Studying the Effect of Working Conditions on WEDM Machining Performance of Super Alloy Inconel 617

Dzionk, Stefan; Siemiątkowski, Mieczysław

doi:10.3390/machines8030054

Cited by 23 publications

(15 citation statements)

References 25 publications

(38 reference statements)

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“…T off was found to have a reverse on MRR, in comparison to T on . An increase in T off reduces the intensity of the spark [ 51 , 52 ]. This further reduces the discharge energy, and subsequently, the MRR value also decreases with an increase in T off .…”

Section: Resultsmentioning

confidence: 99%

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

et al. 2022

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Shape memory alloy (SMA), particularly those having a nickel–titanium combination, can memorize and regain original shape after heating. The superior properties of these alloys, such as better corrosion resistance, inherent shape memory effect, better wear resistance, and adequate superelasticity, as well as biocompatibility, make them a preferable alloy to be used in automotive, aerospace, actuators, robotics, medical, and many other engineering fields. Precise machining of such materials requires inputs of intellectual machining approaches, such as wire electrical discharge machining (WEDM). Machining capabilities of the process can further be enhanced by the addition of Al2O3 nanopowder in the dielectric fluid. Selected input machining process parameters include the following: pulse-on time (Ton), pulse-off time (Toff), and Al2O3 nanopowder concentration. Surface roughness (SR), material removal rate (MRR), and recast layer thickness (RLT) were identified as the response variables. In this study, Taguchi’s three levels L9 approach was used to conduct experimental trials. The analysis of variance (ANOVA) technique was implemented to reaffirm the significance and adequacy of the regression model. Al2O3 nanopowder was found to have the highest contributing effect of 76.13% contribution, Ton was found to be the highest contributing factor for SR and RLT having 91.88% and 88.3% contribution, respectively. Single-objective optimization analysis generated the lowest MRR value of 0.3228 g/min (at Ton of 90 µs, Toff of 5 µs, and powder concentration of 2 g/L), the lowest SR value of 3.13 µm, and the lowest RLT value of 10.24 (both responses at Ton of 30 µs, Toff of 25 µs, and powder concentration of 2 g/L). A specific multi-objective Teaching–Learning-Based Optimization (TLBO) algorithm was implemented to generate optimal points which highlight the non-dominant feasible solutions. The least error between predicted and actual values suggests the effectiveness of both the regression model and the TLBO algorithms. Confirmatory trials have shown an extremely close relation which shows the suitability of both the regression model and the TLBO algorithm for the machining of the nanopowder-mixed WEDM process for Nitinol SMA. A considerable reduction in surface defects owing to the addition of Al2O3 powder was observed in surface morphology analysis.

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Section: Resultsmentioning

confidence: 99%

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

et al. 2022

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“…As a result, the width increases in accordance with the chips removal from the surface. Graph also indicate that the value of KW increases with levels of peak current for the reason that increased intensity of spark attributes to high spark energy generation caused by quantum electrons discharged from wire hitting with the dielectric fluid contributing in large ionization [31], [32]. High intensity spark and large ionization causes the widening of the kerf when considerable amount of ions strike with the test piece.…”

Section: Evaluation Of Kwmentioning

confidence: 93%

“…The quality of finished surface depends on variety of the mechanical and physical characteristics of the test surface particularly, resistance to corrosion, friction, fatigue stability, and loading competency [19], [31]. Thus, the quality of surface obtained throughout the machining of test piece is interpreted by the average roughness height (Ra) and termed as surface roughness (SR).…”

Section: Evaluation Of Srmentioning

confidence: 99%

Analysis of control factors and surface integrity during wire-EDM of Inconel 718 alloy using T-GRA approach

Asgar

Singholi²

2021

EMITTER Int'l J. of Engin. Technol.

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In today’s competitive modern manufacturing sectors, there is a vital need of utter precision and rigorous processing using various manufacturing approaches that directly influences the cost and processing duration of mechanized materials in addition to the consistency of the finished products. Therefore, it’s essential to figure out the required output by adjusting the control factors of any machining techniques which resulted in optimal values of the desired outcome. In this study, machining evaluation and process optimization is carried out on volumetric extraction of material namely material removal rate (MRR), kerf obtained during the machining (KW) and surface roughness (SR) of Inconel 718 superalloy during CNC controlled wire- electrical discharge machining. Four controllable factors- pulse interval, wire speed, pulse duration and peak current are considered to investigate the influence on performance measures. Taguchi's L16 has been used to construct the set of experiments before physical experimental runs and most influencing factors have been evaluated using ANOVA. SEM images and EDXS analysis have been resorted to examine the morphology of Inconel 718. These findings assist in identifying the topography of the machined surface. Further, the optimum integration has been obtained for the best yield and recorded using grey relational analysis integrated with Taguchi’s technique (T-GRA). The unfamiliarity of the work is based on consideration of zinc coated thin wire electrode and Taguchi-Grey combined approach of modelling with four levels of experimental design.

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“…Dzionk [17] and Meshram [18] argued that the occurrence of geometric deviations from circularity and cylindricality of an actual machined surface from a nominal surface after WEDM depends on several factors. First, these geometric deviations depend on the limit values of the accuracy of the hardware and software guidance of the wire electrode and the workpiece.…”

Section: Geometric Accuracy and Surface Roughness In Electrical Discharge Machiningmentioning

confidence: 99%

Adjustment of Wire Vibrations in Order to Improve Geometric Accuracy and Surface Roughness at WEDM

Straka

Čorný

2021

Applied Sciences

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Although WEDM is one of the most precise finishing technologies, deviations from the required geometric shapes and surface roughness occur in the production of parts with rotary surfaces. Even though these shortcomings have only a minimal impact on planar cuts, the production of circular profiles is a different problem. One of the factors causing this poor quality is the vibration of the wire electrode. With appropriate vibration adjustment, it would be possible to achieve significant improvements of the eroded area quality, both in terms of geometric accuracy and in terms of surface roughness. This would significantly increase quality, enabling WEDM technology to compete with other technologies in terms of economic efficiency. Therefore, the proposed solution aims to provide a partial adjustment to the wire tool electrode vibrations, based on their sensing by the means of acoustic emissions or a laser beam, with subsequent dynamic adjustment of the actual technological parameter values. This way, the given solution will increase the production accuracy of circular holes, increase productivity, and ultimately provide an overall increase in the economic efficiency of the WEDM process. The article also presents the scheme of a control algorithm for monitoring and subsequent adjustments of the vibrations of the wire tool electrode during the electroerosion process in order to minimize geometric deviations of circularity, cylindricity and roughness of the machined surface.

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Studying the Effect of Working Conditions on WEDM Machining Performance of Super Alloy Inconel 617

Cited by 23 publications

References 25 publications

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

Multi-Response Optimization of Al2O3 Nanopowder-Mixed Wire Electrical Discharge Machining Process Parameters of Nitinol Shape Memory Alloy

Analysis of control factors and surface integrity during wire-EDM of Inconel 718 alloy using T-GRA approach

Adjustment of Wire Vibrations in Order to Improve Geometric Accuracy and Surface Roughness at WEDM

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