Ultrasonic-assisted Electrical Discharge Machining (UV-EDM) has emerged as a promising technique for improving machining efficiency and electrode life, particularly when processing hard conductive materials. This study presents a hybrid multi- criteria optimization framework that integrates Non- dominated Sorting Genetic Algorithm II (NSGA-II) and the Multi-Attributive Border Approximation Area Comparison (MABAC) method to optimize two conflicting performance measures: Material Removal Rate (MRR) and Electrode Wear Rate (EWR).

This study investigates ultrasonic vibration-assisted (UV) CNC milling of hardened 90CrSi steel cylindrical surfaces, with emphasis on ultrasonic horn design, experimental analysis, and multi-objective optimization of machining parameters, addressing the need for an inte- grated framework combining system design, experimental validation, and multi-objective optimization. A quarter-wavelength ultrasonic horn was designed and experimentally validated to operate at a frequency of 20 kHz. By adjusting the horn–workpiece system, stable vibration amplitudes were achieved to enable effective ultrasonic-assisted milling of cylindrical surfaces. Milling experiments based on a Box–Behnken design were conducted to examine the effects of vibration amplitude, cutting speed, feed rate, and radial depth of cut on material removal rate (MRR) and surface roughness (Ra). Surrogate models using response surface methodology (RSM) and Gaussian process regression (GPR) were developed to predict machining performance. A GPR-assisted NSGA-II algorithm was then applied to simultaneously maximize MRR and minimize Ra, resulting in a well-defined Pareto front that reveals the trade-off between machining productivity and surface quality.

This study investigates the modeling and single-objective optimization of surface roughness (Ra) and material removal rate (MRR) in electrical discharge machining (EDM) of external cylindrical surfaces of hardened 90CrSi tool steel. The machining process is enhanced using ultrasonic vibration assistance and graphite electrodes to improve surface integrity and productivity. Gaussian Process Regression (GPR) and Response Surface Methodology (RSM) were employed to construct predictive models for Ra and MRR based on key process parameters, including vibration amplitude (A), pulse-on time (Ton), pulse-off time (Toff), peak current (IP), and servo voltage (SV). The GPR model provided superior predictive performance for surface roughness, while RSM was more effective in modeling MRR. Optimization results showed that the minimum Ra of 1.6216 µm was achieved at A = 2.7743 µm, Ton = 8.0000 µs, Toff = 11.8294 µs, IP = 8.1723 A, and SV = 4.7936 V. Meanwhile, the maximum MRR of 12.1989 g/h was obtained at A = 3.5339 µm, Ton = 16.0000 µs, Toff = 8.0000 µs, IP = 15.0000 A, and SV = 4.0000 V. The findings provide valuable insights into parameter selection for improving EDM performance on external cylindrical surfaces of high-hardness steels.

The scientific purpose of this study is to optimize 3 main parameters: hammer mass (m), hammer drop height (h) and filter chamber inlet dust concentration (η) of the Electrostatic precipitator (ESP), to meet the dust removal acceleration (a) and the hammer rapping force (F), ensure the working life span of the discharge electrode frames and the collecting electrode plates. This issue is evaluated as a multi-objective problem

The cyclic impact of rapping hammers against the collecting electrode frame of horizontal electrostatic precipitators creates a collision between the hammer and the anvil beam end of the collecting electrode frame.

This study aims to investigate the relationship between the cyclic rapping force of a hammer (F) and the lifespan of a discharge electrode frame, which is an important component of dust filter chambers.

The successful design, manufacturing and operation of an automatic goods sorting system has contributed to optimizing the production process and cutting the costs of logistics enterprises. Vietnam Economic News’ Quynh Nga interviewed Dr. Phan Dang Phong, Director of the National Research Institute of Mechanical Engineering (NARIME) under the Ministry of Industry and Trade (MoIT), about this technology.

Author:  Van-Chien Dinh, Thanh-Phu Nguyen & Van-Canh Tong Place posted: Journal of Adhesion Science and Technology. ISSN 0169-4243 Post time: 2018 Abstract: High Velocity Oxygen Fuel (HVOF) spray is being widely used in many industries to deposit erosion-resistant coatings or restore the dimension for components. The ...

Author: Quy Thu Le, Tuan Van Nguyen, Ly Thi Pham, Ha Thi Pham, Thanh Thi Mai Dinh. Place posted: 8th Asian Thermal Spray Conference (ATSC 2017), Paper P00062, November 6-8, 2017, Jeju – Korea. Post time: 2017 Abstract: The paper presents our study on the ...

Author: Nguyen Van Tuan, Ly Quoc Cuong, Le Thu Quy, Pham Thi Ha, Pham Thi Ly Place posted: The 5th National conference on corrosion and metal protection for energy development (VICORRA2017), Ba Ria – Vung Tau, 19-21/10/2017.Vietnam Journal of Science and ...