Russian Researchers Develop Neural Network for Metal 3D Printing

Share this Article

3D printing is not a simple process, particularly metal 3D printing. It involves a great deal of complex mathematical modeling, with calculations that can take weeks for even the most basic parts. But scientists from Peter the Great St. Petersburg Polytechnic University have developed a neural network for metal 3D printing that is trained with a large number of parameters, which allows for the faster production of parts as well as the ability to use discovered dependencies to manufacture new parts.

Neural networks are computing systems used to process large data inputs. Researchers at the university 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.

The network was developed in the Mathlab modeling environment, and all data was entered manually. A tool exists for the automatic acquisition of printing process parameters, but so far this data set is being processed online. Next, the researchers will develop an online system based on a neural network that will be learning continuously. The parameters will be added to the system automatically, while their tuning will take place in the course of printing. The researchers believe that the system will improve the quality of parts as well as increase the speed of developing process parameters for further manufacturing.

The neural network is already being used to assess the quality parameters of manufactured parts – for example, if the welding process is stable, if the metal is being melted and transferred correctly, etc. The scientists have also used the network to develop stable printing modes for manufacturing mastheads. They have applied for a patent for the new technology.

“We are the first to use neural networks in electric arc deposition,” Panchenko said.

He added that neural networks will soon find applications in additive manufacturing as well. The researchers believe that the use of similar approaches in the future will allow for the creation of fully automated self-learning systems able to continuously improve the quality of manufactured parts without human supervision.

The neural network developed by the Russian researchers is another step towards the overall automation of additive manufacturing, which has the potential to not only speed up the process and improve the quality of parts but to reduce the risk of human error, which is high when complex mathematics are involved. Metal additive manufacturing still suffers from a great deal of wasted time, money and material due to failed builds, but with advancements such as this one, those failures can potentially be greatly reduced in the future.

Discuss this and other 3D printing topics at 3DPrintBoard.com or share your thoughts below. 

[Source: Sputnik News/Images: SPBPU Media Center]

 

Share this Article


Recent News

Northwestern University: Researchers Produce Large Scale 3D Printer & Control Heat with HARP Technology

Additive Manufacturing Collaboration: Ai Build & WEBER Offer Advanced Large-Scale 3D Printing Solutions



Categories

3D Design

3D Printed Art

3D Printed Food

3D Printed Guns


You May Also Like

3D Printing News Briefs: October 10, 2019

We’re talking about events and business today in 3D Printing News Briefs. In November, Cincinnati Inc. is presenting at FABTECH, and Additive Manufacturing Technologies and XJet are heading off to...

Roboze Improving Quality of 3D Printed Parts with Pre-Drying and Heating Equipment

It’s October, which means that this year’s formnext is fast approaching. From November 19-22, thousands of people will descend on Frankfurt to network, see what’s new in the AM industry,...

Cubicure & Evonik Develop One Component Resin System For Flexible Polyesters Through Hot Lithography

Cubicure and Evonik continue on within the 3D printing realm, leading the evolution of materials science with research and development of polyester resins. Focusing on additive manufacturing processes, this joint...

Formnext Start-up Challenge Announces Five Winning 3D Printing Startups

We’re several days into September now, which means that it’s only two short months until this year’s Formnext exhibition and conference in Germany. But before its November event, Formnext holds...


Shop

View our broad assortment of in house and third party products.


Print Services

Subscribe To Our Newsletter

Subscribe To Our Newsletter

Join our mailing list to receive the latest news and updates from our 3DPrint.com.

You have Successfully Subscribed!