Machining Parameter Optimization of Wire Electrical Discharge Machining for Ni50.3Ti29.7Hf20 Alloy Using TOPSIS and Grey Wolf Optimization Technique

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Date

2025

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Springer

Abstract

Ni<inf>50.3</inf>Ti<inf>29.7</inf>Hf<inf>20</inf> is an alloy with shape memory characteristics that can withstand high temperatures. It possesses remarkable strength, hardness, and exceptional corrosion resistance. SMAs are well-suited for various applications, including automotive sensors, automobiles, aerospace technologies, robotics, actuators, and MEMS devices. However, its unique properties make it difficult to machine using conventional methods. Wire EDM is an unconventional machining process suited for difficult-to-machine materials like Ni-Ti-Hf alloy, providing high accuracy and precision and minimizing the risk of material damage. This paper focuses on the optimization of machining parameters, namely Discharge time (P<inf>ON</inf>), Pause time (P<inf>OFF</inf>), Gap voltage (GV), and Wire travel speed (WS) during WEDM of Ni-Ti-Hf shape memory alloy utilizing the TOPSIS and GWO techniques. The aim is to obtain optimal machining parameters for improving the machined Ni-Ti-Hf alloy’s material removal rate (MRR) and surface roughness (R<inf>a</inf>). The optimal machining parameters from GWO were P<inf>ON</inf> = 123.8 µs, P<inf>OFF</inf> = 50 µs, WS = 2, and GV = 25. The predicted values of material removal rate and surface roughness are 4.22 mm3/min and 3.62 µm, respectively. The experimental verification demonstrates the proposed optimization approach's effectiveness, as the predicted values correlate strongly with the actual values. © ASM International 2023.

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Keywords

Corrosion resistance, Corrosion resistant alloys, Electric discharges, Hafnium alloys, Machining centers, Nickel alloys, Shape-memory alloy, Surface roughness, Ternary alloys, Titanium alloys, Wire, Gap voltage, Gray wolf optimization, Gray wolves, Ni-ti-hf, Optimal machining parameters, Optimisations, TOPSIS, Travel speed, WEDM, XRD, Electric discharge machining

Citation

Journal of Materials Engineering and Performance, 2025, 34, 1, pp. 699-710

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