Modeling of TiC-N Thin Film Coating Process on Drills Using Particle Swarm Optimization Algorithm

Amir Mahyar Khorasani, Mohsen Asadnia, Pooneh Saadatkia

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

The prediction of maximum hardness in thin-film coating on high speed cutting drills is an essential prerequisite for developing drilling and it is depended on many factors such as ion bombard time, sub layer temperature, work and chamber pressure. This paper proposes the estimation of hardness of titanium nitride carbide (TIC-N) thin-film layers as protective of high speed cutting drills using Improved Particle Swarm Optimization-based Neural Network (PSONN). Based on the obtained experimental data during the process of chemical vapor deposition (CVD) and physical vapor deposition (PVD), the modeling of the coating variables for achieving the maximum hardness of titanium thin-film layers is performed. By comparison the experimental results with model estimation the accuracy of the system was approximately 97.47 % acquired while back propagation (BP) had 95.5 % precision.

Original languageEnglish
Pages (from-to)1565-1571
Number of pages7
JournalArabian Journal for Science and Engineering
Volume38
Issue number6
DOIs
Publication statusPublished - Jun 2013
Externally publishedYes

Keywords

  • Back propagation
  • Hardening process
  • High speed cutting drills
  • PSO algorithm
  • TiC-N coating

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