Editorial for the Special Issue on Micro-Electro Discharge Machining: Principles, Recent Advancements and Applications, Volume II

Fassi, Irene; Modica, Francesco

doi:10.3390/mi14010029

Cited by 5 publications

(2 citation statements)

References 10 publications

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“…An electric discharge between the cathode and the anode always occurs when the basic conditions are met [ 8 ]. With continuous electric discharges, a temperature of 8000 to 12,000 °C is reached in the spark gap, thanks to which the metal particles from the machined material melt or evaporate, and the residues are subsequently washed away with a dielectric liquid [ 9 , 10 ]. The wire tool electrode is also important in the micro-WEDM process because it affects the cutting speed, dimensional accuracy, and the quality of the machined surface [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Simulation and Optimization of Surface Roughness and Process Performance during Machining of HSS by Micro-WEDM Technology

Straka,

Čorný

2024

Micromachines

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When machining high-speed steels (HSS) with micro-wire electrical discharge machining (micro-WEDM), high surface quality is achieved as standard. The value of the roughness parameter Ra is less than 0.2 μm. However, the problem is the performance of the electroerosion process (MRR), which is low. This problem is related to the mechanical and physical properties of the HSS in combination with the setting of the main technological parameters (MTP). The proposed solution to eliminate this problem relies on the selection of proper procedures for the determination of optimization criteria in relation to Ra and MTP, with the inclusion of properties of the machined material. The solution consisted in the identification of four significant physical (ρ, κ) and mechanical (Rm, HRC) indicators of HSS properties, on the basis of which a suitable combination of the process output parameters Ra and MRR can be determined through established mathematical regression models using simulation and optimization. In the next step, the proper values of the MTP output process parameter settings, which correspond to the optimized output parameters Ra and MRR during machining of HSS by micro-WEDM technology, were then obtained by the same approach.

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Section: Introductionmentioning

confidence: 99%

Simulation and Optimization of Surface Roughness and Process Performance during Machining of HSS by Micro-WEDM Technology

Straka,

Čorný

2024

Micromachines

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“…Multiparametric optimization appears to be a suitable solution to this problem. As part of multiparametric optimization, it is necessary to pay particular attention to qualitative indicators of the machined surface that have a significant impact on the overall quality of the finished product while significantly affecting the overall productivity of the electrical discharge process [4][5][6]. The execution of multiparametric optimization of the quality of a machined surface is based on the search for a suitable combination of settings for the main technological parameters.…”

Section: Introductionmentioning

confidence: 99%

Prediction and Multiparametric Optimization of the Machined Surface Quality of Tool Steels in Precise Wire Electrical Discharge Machining

Straka,

Čorný

2024

Machines

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This article describes a proposed procedure for multiparametric optimization of the quality of machined surfaces, including mathematical models that can predict the high quality of a precisely machined surface and, at the same time, the high productivity of the process in WEDM of tool steels. The experimental research was carried out using the full DoE factorial design method, which has four technological parameters. The measured output qualitative parameter Surface Roughness (SR) and the output quantitative parameter Material Removal Rate (MRR) were evaluated using the Grey Relational Analysis (GRA) and Analysis of Variance (ANOVA) methods. Multiple Regression Models (MRM) were developed to represent the multiple responses of the investigated tool steels using a regression tool set. The results of the multiparametric optimization revealed a correlation between the input variable parameters of the electrical discharge process, while the favorable results of the observed output-dependent parameters SR and MRR were coupled to the parameters of low peak current I, low value of pulse on-time duration ton, low voltage of discharge U, and high value of pulse off-time duration toff. Based on the multiparametric optimization, key results were obtained that demonstrated the mutual dependence of the observed output process parameters. An optimum SR value of 1.50 μm was obtained with L8-level settings for the input variable parameters I, ton, U, and toff (2 A, 32 μs, 90 V, and 20 μs, respectively) and an MRR value of 12.50 mm3·min−1 was achieved.

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Controlling recast layer and material removal in reverse µEDM for sustainable fabrication of microelectrode arrays

Pratap,

Datta,

Sharma

2024

Proceedings of the Institution of Mechanical Engineers, Part E:

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Microelectrode arrays (MEAs) are essential for researching neurons and heart tissue because they record and stimulate neuronal activity. For manufacturing MEAs on conductive materials, reverse microelectrical discharge machining, or reverse µEDM, presents a viable method. However, achieving precise MEAs requires control over recast layers generated during micromachining. This study focuses on recast layer thickness (RLT) and material removal rate (MRR) as key performance indicators for sustainable reverse µEDM fabrication of MEAs. RLT affects surface stability, while MRR influences energy consumption and cost. Optimising these responses depends on three input factors: feed rate, capacitance, and voltage. ANOVA analysis reveals that capacitance is crucial in both MRR and recast layer thickness (RLT) in reverse µEDM, contributing to 88.71% and 94.04% simultaneously. A hybrid artificial neural network-genetic algorithm for global optimisation was employed. The optimised parameters 46.5nF capacitance, 110 V voltage, and 5 µm/sec feed yielded a minimum RLT of 1.58 µm and a maximum MRR of 0.3 mm³/min. These advancements signify significant improvements in the precision and efficiency of MEAs fabrication through reverse µEDM, contributing to its sustainable implementation.

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Editorial for the Special Issue on Micro-Electro Discharge Machining: Principles, Recent Advancements and Applications, Volume II

Cited by 5 publications

References 10 publications

Simulation and Optimization of Surface Roughness and Process Performance during Machining of HSS by Micro-WEDM Technology

Simulation and Optimization of Surface Roughness and Process Performance during Machining of HSS by Micro-WEDM Technology

Prediction and Multiparametric Optimization of the Machined Surface Quality of Tool Steels in Precise Wire Electrical Discharge Machining

Controlling recast layer and material removal in reverse µEDM for sustainable fabrication of microelectrode arrays

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