework they’ve dubbed the Accurate Inverse process optimization framework in laser Directed Energy Deposition (AIDED).  The post Machine Learning Framework Enhances AM Precision and Efficiency appeared first on Metrology and Quality New…

Efficiency in 3D Printing: The power of double-nozzle systems for large-scale, high-volume production

The world of additive manufacturing is evolving at a breakneck pace, and one of the most significant advancements in recent years has been the development of double-nozzle 3D printing systems. These systems are revolutionizing large-scale, high-volume production by offering unprecedented levels of efficiency, precision, and versatility. For industries that rely on mass production, such as automotive, aerospace, healthcare, and consumer goods, do…