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<p>Titanium alloy Grade 5 (Ti-6Al-4V) is widely used for biomedical applications due to its high strength and high corrosion resistance. In this work, the reverse electric discharge machining (R-EDM) for the fabrication of macro-pillared array structures on Ti-6Al-4V work piece is carried out using tungsten, copper and copper-tungsten electrodes. The effect of pulse-on time (Ton), flushing pressure (Fp), peak current (I), voltage (U), duty factor (τ) and electrode material on surface roughness, microhardness, recast layer thickness and surface crack density is investigated. A Box Behnken design of response surface methodology (RSM) is used to assess the significance of the parameters and their interaction effects. A meticulous scanning electron microscopy (SEM) analysis is carried out to evaluate the machined surface quality. Multi-response optimization is carried out using the additive ratio assessment (ARAS) method and is coupled with the Firefly Algorithm (FA)&#xa0;to achieve the optimum results. The optimum machining condition is validated by conducting a confirmative test showing an improvement of 6.86 percentage. The proposed work is useful for selecting ideal process conditions while machining Titanium (Ti-6Al-4V) work piece for biomedical application.&#xa0;</p>

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Hybrid Firefly Algorithm-based optimization of reverse EDM for machining of titanium superalloys for high-precision biomedical applications

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年6月23日

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  • Renu Kiran Shastri,
  • Chinmaya P. Mohanty,
  • Kishore Kumar Mahato,
  • Pravat Ranjan Pati

摘要

Titanium alloy Grade 5 (Ti-6Al-4V) is widely used for biomedical applications due to its high strength and high corrosion resistance. In this work, the reverse electric discharge machining (R-EDM) for the fabrication of macro-pillared array structures on Ti-6Al-4V work piece is carried out using tungsten, copper and copper-tungsten electrodes. The effect of pulse-on time (Ton), flushing pressure (Fp), peak current (I), voltage (U), duty factor (τ) and electrode material on surface roughness, microhardness, recast layer thickness and surface crack density is investigated. A Box Behnken design of response surface methodology (RSM) is used to assess the significance of the parameters and their interaction effects. A meticulous scanning electron microscopy (SEM) analysis is carried out to evaluate the machined surface quality. Multi-response optimization is carried out using the additive ratio assessment (ARAS) method and is coupled with the Firefly Algorithm (FA) to achieve the optimum results. The optimum machining condition is validated by conducting a confirmative test showing an improvement of 6.86 percentage. The proposed work is useful for selecting ideal process conditions while machining Titanium (Ti-6Al-4V) work piece for biomedical application.