Advances in Wire EDM Technology for Cutting Silicon Carbide Ceramics: A Review
Abstract
1. Introduction
1.1. Machining Characteristics of Silicon Carbide Ceramics
1.2. SiC Ceramic Types: Implications for WEDM Performance
1.3. Fundamentals of Wire Electrical Discharge Machining
2. Material Removal Mechanisms in WEDM
3. Process Parameters Influencing WEDM for SiC
4. Electrode Selection in WEDM Technology
5. Advances in WEDM Technology for SiC
5.1. Cryogenic Wire EDM: Enhancing Efficiency and Practicality
5.2. Eco-Friendly Approaches and Challenges in WEDM
6. Conclusions
- Using assisting electrodes can enhance the electrical conductivity of SiC during the WEDM process by introducing a conductive layer or material that is in contact with the SiC workpiece.
- Adjusting the pulse duration, discharge energy, and frequency can improve the efficiency of WEDM for SiC, with shorter pulse durations and lower discharge energies reducing thermal damage and improving surface quality.
- Utilizing advanced wire materials, such as coated or composite wires, can reduce wire wear and breakage, while specialized dielectric fluids with enhanced cooling and flushing capabilities can help dissipate heat more effectively and remove debris from the cutting zone.
- Implementing multi-wire EDM techniques can increase cutting efficiency and reduce kerf loss, as multiple wires are used simultaneously to slice through the SiC material.
- Combining WEDM with other machining processes, such as laser or ultrasonic machining, can enhance overall cutting performance. For instance, laser-assisted WEDM can be used to pre-treat the SiC surface, creating controlled microcracks that facilitate increased material erosion via subsequent electrical discharges. Similarly, ultrasonic-assisted WEDM, where high-frequency vibrations are applied to the wire or workpiece, can improve debris evacuation and dielectric circulation in the cutting zone, leading to a more stable process and improved surface finish. These hybrid approaches synergistically combine the strengths of different processes to overcome the inherent challenges of machining SiC. Finally, advanced temperature-control systems can help manage the heat generated during the WEDM process, ensuring consistent and high-quality cuts.
- To bridge the gap between academic research and industrial application, collaborative efforts are needed to establish standardized WEDM process parameters and testing protocols for different variants of SiC ceramics. This would enhance process reliability and consistency, a crucial step for wider adoption.
- Recent advancements in manufacturing are increasingly leveraging Artificial Intelligence (AI) and Machine Learning (ML) to optimize complex processes, and WEDM is no exception. For SiC machining, where the process window for achieving high quality and efficiency is narrow, AI offers significant potential. As noted in the literature, models such as Artificial Neural Networks (ANNs) and Machine Learning algorithms are already being used to predict outcomes for other materials. Applying these techniques to SiC could involve developing models to predict surface roughness, material removal rate, and the likelihood of microcrack formation based on real-time sensor data (e.g., discharge voltage, acoustic emissions). Such intelligent systems could enable real-time parameter adjustments to maintain process stability, prevent wire breakage, and ensure consistent part quality, moving beyond static optimization tables toward adaptive, intelligent manufacturing.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Industry | Part | Description | |
---|---|---|---|
Power | Used in power devices such as MOSFETs and diodes [2] | [3] | These components are usually small, measuring in the millimeter range, which allows for compact and efficient power conversion systems. |
Defense | Armor [4] | [5] | Large silicon carbide (SiC) components, measuring from centimeters to meters, are utilized for their exceptional strength and ability to withstand extreme conditions. |
Aerospace | Gas turbine engines | Reprinted with permission from Ref. [6]. Copyright 2022 Elsevier. | These components experience extremely high temperatures and harsh conditions within the engine. SiC’s exceptional thermal stability, high strength, and resistance to oxidation and thermal shock make it an ideal material for these applications. |
Nozzle vanes | [7] | These components must possess thermal stability and oxidation resistance under extreme temperature conditions. | |
Automotive | (EV) powertrains | [8] | The size of these components can vary, but they are generally designed to fit within the compact spaces of automotive systems. |
Biomedical devices | Biosensors [9], neural implants [10], dental implants [11] | [12] | Small components, ranging from millimeters to centimeters, are utilized for their biocompatibility and durability in advanced medical applications. |
Industry | Bearings | [13] | SiC is used in the production of high-performance brake disks. These discs offer superior thermal conductivity and wear resistance, improving braking performance and durability. |
Mechanical seals | [14] | SiC is used in mechanical seals for pumps and compressors, providing excellent wear resistance and extending the lifespan of these components. | |
Cutting tools | [15] | These are ideal for machining hard materials due to their exceptional wear resistance and hardness, making them suitable for cutting and grinding applications. |
Property | Value | Description |
---|---|---|
Density | ~3.15–3.21 g/cm3 | Low density contributes to lightweight components in high-performance applications. |
Hardness | ~25–28 GPa (Vickers) | Extremely high hardness, making it one of the hardest ceramics available. |
Thermal Conductivity | ~120–180 W/m·K | Excellent thermal conductivity, ideal for high-temperature environments. |
Thermal Expansion | ~4.0 × 10−6/K (20–1000 °C) | Low thermal expansion ensures dimensional stability under temperature variations. |
Flexural Strength | ~350–500 MPa | High strength across a wide range of temperatures. |
Compressive Strength | ~3900 MPa | Exceptional resistance to compression, ideal for structural applications. |
Elastic Modulus | ~410 GPa | High stiffness is suitable for precision engineering applications. |
Electrical Conductivity | Semi-conductive | Conductivity varies depending on doping; used in electronic devices. |
Chemical Resistance | High | Resistant to oxidation, acids, and bases, enhancing longevity in harsh environments. |
Property | SSiC | SiSiC | Doped SiC |
---|---|---|---|
Electrical Conductivity | Very low | Moderate (due to Si) | Moderate to high |
Hardness (Vickers, GPa) | ~25–28 | ~22–26 | ~20–27 |
Thermal Conductivity (W/m·K) | ~120–180 | ~130–160 | ~140–180 |
Brittleness | High | Moderate | Moderate |
WEDM Suitability | Requires enhancement | Suitable | Suitable |
Reference | Electrode | Assisting Electrode | Polarity | Peak Current | Pulse Duration | Pulse-off Time | Interval Time | Open Voltage | Servo Voltage | Wire Tension | Wire Feed Rate | Dielectric Flushing Pressure | Outcomes |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[59] | Brass (Ø 0.2 mm) | TiN (t = 3 μm) | Negative | 3.9 –4.9 A | 4 μs | 16 μs | 2.45 N | They reported that the most important considerations for slicing ultra-thin wafers are balancing the wafer thickness, kerf loss, and slicing rate. A wafer thickness of 150 μm with a slicing rate of 1.05 mm/min and kerf loss of 121 μm is optimal for minimizing material waste while maintaining efficiency. The use of response methodology and composite desirability optimization reduced kerf loss by 40–50%. Surface analysis revealed crack-free wafers with minor defects such as dents and holes, highlighting complex material removal phenomena during machining. | |||||
[60] | 0.3 μs | 20 μs | 4 N | 62 | 10 (bar/kg) | By increasing servo voltage, the kerf loss and the inter-electrode gap also increased, leading to significant debris accumulation on the machined surface. | |||||||
[25] | Brass (Ø 0.2 mm) | Negative | 80 V | 58 V | 8 | 8 | When the tool electrode has a negative polarity, a higher machining speed and a lower tool wear ratio will be reached during foil EDM of SiC with short pulse durations. Due to the larger kerf width and slower machining speed, long pulse durations are not acceptable for SiC EDM. | ||||||
[61] | Brass (Ø 0.2 mm) | 50.85 mm/14.3 mm | 1 | 4 μs | 3.5 μs | 100 V | 75 V | 20 N | 80 m/min | 2 l/min | They investigated the efficiency and quality of slicing under oil- and water-based Wire Electrical Discharge Machining (WEDM) conditions. Water machining is faster at a discharge current of 1 A, but only by about 1.1-fold compared to that of oil machining. Additionally, the average width of the machined groove during water machining at 1 A is smaller than that of oil machining. The groove width remains wider even at a discharge current of 0.7 A for water machining compared to a discharge current of 1 A for oil machining. | ||
[62] | Zinc-coated (Ø 0.25 mm) | Negative | 11.2 A | 12.82 (μs) | 42 V | 600 g | 10 m/min | Because of its high electrical resistivity and thermal conductivity, SiSiC requires a high sparking power during EDM machining. To initiate the spark and for it to remain stable, in this study, a high peak current was necessary. The high thermal conductivity of the material triggered heat loss owing to the conductivity that decreased the energy output of the operation. The connection between machining parameters and several responses was established experimentally. Statistical analysis provided a clear understanding on the influence of the machining parameter, elucidated by validated mathematical models. | |||||
[63] | (EDM-C3 grade) | Negative | 32 A | 3.2 µs | 100 µs | −200 V | They observed that using high-energy parameters, such as elevated peak currents and prolonged discharge durations, during the machining of conductive SiC led to instability in the process and caused significant damage to both the surface and subsurface of the material. When material melts and evaporates with high-energy discharge, there is not enough time for it to be ejected before it resolidifies. | ||||||
[64] | Molybdenum (Ø 0.18 mm) | Workpiece (+) | 6 A | 5 µs, 10 µs, 20 µs, 40 µs, 80 µs. | 8 × Ton | Ton + Toff | 140 V | 7.2 m/s | They assessed the damage of a particular crystal face of single-crystal silicon, studying various input variables for EDM. In experiments with a variable pulse width, differences were found in material removal mechanisms. Analysis indicates that, during semiconductor processing, the melting and vaporization resulting from prolonged discharge pulses do not remove more material than the thermal stresses and explosive forces generated by brief pulses. Extended pulses often result in a concentration of the discharge, which can lead to an unpredictable process. | ||||
[65] | Molybdenum (Ø 0.18 mm) | 2 A, 3 A, 4 A. | 100 µs, 130 µs, 150 µs. | 11 m/min | 30 kPa, 40 kPa, 50 kPa. | In the examination of material removal rate (MRR), it was discovered that the pulse-on time, along with its interplay with powder concentration and current, was an important factor. Pressure also proved to be significant. The findings demonstrated that a longer pulse-on time was associated with a lower MRR. Furthermore, the outcomes were exactly understood when these relations were taken into account. Specifically, a higher pulse-on time combined with low to average powder concentrations (2 and 4 g/l) is expected to distribute or dilute the effect of heat intensity, which in turn reduces the MRR. However, increasing the powder concentration to 6 g/l resulted in an improvement, likely due to enhanced bridging phenomena. |
Author/Year | Wire Material | Work Material | Input Variables | Responses | Optimization Method | Key Observations |
---|---|---|---|---|---|---|
[70] Sheth et al. (2020) | Molybdenum (Ø 0.018 mm) | Mg-Zn-RE-Zr Alloy | Current, Ton, Toff, Wire Feed Rate | Surface Roughness | CCD + RSM + PVS | Toff is least influential; Ton and current are dominant |
[71] Ali et al. (2025) | Molybdenum (Ø 0.18 mm) | AA2024/Al2O3/SiC/Si3N4/BN Hybrid Composite | Voltage, Current, Gap, Wire Feed, Wire Speed | Ra, CS, KW | Taguchi DOE, Desirability Index, SEM, Topography, ANOVA | Achieved smoother Ra and higher CS for complex profiles using optimal WEDM settings; reduced KW and minimized craters |
[72] Das & Joshi (2025) | Zinc-Coated Brass (Ø 0.25 mm) | Ti-6Al-4V | Voltage, Current, Pulse-On/Off Time | Crater Volume, Wire Stress, Wire Failure Risk | 3D Thermo-Mechanical FEM, Experimental Validation | Predicted wire breakage based on crater volume; defined wire failure threshold; model improves tool longevity and sustainability |
[73] Soundararajan et al. (2020) | Zinc-Coated Brass (Ø 0.25 mm) | A413 + 12 wt% B4C Composites | Ton, Toff, Peak Current | MRR, Surface Roughness | CCD + RSM | Ton significantly affects MRR and SR; Toff reduces SR |
[74] Kumar et al. (2019) | Brass (Ø 0.25 mm) | Inconel 825 | Ton, Toff, Peak Current, Spark Gap, Wire Tension, Wire Feed | MRR, Surface Roughness, Wire Wear Ratio | RSM + Desirability Approach | Ton, gap voltage, and peak current positively impact MRR; Toff negatively affects SR |
[75] Alduroobi et al. (2020) | Brass (Ø 0.25 mm) | AISI 1045 Steel | Ton, Toff, Servo Feed (SF) | MRR, SR | ANN | MRR optimal: Ton = 25 μs, Toff = 20 μs, SF = 30 mm/min; SR optimal: Ton = 10 μs, Toff = 40 μs, SF = 0 mm/min |
[76] Abbas et al. (2023) | SS-304, Copper, Brass | Al/SiC/Gr Composite | Ton, Toff, SV, I, Tool Electrode | MRR, TWR | RSM + COPRAS + Machine Learning | Ton: 60, Toff: 60, SV: 7, I: 12; brass tool had highest TWR |
[77] Sharma et al. (2013) | Brass | High-Strength Low-Alloy Steel (HSLA) | Ton, Toff, Peak Current, SV | MRR, Surface Roughness | RSM | Ton ↑ → SR ↑; Toff ↑ & I ↓ → better SR |
[78] Khanna et al. (2022) | Brass (Ø 0.25 mm) | Al/SiC/Ti Hybrid Composite | Ton, Toff, SV, Wire Feed | Cutting Speed (CS), Kerf Width (Kw) | BBD + RSM + Teaching-Learning-Based Optimization (TLBO) | Ton strongly affects CS; SV influences Kw |
Cryogenic Fluid | Temperature (°C) | Nature | Availability in Nature | Notes |
---|---|---|---|---|
Helium 3 | −269.96 | Inert Gas | 5 ppm | Rare isotope |
Helium 4 | −268.94 | Inert Gas | 5 ppm | Common isotope |
Hydrogen | −252.88 | Combustible | 0.6 ppm | Highly combustible gas |
Neon | −246.06 | Neutral | 18 ppm | Used in lighting |
Nitrogen | −196.06 | Neutral | 78.09% | Major component of air |
Mixture of Air | −194.35 | Neutral | 100% | Air composition |
Fluorine | −187.91 | Toxic | 0.6 ppb | Highly toxic |
Argon | −185.91 | Inert Gas | 0.94% | Used in welding |
Oxygen | −182.97 | Flammable | 20.95% | Supports combustion |
Methane | −161.45 | Flammable | 1866 ppb | Natural gas component |
Carbon Dioxide | −56.6 | Neutral | 0.04% | Greenhouse gas |
Author(s), Year | Eco-Friendly Approach | Method/Principle | Environmental Benefit | Relevance to SiC Machining |
---|---|---|---|---|
[104] Boopathi et al., 2021 | Near-Dry WEDM | Compressed air + water mist as dielectric | Reduces toxic emissions, improves operator safety | The possibility of reducing dielectric contamination in brittle ceramics such as SiC |
[104] Boopathi et al., 2021 | Pulse Parameter Optimization | Adjusting pulse-on/off times and discharge energy | Reduces energy usage and gas emissions | Adjusting for SiC conductivity limits may improve both efficiency and quality |
[105] Das et al., 2020; [102] Camposeco-Negrete., 2021 | Green Dielectrics (e.g., Bio-Oils) | Use of biodegradable dielectrics like vegetable oils or nano-emulsions | Lower toxicity, safer handling, reduced disposal issues | Under investigation for ceramics such as SiC |
[106] Ng et al., 2016 | Multi-Objective Optimization (Taguchi + TLBO) | Hybrid optimization method for energy, Ra, MRR, and kerf width | Balances multiple eco-efficiency metrics | Can be adapted for SiC if mechanical and electrical properties are considered |
[107] Venkatarao et al., 2023 | Deionized Water as Dielectric | Substitution of hydrocarbon oils with deionized water | Lower environmental impact, cleaner machining process | Effective for SiC when combined with auxiliary electrode or conductivity coating |
[108] Ming et al., 2019 | Magnetic-Field-Assisted WEDM | Enhancing debris evacuation using magnetic fields | Improves MRR and reduces thermal input | Underexplored for SiC, but promising for heat-sensitive materials |
[109] He et al., 2020 | Energy Prediction Using ML | Machine learning-based prediction of energy consumption | Enables pre-optimization of energy-intensive cycles | Could guide parameter design in SiC machining for better efficiency |
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Fard, M.G.; Petru, J.; Hloch, S. Advances in Wire EDM Technology for Cutting Silicon Carbide Ceramics: A Review. Materials 2025, 18, 3955. https://doi.org/10.3390/ma18173955
Fard MG, Petru J, Hloch S. Advances in Wire EDM Technology for Cutting Silicon Carbide Ceramics: A Review. Materials. 2025; 18(17):3955. https://doi.org/10.3390/ma18173955
Chicago/Turabian StyleFard, Mohammad Ghasemian, Jana Petru, and Sergej Hloch. 2025. "Advances in Wire EDM Technology for Cutting Silicon Carbide Ceramics: A Review" Materials 18, no. 17: 3955. https://doi.org/10.3390/ma18173955
APA StyleFard, M. G., Petru, J., & Hloch, S. (2025). Advances in Wire EDM Technology for Cutting Silicon Carbide Ceramics: A Review. Materials, 18(17), 3955. https://doi.org/10.3390/ma18173955