Search Results (282)

Electric discharge machining (EDM) has a unique ability to accurately cut exotic, hard-to-cut materials such as titanium without physical contact, with negligible force and vibration. Such a characteristic makes it a promising machining technique to be combined with robot manipulators to maximise the flexibility of the working envelope. Such a combination enabled robots to make a more sustainable cut of large, monolithic, and complex workpieces used in relevant defence and aerospace industries. The concept has been proven through a feasibility study prototype using wire EDM, followed by rotational milling EDM configurations. The wire EDM configuration was challenging due to instability in the wire control system and tension. The milling EDM configuration has been proven successful for intricate geometries. However, it involves removing large amounts of material and is thus not ideal for large geometries or deep cuts. Thus, to further explore sustainable robotic EDM for large workpieces without vaporising significant amounts of scarce, exotic, hard-to-cut materials, new inventive tools are needed. Therefore, this research aims to present a new knife EDM (KEDM) end-effector concept as a pure simulation capable of making large, deep cuts on a titanium workpiece without interruption. Using the TRIZ algorithm, engineering constraints are overcome to propose a KEDM design that vibrates and operates like a large WEDM, without frequent wire breakage, setup, or restarts. This research further explores the proposed end-effector through a digital twin kinematic simulation to find and demonstrate the extent of the machined workpiece and the robot’s enlarged workspace. Full article

Fast-switching transients and high dv/dt associated with PWM inverters exacerbate the reflected-wave effects in the motor feeder cable. This leads to higher motor-side overvoltages, which increase the stress on the motor winding insulation, potentially accelerating insulation degradation and increasing the risk of partial discharge within the motor windings. Moreover, the common-mode voltages at the motor terminals propagate through parasitic capacitive paths within the motor, inducing shaft voltages that lead to electric discharge machining (EDM) currents and premature bearing failure. This paper experimentally investigates the influence of motor feeder cable length and type (shielded and unshielded) on motor terminal overvoltage, shaft voltage, and bearing current behavior in an inverter-fed 11 kW permanent magnet synchronous motor drive system. Three cable lengths (1 m, 3 m, and 16 m) with shielded and unshielded configurations are evaluated under identical operating conditions. Measurements of line-to-line voltage, line-to-ground voltage, shaft voltage, bearing current, and EDM discharge currents are recorded and statistically analyzed to assess the influence of cable configuration. The study also examines the influence of the motor grounding configuration on common-mode current and bearing current behavior. Overall, the findings provide comprehensive insights into the influence of motor feeder cable on overvoltage, shaft voltage, and bearing discharge behavior, supporting informed cable selection for WBG inverter-fed electric drives. Full article

Bearing damage caused by electric discharge machining (EDM) is a concern in electric ship propulsion drives, particularly during low-speed operations such as maneuvering and slow steaming. In a modular multilevel converter (MMC) operated with nearest-level modulation (NLM), rounding of the three-phase submodule insertion numbers produces a residual imbalance that appears as common-mode voltage (CMV) and charges the bearing film capacitance. The peak bearing voltage rises from 6.4 V at 60 Hz to 20.0 V at 10 Hz, while the thinning lubricant film lowers the dielectric breakdown threshold. Always-on CMV reduction approaches apply a corrected switching candidate in every control period, including intervals where the bearing voltage stays well below the threshold. This paper proposes a selective NLM correction driven by predicted bearing voltage risk: a reduced-order RC model predicts the bearing voltage the conventional NLM candidate would produce, and a hysteretic controller applies a zero-CMV candidate only when that prediction approaches the insulation threshold. Using a worst-case discharge criterion and thresholds of 5.9–29 V derived from elastohydrodynamic film thickness estimates, simulations at 10 Hz show that the method eliminates EDM events over the full evaluated threshold range. It achieves the same zero-EDM outcome as always-on correction while reducing the correction mode activation ratio from 100% to at most 30.8%, and remains inactive where conventional NLM is already safe. Full article

Electrical discharge machining (EDM) demonstrates significant advantages in machining difficult-to-cut materials, particularly those with high hardness and brittleness, owing to its thermally driven material removal mechanism in which the arc plasma serves as the heat source. However, machining performance varies markedly across different workpiece materials. Such differences are likely attributable to the coupled effects of arc plasma characteristics, which may vary with tool–workpiece material combinations, and the thermophysical properties of the workpiece. Nevertheless, the mechanisms underlying this coupling remain poorly understood. In this study, arc plasma characteristics and material removal behavior under different material combinations were investigated using arc plasma and thermo-hydrodynamic simulation models. Under positive polarity, a copper tool electrode was paired with 304 stainless steel, Ti-6Al-4V, and Inconel 718 workpieces, while copper and tungsten electrodes were compared using a 304 stainless steel workpiece. Simulation results show that material combinations significantly affect anode heat flux and energy distribution, with 304 stainless steel exhibiting the highest heat flux and Inconel 718 receiving the largest energy distribution ratio. Crater depth correlates strongly with heat flux magnitude, while crater diameter is jointly determined by heat flux radius and melt flow dynamics, with the selected cathode material exerting only minor influence. High-speed imaging and crater morphology measurements validate the simulation results, confirming model reliability. These findings provide theoretical guidance for process optimization in EDM. Full article

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