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<p>Wire Electrical Discharge Machining (WEDM) is widely used for machining titanium alloys such as Ti-6Al-4&#xa0;V. However, comprehensive multi-response optimisation incorporating a larger set of input and output variables remains limited. This study presents a systematic and extensive optimization of the WEDM process by simultaneously considering six control parameters and four critical performance responses: cutting velocity (CV), material removal rate (MRR), surface roughness (SR), and kerf width (KW). Response Surface Methodology (RSM) was employed to develop second-order predictive models, and their statistical significance and adequacy were validated using analysis of variance (ANOVA). The results reveal that pulse width (PW) and short-pulse time (SPT) exert a dominant influence on all machining responses, whereas wire feed rate (WFR) and wire mechanical tension (WMT) exert minimal influence. Multi-response optimization using the desirability function approach identified optimal machining conditions that significantly enhance productivity while maintaining superior surface integrity. Field emission scanning electron microscopy (FE-SEM) analysis of the optimized surfaces confirmed smooth morphology with minimal defects. The novelty of this work lies in the integrated optimization framework involving an expanded parameter–response space, offering robust guidelines for high-precision WEDM of Ti-6Al-4&#xa0;V for biomedical and aerospace applications.</p>

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Multi-response optimization of wire electrical discharge machining parameters for enhanced machinability of Ti-6Al-4 V alloy

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月1日

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  • Anu Anand,
  • Ghulam Anwer,
  • S. M. Mozammil Hasnain,
  • Prabhu Paramasivam,
  • Leliso Hobicho Dabelo

摘要

Wire Electrical Discharge Machining (WEDM) is widely used for machining titanium alloys such as Ti-6Al-4 V. However, comprehensive multi-response optimisation incorporating a larger set of input and output variables remains limited. This study presents a systematic and extensive optimization of the WEDM process by simultaneously considering six control parameters and four critical performance responses: cutting velocity (CV), material removal rate (MRR), surface roughness (SR), and kerf width (KW). Response Surface Methodology (RSM) was employed to develop second-order predictive models, and their statistical significance and adequacy were validated using analysis of variance (ANOVA). The results reveal that pulse width (PW) and short-pulse time (SPT) exert a dominant influence on all machining responses, whereas wire feed rate (WFR) and wire mechanical tension (WMT) exert minimal influence. Multi-response optimization using the desirability function approach identified optimal machining conditions that significantly enhance productivity while maintaining superior surface integrity. Field emission scanning electron microscopy (FE-SEM) analysis of the optimized surfaces confirmed smooth morphology with minimal defects. The novelty of this work lies in the integrated optimization framework involving an expanded parameter–response space, offering robust guidelines for high-precision WEDM of Ti-6Al-4 V for biomedical and aerospace applications.