WEDM performance and surface integrity of Inconel alloy IN718 with coated and uncoated wires

Reolon, Luca Watanabe; Laurindo, Carlos Augusto Henning; Torres, Ricardo; Amorim, Fred L.

doi:10.1007/s00170-018-2828-6

Cited by 44 publications

(21 citation statements)

References 18 publications

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“…Proper selection of input process parameters is a key factor in the WEDM process to avoid wire rupture problems and the formation of larger craters on the work surface [18]. In past research, electrodes of brass and copper wires have been used for surface analysis of SMAs for samples machined by WEDM [19,20].…”

Section: Introductionmentioning

confidence: 99%

Effect of WEDM Process Parameters on Surface Morphology of Nitinol Shape Memory Alloy

et al. 2020

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Nickel–titanium shape memory alloys (SMAs) have started becoming popular owing to their unique ability to memorize or regain their original shape from the plastically deformed condition by means of heating or magnetic or mechanical loading. Nickel–titanium alloys, commonly known as nitinol, have been widely used in actuators, microelectromechanical system (MEMS) devices, and many other applications, including in the biomedical, aerospace, and automotive fields. However, nitinol is a difficult-to-cut material because of its versatile specific properties such as the shape memory effect, superelasticity, high specific strength, high wear and corrosion resistance, and severe strain hardening. There are several challenges faced when machining nitinol SMA with conventional machining techniques. Noncontact operation of the wire electrical discharge machining (WEDM) process between the tool (wire) and workpiece significantly eliminates the problems of conventional machining processes. The WEDM process consists of multiple input parameters that should be controlled to obtain great surface quality. In this study, the effect of WEDM process parameters on the surface morphology of nitinol SMA was studied using 3D surface analysis, scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX) analysis. 3D surface analysis results indicated a higher value of surface roughness (SR) on the top of the work surface and a lower SR on the bottom portion of the work surface. The surface morphology of the machined sample obtained at optimized parameters showed a reduction in microcracks, micropores, and globules in comparison with the machined surface obtained at a high discharge energy level. EDX analysis indicated a machined surface free of molybdenum (tool electrode).

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Section: Introductionmentioning

confidence: 99%

Effect of WEDM Process Parameters on Surface Morphology of Nitinol Shape Memory Alloy

et al. 2020

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“…Muthuramalingam et al [38] observed that a diffused type of brass electrode produces better surface morphology in comparison with conventional brass wire or zinc coated electrodes. Reolon et al [39] concluded that zinc coated copper wire produces better surface integrity for WEDMed Inconel alloy IN718 in comparison with uncoated brass wire. Thus, from the present analysis, the surface integrity of EN 31 could be improved without any post-processing or complexity while machining using WEDM.…”

Section: Resultsmentioning

confidence: 99%

Modeling and Optimization of Fractal Dimension in Wire Electrical Discharge Machining of EN 31 Steel Using the ANN-GA Approach

et al. 2019

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To achieve enhanced surface characteristics in wire electrical discharge machining (WEDM), the present work reports the use of an artificial neural network (ANN) combined with a genetic algorithm (GA) for the correlation and optimization of WEDM process parameters. The parameters considered are the discharge current, voltage, pulse-on time, and pulse-off time, while the response is fractal dimension. The usefulness of fractal dimension to characterize a machined surface lies in the fact that it is independent of the resolution of the instrument or length scales. Experiments were carried out based on a rotatable central composite design. A feed-forward ANN architecture trained using the Levenberg-Marquardt (L-M) back-propagation algorithm has been used to model the complex relationship between WEDM process parameters and fractal dimension. After several trials, 4-3-3-1 neural network architecture has been found to predict the fractal dimension with reasonable accuracy, having an overall R-value of 0.97. Furthermore, the genetic algorithm (GA) has been used to predict the optimal combination of machining parameters to achieve a higher fractal dimension. The predicted optimal condition is seen to be in close agreement with experimental results. Scanning electron micrography of the machined surface reveals that the combined ANN-GA method can significantly improve the surface texture produced from WEDM by reducing the formation of re-solidified globules.

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“…Moreover, it was found out that water dielectric and the surface alloying was evident in main cut, which can be minimized in trim cuts. Reolon et al [18] studied the surface integrity and the performance of the WEDM process of Inconel alloy IN718. During the experiments a zinc-coated copper wire and an uncoated brass wire were used while analysing input and output process variables.…”

Section: Introductionmentioning

confidence: 99%

Machining of B1914 nickel-based superalloy using wire electrical discharge machining

Mouralová

Polzer

Beneš

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part E:

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The unconventional technology of wire electrical discharge machining is a key engineering technology, designed primarily for machining of conventionally difficult machine materials. One of them is nickel alloys, which are majorly used in the aerospace and energy industries. The subject of research in this study was specifically the B1914 nickel-based superalloy, which was subjected to many analyses leading to an overall optimization of its machining using wire electrical discharge machining. In order to determine the effect of machine parameters setup (pulse off time, gap voltage, discharge current, pulse on time and wire feed) on cutting speed, topography, morphology, surface and subsurface layer quality, an extensive Box–Behnken design experiment consisting of 46 rounds was carried out. The analyses of the condition of the surface and subsurface layers were performed, including their chemical composition and changes caused by wire electrical discharge machining. It was found out that the factors like pulse off time, discharge current and pulse on time have the greatest effect on the cutting speed, although from the point of view of surface topography the parameter pulse off time is not significant. The remaining two parameters cause the cutting speed to act against the surface topography i.e. with the increasing cutting speed, the surface topography gets worse and vice versa.

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WEDM performance and surface integrity of Inconel alloy IN718 with coated and uncoated wires

Cited by 44 publications

References 18 publications

Effect of WEDM Process Parameters on Surface Morphology of Nitinol Shape Memory Alloy

Effect of WEDM Process Parameters on Surface Morphology of Nitinol Shape Memory Alloy

Modeling and Optimization of Fractal Dimension in Wire Electrical Discharge Machining of EN 31 Steel Using the ANN-GA Approach

Machining of B1914 nickel-based superalloy using wire electrical discharge machining

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