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Modeling of TiC-N thin film coating process on drills using particle swarm optimization algorithm

Version 2 2024-06-04, 11:50
Version 1 2019-12-02, 15:42
journal contribution
posted on 2024-06-04, 11:50 authored by AM Khorasani, M Asadnia, P Saadatkia
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. © 2013 King Fahd University of Petroleum and Minerals.

History

Journal

Arabian journal for science and engineering

Volume

38

Pagination

1565-1571

Location

Cham, Switzerland

ISSN

1319-8025

eISSN

2191-4281

Language

eng

Publication classification

C1.1 Refereed article in a scholarly journal

Issue

6

Publisher

Springer

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