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All Journal International Journal of Industrial Engineering and Engineering Management
John Rajan
School of Mechanical Engineering, Vellore Institute of Technology, Chennai Campus, India
Industrial & Manufacturing Engineering

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Coating Adherence Optimization for 67Ni18Cr5Si4B Alloy Powder by High-Velocity Oxygen Fuel Spray Based on the Grey Wolf Algorithm Method Anthony Ozimu Adekola; Bayo Yemisi Ogunmola; Modupe Adeoye Onitiri; Nehemiah Sabinus Alozie; Adeyinka Oluwo; John Rajan; Swaminathan Jose; Sunday Ayoola Oke
International Journal of Industrial Engineering and Engineering Management Vol. 7 No. 2 (2025)
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijieem.v7i2.7874

Abstract

Adhesion engineers increasingly use coatings in industrial equipment on gas turbine blades and vanes because of the benefits of protection against thermal stresses, oxidation, and hot corrosion. However, the coating process has suffered sub-optimal value determination, posing a serious threat to the economics of coating. While the prevailing approach of introducing the Taguchi method appears effective in resolving this issue, it sacrifices convergence speed and multiple optimization solutions. Thus, the grey wolf algorithm is proposed to optimize the coating of 67Ni18Cr5Si4B alloy powder process parameters, including powder feed rate, spray velocity, and spray distance. The high-velocity oxygen fuel spray was used, and the objectives were good microhardness, adhesion strength, and porosity. The optimal value to obtain the best coating for each of the responses was given as 85MPa for the adhesion strength, 0.684909% porosity, and 583.04HV microhardness. The present study offers important insights into the optimization thresholds to help the components development process. The quantitative form of this work is new. Fast convergence solutions offered by metaheuristics such as the grey wolf optimization algorithm are rarely found in the literature.
Co-Authors Adeyinka Oluwo Anthony Ozimu Adekola Bayo Yemisi Ogunmola Modupe Adeoye Onitiri Nehemiah Sabinus Alozie Sunday Ayoola Oke Swaminathan Jose