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

  • Research Article - Mechanical Engineering
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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.

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Authors and Affiliations

  1. Faculty of Hi-tech and Engineering, IUIM, Tehran, Iran

    Amir Mahyar Khorasani & Mohsen Asadnia

  2. College of Engineering and Science, Victoria University, Melbourne, Australia

    Pooneh Saadatkia

Authors
  1. Amir Mahyar Khorasani
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  2. Mohsen Asadnia
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  3. Pooneh Saadatkia
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Correspondence to Amir Mahyar Khorasani.

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Khorasani, A.M., Asadnia, M. & Saadatkia, P. Modeling of TiC-N Thin Film Coating Process on Drills Using Particle Swarm Optimization Algorithm. Arab J Sci Eng 38, 1565–1571 (2013). https://doi.org/10.1007/s13369-013-0600-7

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  • DOI: https://doi.org/10.1007/s13369-013-0600-7

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