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<p>Wire Electrical Discharge Machining (WEDM) study employed gamma diffused zinc-coated brass wire to cut titanium alloy grade 5. The manipulated variables encompassed current, Stability B, wire tension, and servo voltage. Subsequently, the resultant surface quality of the titanium alloy was assessed. Characterization involved the measurement of surface roughness, coupled with the utilization of Scanning Electron Microscopy (SEM) equipped with Energy-Dispersive X-ray Spectroscopy (EDX) to provide an in-depth analysis of the machined surface. Additionally, Atomic Force Microscopy (AFM) was employed to capture a three-dimensional perspective of the surface. Alongside these evaluations integrated fuzzy logic prediction to estimate the surface roughness of the titanium alloy. Furthermore, we investigated the rate of electrode wear and scrutinized the microscopic structure of each electrode. With a 92.6% contribution to the surface smoothness, the pulse current (Ip) is most critical parameter, and the ANOVA model's error is less than 1%. If the pulse current increased, then increase in surface roughness of 4.50&#xa0;µm for linear regression prediction whereas for polynomial regression prediction was 4.23&#xa0;µm. This prediction can be valuable in optimizing the WEDM process to achieve the desired surface finish without the need for extensive experimentation.</p> Graphical Abstract <p></p>

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Surface roughness prediction in wire EDM of titanium alloy with gamma-diffused zinc-coated brass wire: a fuzzy logic approach

  • 期刊论文

  • 发表日期：

    2026年2月21日

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  • S. Oliver Nesa Raj,
  • Prabhu Sethuramalingam,
  • M. Uma

摘要

Wire Electrical Discharge Machining (WEDM) study employed gamma diffused zinc-coated brass wire to cut titanium alloy grade 5. The manipulated variables encompassed current, Stability B, wire tension, and servo voltage. Subsequently, the resultant surface quality of the titanium alloy was assessed. Characterization involved the measurement of surface roughness, coupled with the utilization of Scanning Electron Microscopy (SEM) equipped with Energy-Dispersive X-ray Spectroscopy (EDX) to provide an in-depth analysis of the machined surface. Additionally, Atomic Force Microscopy (AFM) was employed to capture a three-dimensional perspective of the surface. Alongside these evaluations integrated fuzzy logic prediction to estimate the surface roughness of the titanium alloy. Furthermore, we investigated the rate of electrode wear and scrutinized the microscopic structure of each electrode. With a 92.6% contribution to the surface smoothness, the pulse current (Ip) is most critical parameter, and the ANOVA model's error is less than 1%. If the pulse current increased, then increase in surface roughness of 4.50 µm for linear regression prediction whereas for polynomial regression prediction was 4.23 µm. This prediction can be valuable in optimizing the WEDM process to achieve the desired surface finish without the need for extensive experimentation.

Graphical Abstract