Experimental Analysis of Surface Roughness Optimization of EN19 Alloy Steel Milling by the Cuckoo Search Algorithm

  • Shubham Jain Department of Mechanical Engineering, Maulana Azad National Institute of Technology Bhopal, Madhya Pradesh, India https://orcid.org/0000-0003-1254-522X
  • Anil Mulewa Faculty of Mechanical Engineering, Shri G. S. Institute of Technology and Science, Indore, Madhya Pradesh, India https://orcid.org/0000-0002-0731-9458
Keywords: Cuckoo search algorithm, EN19 alloy steel, milling, optimization, surface roughness

Abstract

In the present paper, end milling has been performed on EN19 alloy steel by selecting cutting speed, feed rate, & depth of cut as input parameters and surface roughness (SR) as a response. EN19 alloy steel milling is widely used in various sectors, such as the automotive, defence, construction, aerospace, and nuclear sectors. A parametric study of EN19 alloy steel is needed for better machining. The central composite design was used for designing the experiments & modeling the surface roughness as a response. A cuckoo search algorithm was applied to minimize the surface roughness. It was found that feed rate is the most important factor affecting surface roughness (SR). The Cuckoo Search Algorithm also reveals that a minimum SR 1.8576 micrometer has been achieved at a higher speed of 765 RPM, a lower feed rate of 55.9516 mm/min., & a lower depth of cut of 0.4846 mm. The experiment concludes that it is so that the optimum SR is exhibited at both lower feed rates & high speeds. This, in turn, indicates that our implementation of CCD-based SR, followed by the real cuckoo search algorithm optimization, provides similar results and a good model to the practical results we would expect.

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Published
2024-04-30
How to Cite
Jain, S., & Mulewa, A. (2024). Experimental Analysis of Surface Roughness Optimization of EN19 Alloy Steel Milling by the Cuckoo Search Algorithm. International Journal of Experimental Research and Review, 38, 102-110. https://doi.org/10.52756/ijerr.2024.v38.009
Section
Articles