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Comparative assessment reveals Inconel 718's superior machinability and surface integrity in aerospace applications, implying significance for alloy choice.
This study presents a comparative assessment of Electrical Discharge Drilling (EDD) performance on two aerospace-grade nickel-based superalloys, Nimonic AE 435 and Inconel 718, focusing on machinability, surface integrity, and recast layer characteristics. A One-Parameter-At-a-Time (OPAT) methodology was adopted to isolate the individual effects of discharge current, duty factor, and tool-electrode rotation on material removal rate (MRR) and surface roughness (Ra). All experiments were performed in triplicate, and results are reported with standard deviations and 95% confidence intervals to strengthen statistical reliability. Higher current and duty factor increased Ra and MRR due to intensified and sustained spark energy, whereas tool rotation significantly improved surface finish by enhancing debris evacuation. Comparative analysis revealed superior machinability of Inconel 718, which achieved higher MRR (40–78 mg) and lower Ra (1.9–4.2 µm) than AE 435 (MRR: 38–70 mg; Ra: 2.5–4.6 µm). These differences arise from alloy-specific precipitation mechanisms: dominant γ′ precipitates in AE 435 promote localized thermal resistance and uneven molten pool formation, while the γ′–γʺ combination in Inconel 718 enables more uniform erosion. Optical microscopy at 100 × magnification confirmed thinner, smoother recast layers for Inconel 718, whereas AE 435 exhibited globular resolidified structures linked to its stronger precipitation hardening response. The results benchmark EDD behavior of two strategically important aerospace superalloys and highlight the governing role of metallurgical phase composition, rather than nickel percentage alone, on spark-erosion dynamics. The study establishes essential baseline trends for optimizing micro-drilling of advanced alloys, while recommending future SEM/EDS and multivariable statistical modeling for deeper surface-integrity and interaction-effect characterization.
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Kumar et al. (2026) studied this question.
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