Search Results (278)

Bearings in electric motors are exposed to stray currents and shaft voltages, which can accelerate surface damage and reduce service life. This study examines how pulsed direct current (DC) direction affects early-stage degradation in rolling bearings under low-speed operation. A dedicated test rig was used in which the bearing inner and outer rings were connected directly to the positive and negative terminals of a pulsed DC power supply. Unipolar excitation was applied at 20 kHz with a nominal current of 3 A and shaft-voltage peaks of about 3 V for 3 h, with current flowing in only one direction during each test. After testing, the bearings were sectioned and examined by optical microscopy, scanning electron microscopy (SEM), and X-ray photoelectron spectroscopy (XPS). The results showed that when current flowed from the outer ring to the inner ring, visible electrical discharge machining (EDM)-type damage was mainly found on the outer raceway. When the current direction was reversed, the damaged region shifted to the inner raceway. The affected areas showed crater-like discharge features and surface chemical changes, while the opposite raceway showed much less change under the same test conditions. These observations indicate that current direction influences where EDM-type damage more likely forms in the bearing under the present low-speed unipolar excitation conditions. Full article

Electrical discharge machining (EDM) is an efficient method for processing silicon carbide (SiC) substrates. However, the chemical modification mechanism of SiC substrates in the EDM process remains not fully elucidated. To clarify the material removal mechanism of SiC substrates in EDM, this study investigated the behaviors of SiC substrates under different discharge conditions through experimental analysis and interface temperature field simulation. Results indicate that the SiC substrates sequentially exhibit characteristic morphologies of surface oxidation, thermal decomposition, and fracture as discharge energy increases. A discolored layer composed of amorphous SiO₂ is formed on the SiC surface in low-discharge energy. Crystalline silicon and graphitic carbon are generated from the thermal decomposition of SiC substrates in high-discharge energy. Excessively high discharge energy induces the breakdown of SiC substrates. A critical temperature threshold is identified that delineates the initiation of prominent thermal oxidation on the SiC surface. Temperature field simulations further reveal the correlation between EDM parameters and interfacial temperature variations, along with the mechanisms of material removal driven by thermal diffusion. This study deepens the fundamental understanding of the EDM removal mechanism of SiC substrates and is expected to provide a scientific basis for the efficient material removal of SiC substrates. Full article

As one of the most promising new materials in the field of materials science, high-entropy alloys (HEAs) have attracted widespread attention due to the unique structure, exceptional properties and engineering performance, and complex composition. The CoCrFeNiZr_0.5 eutectic high-entropy alloys (EHEAs) exhibits excellent high-temperature thermal stability, ductility, creep resistance, and corrosion resistance, demonstrating great potential for applications in marine equipment. This paper explores the engineering feasibility of electrical discharge machining (EDM) of CoCrFeNiZr_0.5 EHEAs and investigates the EDM of micro-holes using a hollow copper electrode on a CNC EDM drilling machine under various machining parameters, including different gap voltage, pulse-on time, pulse-off time, and pulse amplifier settings. The effects of these parameters on the inlet diameter, outlet diameter, and recast layer of the micro holes are analyzed. The optimal micro-hole machining parameters are determined by comprehensively considering machining efficiency and electrode wear: gap voltage of 33 V, pulse-on time of 3 μs, pulse-off time of 1 μs, and pulse amplifier output of 3 A. Adopting the parameters to process a button ingot sample with a depth of 5 mm, it was found that the machining speed is 7.79 mm/min and the electrode wear is 1 cm. This research renders the foundation for further development and engineering application of CoCrFeNiZr_0.5 EHEAs in the context of high-value material design and manufacturing. Full article

Surface topography characterization is essential for evaluating the effects of texturing processes and for describing surface-dependent phenomena. Assessing the relationships between manufacturing, surface geometries, and functional properties requires, firstly, a detailed characterization of surfaces. Conventional parameters defined in ISO 25178-2 describe the statistical distribution of surface heights relative to the mean plane, as well as the arrangement, spacing, and directionality of surface features. They also include height and spatial descriptors, functional properties derived from the Abbott–Firestone curve, and characteristics of individual topographic features, such as peaks and valleys, including their shape, volume, and distribution. While these parameters provide a valuable description of the surface, they are not intrinsically multiscale and provide only a single aggregated descriptor of the surface. Therefore, multiscale parameters complement this description by capturing relative areas and area-scale fractal-like complexity across geometrically decomposed surface features over a range of scales from the nano and micro to the macro scale. The main objective of this study is to evaluate correlations between conventional and multiscale topographic parameters, based on surfaces produced by electrical discharge machining (EDM). The novelty of this study lies in the integrated analysis of correlations between conventional and multiscale parameters, enabling a more comprehensive framework for surface characterization. Full article

Pulse repetition frequency (PRF) controls pulse off-time and, therefore, the extent of thermal accumulation, melt expulsion, and dielectric recovery in finishing electrical discharge machining (EDM). This study clarifies how PRF modifies crater evolution and surface integrity in finishing EDM of 4Cr13 martensitic stainless steel, a corrosion-resistant mold steel used in precision dies and molds. A 2D axisymmetric electro-thermo-fluid model was established in COMSOL, where Gaussian current density, heat-flux, and plasma pressure were periodically imposed at PRFs of 25–100 kHz, while pulse-on time (6 μs) and peak current (8 A) were kept constant. The simulations tracked the transient pressure, heat-flux, velocity, and temperature fields over a common elapsed time of 25 μs. Finishing experiments were then carried out on flat 4Cr13 coupons at 50, 75, and 100 kHz using a copper electrode and deionized water, followed by characterization by laser confocal microscopy, SEM/EDS, and X-ray diffraction using the cosα method. Increasing PRF localized the coupled pressure-heat-flow fields near the crater rim, but shortened off-time and intensified inter-pulse heat accumulation. Accordingly, the surface roughness decreased from Ra = 1.18 μm at 50 kHz to 0.63 μm at 75 kHz, and then slightly increased to 0.71 μm at 100 kHz because of crater overlap, re-melting, and incomplete gap recovery. SEM observations confirmed large irregular craters with cracks at 50 kHz, more uniform fine craters at 75 kHz, and overlapping re-solidified traces at 100 kHz. The residual stress remained compressive for all tested conditions (−341 to −409 MPa). Overall, 75 kHz offers the best compromise between crater uniformity, roughness, and compressive stress for finishing EDM of 4Cr13 steel. Full article

The paper deals with the comparative analysis, at microgeometric scale, of machined surfaces by classic electrical discharge machining (EDM) and hybrid ultrasonic EDM of CoCr alloys, using computer vision aimed at emphasizing the advantages of this hybrid technology. The analysis generally revealed the superior stability of EDM+US process against classic EDM, explained by the better evacuation of debris from the working gap due to ultrasonically induced cavitation. This key phenomenon also contributed to the enhancement of machining rate by removing the material in liquid and solid state from the microgeometry peaks, while also reducing the surface roughness if the power on the ultrasonic chain was optimized. Full article

The design of millimeter-scale micro-turbine blades is challenging due to conflicting requirements: achieving aerodynamic performance while remaining compatible with microfabrication, and exploring high-dimensional morphological design spaces without prohibitive computational cost. To address these challenges, this study proposes an intelligent framework for the design and optimization of the three-dimensional blade profile of a 3 mm diameter micro-turbine. The blade morphology is parameterized using 22 variables, ensuring geometric feasibility for micro-EDM (Electrical Discharge Machining) fabrication. A physics-informed neural network (PINN) surrogate model, efficiently trained through a two-stage active learning strategy combining KD-tree exploration and residual-based sampling, provides accurate predictions of flow fields. Multi-objective optimization using Non-dominated Sorting Genetic Algorithm II (NSGA-II) is then performed to maximize torque and thrust. Experimental results show that the optimized blade achieves a 38.6% increase in rotational speed while retaining 75.1% of thrust at 0.2 MPa inlet pressure, validating the framework’s effectiveness. This methodology offers a systematic solution for designing microfluidic devices characterized by high-dimensional parameters and high-fidelity simulation requirements. Full article

The study focused on the development and optimization of plastic deformation of pure M1E copper using an unconventional hydrostatic extrusion (HE) process aimed at improving the performance of electrodes used in electrical discharge machining (EDM). The process was designed to refine the microstructure while maintaining the high electrical conductivity required for EDM applications. Optimization of a three-stage HE process (cumulative strain ε = 2.51) resulted in the formation of an ultrafine-grained structure (d₂ ≈ 370 nm), leading to a significant increase in mechanical strength (UTS ≈ 400 MPa) while preserving very high electrical conductivity (~99% IACS). This combination of properties is particularly important for EDM electrodes, as it allows improved wear resistance without compromising electrical performance. Due to the application-oriented nature of the study, the HE-processed copper was tested under industrial EDM conditions. Wear tests were conducted using seven electrodes of different geometries required for the production of a sample injection mold. The results demonstrated a substantial reduction in electroerosion wear of HE-processed electrodes (30–90%) compared with undeformed copper, together with up to 25% improvement in surface quality. These findings indicate that hydrostatic extrusion is an effective method for producing high performance EDM electrode materials with improved durability and machining quality. Full article

Electrical Discharge Machining (EDM) enables precision post-weld finishing of AISI 304 stainless steel, but stochastic spark overlaps make the fatigue-critical maximum peak-to-valley height (R_max) difficult to predict. This study develops a validated physics-based framework quantifying how crater overlap governs R_max evolution. Experiments on unwelded AISI 304 cylinders—proxying weld metal while excluding heat-affected zone (HAZ) effects—used Central Composite Design (20 trials, 900–9380 μJ discharge energies). Profilometry and scanning electron microscopy (SEM) correlated the crater size, overlap intensity, micro-cracking, and R_max escalation from 18 to 85 μm. Primary and secondary crater formation under minimum and maximum overlap configurations were simulated using a 2D axisymmetric finite element model with Gaussian heat flux and temperature-dependent thermophysical properties. The predictive metric R_max,num = (d_initial + d_secondary)/2 achieved 11–19% average error against the experimental R_max,exp, with complementary valley depth (R_v) validation at 13% error. The Specimen 7 outlier (~50% error) reveals the limitations of deterministic modelling under stochastic debris accumulation and plasma instability at intermediate energies. Crater overlap generates secondary dimples, sharp inter-crater peaks, and rim micro-crack networks, driving the 4.7-fold R_max increase—approaching International Institute of Welding (IIW) fatigue thresholds (<25 μm for high-cycle categories). The framework explicitly links the discharge energy, plasma channel radius (R_pc), and overlap geometry to surface topography, enabling process optimization (I·t_on < 60 A·s maintains R_max < 25 μm). Mesh independence (<2.5% convergence) and six centre-point replicates (CV = 4.2%) confirm robustness. This validated upper-bound R_max predictor supports the digital co-optimization of welding and EDM parameters for aerospace/energy applications, with planned extensions to stochastic 3D models incorporating adaptive remeshing and real weld topographies. Full article

Electric Discharge Machining (EDM) is a well-established process for fabricating complex geometries from hard materials. However, identifying the influence of process parameters remains challenging and costly due to the stochastic nature of EDM and the expense of experimental validation. Machine Learning (ML) techniques provide an alternative to mitigate these limitations by enabling predictive modeling with reduced experimental effort. This research proposes a generalizable framework employing four ML models to analyze the correlation between EDM inputs and outputs, incorporating 11 levels of cryogenic electrode treatment. Independent variables include electrode material, cryogenic conditions, pulse current, and pulse duration, while performance is assessed through Material Removal Rate (MRR) and Electrode Wear Rate (EWR). The results demonstrate that Random Forest (RF) and Artificial Neural Networks (ANNs) achieve superior predictive performance compared to alternative approaches, improving the $R^2$ metric from 0.973 to 0.9956 for EWR in the case of an ANN and from 0.980 to 0.9943 for RF with MRR, compared with previous work in the literature and the best methods across 30 executions. Both models consistently yield high predictive accuracy, with $R^2$ values ranging from 0.9936 to 0.9979 in training and testing datasets. Furthermore, ANN significantly reduces mean squared error, decreasing EWR prediction error from 5.79 to 0.68 and MRR error from 122.75 to 35.89. This research contributes to a deeper understanding of EDM process dynamics. Full article

Bacterial infections and the lack of bioactivity of titanium implants and their alloys remain critical challenges for the long-term performance and clinical success of these devices. These issues arise from the undesirable combination of early microbial adhesion and the limited ability of metallic surfaces to form a bioactive interface capable of supporting osseointegration. To address these limitations simultaneously, this study employed electrical discharge machining (EDM), which enables surface topography modification and in situ incorporation of bioactive ions from the dielectric fluid. Ti-6Al-4V ELI surfaces were modified using two dielectric fluids, a fluorine/phosphorus-based solution (DF1-F) and a calcium/phosphorus-based solution (DF2-Ca), under positive and negative polarities. The recast layer was characterized by SEM and EDS, while bioactivity was evaluated through immersion in simulated body fluid (SBF) for up to 21 days. Antibacterial performance was assessed against Staphylococcus aureus at 6 h and 24 h of incubation. The results demonstrated that dielectric composition and polarity strongly influenced ionic incorporation and the structural stability of the modified layers. The DF2-Ca(+) condition exhibited the most favorable bioactive response, with Ca/P ratios closer to hydroxyapatite and surface morphologies typical of mineralized coatings. In antibacterial assays, Ca/P-containing surfaces significantly decreased S. aureus attachment (>80–90%). Overall, EDM with Ca/P-containing dielectrics enables the fabrication of Ti-6Al-4V surfaces with enhanced mineralization capacity and anti-adhesive effects against Gram-positive bacteria, reinforcing their potential for multifunctional biomedical applications. Full article

The emergence of new hard and extra-hard materials has led to the development of new technologies capable of processing them, known as unconventional technologies. Electrical discharge machining (EDM) is a very common unconventional technology in the manufacturing industry, used to process special materials. The primary benefit is the ability to machine various complex shapes at a reduced cost. This study addressed the use of intensive machining regimes that would enhance productivity while also maintaining a high quality of the resulting surface. The experimental setup was designed according to a D-optimal response surface method, and the results were statistically processed using ANOVA. The results revealed that it is possible to achieve both high productivity and good surface quality, but it was also found that increasing the processing parameters is feasible only to a certain extent. Full article

Electrical discharge machining (EDM) is widely used for machining hard and difficult-to-cut materials; however, the complex and nonlinear nature of the process makes the accurate prediction of key performance indicators challenging, particularly when only limited experimental data are available. In this study, a combined Taguchi design and Gaussian process regression (GPR) modeling framework is proposed to predict the surface roughness (Ra), material removal rate (MRR), and overcut (OC) in die-sinking EDM. An L18 Taguchi orthogonal array was employed to efficiently design experiments involving discharge current, pulse duration, and electrode material. GPR models with an automatic relevance determination (ARD) radial basis function kernel were developed to capture nonlinear relationships and varying parameter relevance. Model performance was evaluated using strict leave-one-out cross-validation (LOOCV). The developed GPR models achieved low prediction errors, with RMSE (MAE) values of 0.54 µm (0.41 µm) for R_a, 1.56 mm³/min (1.21 mm³/min) for MRR, and 0.0065 mm (0.0055 mm) for OC, corresponding to approximately 9.8%, 5.4%, and 5.9% of the respective response ranges. These results confirm stable and reliable predictive accuracy within the investigated parameter domain. Based on the validated surrogate models, multi-objective optimization was performed to identify Pareto-optimal process conditions, revealing graphite electrodes as the dominant choice within the feasible operating region. The proposed approach demonstrates that accurate and robust prediction of EDM performance can be achieved even with compact experimental datasets, providing a practical tool for process analysis and optimization. Full article

Carbon fiber reinforced silicon carbide (C/SiC) composite material exhibits exceptional properties, including high strength, high stiffness, low density, outstanding high-temperature performance, and corrosion resistance. Consequently, they are widely used in aerospace, defense, and automotive engineering. However, their anisotropic, high hardness, and brittle characteristics make them a typical difficult-to-machine material. This paper focuses on achieving high-quality micro hole machining of C/SiC composite material via electrical discharge machining. It systematically investigates electrical discharge machining characteristics and innovatively develops a hollow internal flow helical electrode reaming process. Experimental results reveal four typical chip morphologies: spherical, columnar, blocky, and molten. The study uncovers a multi-mechanism cutting process: the EDM ablation of the composite involves material melting and explosive vaporization, the intact extraction and fracture of carbon fibers, and the brittle fracture and spalling of the SiC matrix. Discharge energy correlates closely with surface roughness: higher energy removes more SiC, resulting in greater roughness, while lower energy concentrates on m fibers, yielding higher vaporization rates. C fiber orientation significantly impacts removal rates: processing time is shortest at θ = 90°, longest at θ = 0°, and increases as θ decreases. Typical defects such as delamination were observed between alternating 0° and 90° fiber bundles or at hole entrances. Cracks were also detected at the SiC matrix–C fiber interface. The proposed hole-enlargement process enhances chip removal efficiency through its helical structure and internal flushing, reduces abnormal discharges, mitigates micro hole taper, and thereby improves forming quality. This study provides practical references for the EDM of C/SiC composite material. Full article

Network microstructure titanium matrix composites (NMTMCs) possess excellent performance and are promising for aerospace applications, yet their microstructural heterogeneity poses substantial challenges to achieving high-quality micro-machined surfaces. The aim of this study is to evaluate electrochemical machining (ECM) as a post-processing method for improving the surface quality of NMTMCs after electrical discharge machining (EDM). This study systematically examines the effects of electrolyte concentration, machining voltage, and pulse frequency on surface roughness. Electrochemical measurements in NaCl and NaNO₃ revealed that standalone electrochemical machining causes severe selective corrosion due to the large dissolution rate mismatch between TiBw reinforcements and the Ti-6Al-4V matrix, making it unsuitable for direct finishing. Accordingly, ECM was applied to EDM-prepared surfaces, and under optimized conditions (10 wt.% NaCl, 4.5 V, 200 kHz), ECM effectively mitigates the protrusions at the edges of discharge pits caused by the EDM process. Surface roughness (Sa) is significantly reduced from 0.90 μm to 0.45 μm, and the surface morphology becomes more uniform. These results demonstrate that ECM is a viable post-EDM finishing strategy for achieving high-quality micro-machining of NMTMCs. Full article