Russian Scientists Develop Neural Network for 3D Printing of Metal Products
Scientists from Peter the Great St. Petersburg Polytechnic University (SPbPU) recently developed a neural network for the 3D printing of metal products.
Nov 10, 2018
The mathematical modeling necessary for 3D printing requires great computing power, and making calculations for manufacturing even the most basic parts takes weeks, said a representative from the university's Media Center in an interview with Sputnik. Experts state that using neural networks trained with the help of larger number of parameters allows not only obtaining parts faster, but also using the discovered dependencies to manufacture new parts.
Neural networks are computing systems used to process large data inputs. University researchers used this method to obtain 3D printing process parameters and ensure the stability of the process.
"This was very important for us, since the metal transfer, which takes place in the course of printing parts from wire, is a very complex process characterized by competing physical effects; it has, however, a critical impact on the quality of the printed part," said Oleg Panchenko, Head of the St. Petersburg Polytechnic University's Laboratory of Light Materials and Structures SPbPU.
Neural networks are computing systems used to process large data inputs. University researchers used this method to obtain 3D printing process parameters and ensure the stability of the process.
"This was very important for us, since the metal transfer, which takes place in the course of printing parts from wire, is a very complex process characterized by competing physical effects; it has, however, a critical impact on the quality of the printed part," said Oleg Panchenko, Head of the St. Petersburg Polytechnic University's Laboratory of Light Materials and Structures SPbPU.