Training neural networks for machining applications

Güngör O., ÇAKIR A.

Electronics World, vol.126, no.2002, pp.32-36, 2020 (Scopus) identifier

  • Publication Type: Article / Article
  • Volume: 126 Issue: 2002
  • Publication Date: 2020
  • Journal Name: Electronics World
  • Journal Indexes: Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences
  • Page Numbers: pp.32-36
  • Isparta University of Applied Sciences Affiliated: Yes

Abstract

Machining is one of the most important techniques in modern-day manufacturing, and it continually evolves. One vital raw material category in machining is the nickel-based super-alloy. More recently, nickel-based super-alloys have become more widespread, especially in the aviation sector, industrial gas turbines, space applications, engines, nuclear reactors, submarines, steam production facilities, petrochemical devices, heat-resistant applications, and many more.