Influence of tool steel properties on surface quality after electrical discharge machining by wire electrode

Straka, Ľuboslav; Dittrich, Gabriel

doi:10.1007/s00170-019-04708-9

Cited by 11 publications

(2 citation statements)

References 18 publications

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“…These reasons led us to perform experimental research, the goal of which was to achieve significant progress in optimizing the quality of the machined surface while maintaining high productivity of the electrical discharge process. At the same time, we would like to contribute to the database of already existing knowledge through clear formulations of particular laws in relation to the processes that take place directly on the machined surface during the electrical discharge [ 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 ].…”

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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“…Several experimental investigations were carried out, the aim of which was to contribute to the reduction of wear of the wire tool electrode (TWR) while increasing the MRR and the overall productivity of the electrical discharge process. Most of these experimental studies included new approaches to solving shortcomings in the process of EDM with a wire electrode, including identification of the morphology of the machined surface, modeling, optimization, and direct application of the results obtained from experimental research to applications in science and technology in the field of EDM of selected types of materials [14]. However, very few researchers have devoted themselves to the mutual optimization of the abovementioned output qualitative and quantitative parameters of the electrical discharge process.…”

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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Machinability investigations through novel controlled flushing characteristics in wire electric discharge machining of M42 high-speed steel

Ehsan

Rehman

Mughal

et al. 2022

Int J Adv Manuf Technol

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Influence of tool steel properties on surface quality after electrical discharge machining by wire electrode

Cited by 11 publications

References 18 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

Machinability investigations through novel controlled flushing characteristics in wire electric discharge machining of M42 high-speed steel

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