Single-Optimization of Ultrasonic Vibration-Assisted EDM for External Cylindrical Machining of 90CrSi

Van Thanh Dinh; Thu Quy Le; Thi Tam Do; Ngoc Pi Vu; Thi Phuong Thao Tran

doi:10.48084/etasr.11450

Authors

Van Thanh Dinh East Asia University of Technology, Trinh Van Bo Street, Hanoi City 12000, Vietnam
Thu Quy Le National Research Institute of Mechanical Engineering, 04 Pham Van Dong, Ha Noi City 11309, Vietnam
Thi Tam Do Thai Nguyen University of Technology, 3/2 street, Tich Luong ward, Thai Nguyen City 251750, Vietnam
Ngoc Pi Vu
Thi Phuong Thao Tran Thai Nguyen University of Technology, 3/2 street, Tich Luong ward, Thai Nguyen City 251750, Vietnam

Volume: 15 | Issue: 4 | Pages: 25959-25970 | August 2025 | https://doi.org/10.48084/etasr.11450

Received: 12 April 2025 | Revised: 7 May 2025 and 25 May 2025 | Accepted: 27 May 2025 | Online: 2 August 2025

Corresponding author: Thi Phuong Thao Tran

Abstract

The present study investigates the optimization of Ultrasonic Vibration-Assisted Electrical Discharge Machining (UV-EDM) for external cylindrical machining of 90CrSi tool steel, a material known for its high hardness and poor machinability by conventional methods. Traditional EDM often suffers from low Material Removal Rate (MRR) and poor surface finish (Ra), limiting its productivity and surface integrity. To address this, the research aims to determine optimal machining parameters that enhance MRR while maintaining or improving Ra using ultrasonic assistance. A Box–Behnken experimental design was employed with five input parameters: vibration amplitude, pulse-on time, pulse-off time, discharge current, and servo voltage. Forty-six experiments were conducted, and second-order regression models were developed for both MRR and Ra. The effects and interactions of parameters were analyzed using response surface plots and interaction heatmaps. Results show that discharge current and pulse-on time strongly influence MRR, whereas servo voltage and pulse-off time significantly affect Ra. Ultrasonic vibration was found to notably increase MRR, and when properly tuned, improved surface roughness by enhancing debris evacuation and discharge stability. Key interaction effects (e.g., between current and amplitude) were identified, emphasizing the importance of balanced settings. The developed regression models (R² = 0.987 for MRR and R² = 0.783 for Ra) provide reliable predictions and can support future process control. Overall, UV-EDM proves to be a highly effective technique for improving both efficiency and surface quality in precision machining of hard tool steels.

Keywords:

ultrasonic vibration-assisted EDM, single-objective optimization, 90CrSi tool steel, surface roughness;, material removal rate, Box–Behnken Design (BBD), regression modeling

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