Prediction of white layer formation in μ-WEDM process of NiTi shape memory superalloy: FEM with experimental verification

Ilkhchi, Reza Najati; Akar, Samet; Meshri, Hassan Ali M.; Seyedzavvar, Mirsadegh

doi:10.1007/s00170-021-06796-y

Cited by 5 publications

(2 citation statements)

References 28 publications

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“…The second important factor that has a strong influence on the parameters of WEDM is the conditions of machining. Ilkhchi et al [ 11 ] indicated that in addition to the parameters that define the discharge energy, the dielectric flow has an influence on the process of material removal. The turbulent dielectric flow in the gap increases the efficiency of flushing in the gap and removing molten material from the craters, which have a strong influence on the surface morphology.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods

2022

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Precise machining of micro parts from difficult-to-cut materials requires using advanced technology such as wire electrical discharge machining (WEDM). In order to enhance the productivity of micro WEDM, the key role is understanding the influence of process parameters on the surface topography and the material’s removal rate (MRR). Furthermore, effective models which allow us to predict the influence of the parameters of micro-WEDM on the qualitative effects of the process are required. This paper influences the discharge energy, time interval, and wire speed on the surface topography’s properties, namely Sa, Sk, Spk, Svk, and MRR, after micro-WEDM of Inconel 718 were described. Developed RSM and ANN model of the micro-WEDM process, showing that the discharge energy had the main influence (over 70%) on the surface topography’s parameters. However, for MRR, the time interval was also significant. Furthermore, a reduction in wire speed can lead to a decrease in the cost process and have a positive influence on the environment and sustainability of the process. Evaluation of developed prediction models of micro-WEDM of Inconel 718 indicates that ANN had a lower value for the relative error compared with the RSM models and did not exceed 4%.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods

2022

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“…μ-WEDM süreç parametrelerinin etkilerini simüle etmek için bir sonlu eleman modeli (FEM) geliştirmişlerdir. Parametrelerinin beyaz tabaka oluşumu üzerindeki etkilerini, FEM sonuçlarına dayalı olarak ayrıntılı olarak inceleyip tahmin hata payının %14 olduğunu belirtmişlerdir [11]. Muthuramalingam ve diğ.…”

Section: Introductionunclassified

The Effect of Cutting Parameters on White Layer Thickness and Surface Hardness in Wire EDM of Heat-treated D2 Cold Work Tool Steel

Ballikaya

Altuğ

2021

International Journal of Innovative Engineering Applications

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Original scientific paperIn this study, the effects of cutting parameters of Sverker 21 cold work tool steel on the white layer and cutting surface hardness of the post-processing material were investigated using wire erosion (WEDM) method. The purpose of using high alloy steel; It is widely used in the molding industry due to its high hardness, wear resistance and toughness properties depending on the alloying element and carbon ratio it contains. Both commercial and heat-treated cold work tool steel were used in the experimental studies. Commercial sample and heat-treated sample, time between two arcs (µs), voltage (V), liquid pressure (bar), wire tension (g), wire feed rate (m/min) were used as cutting parameters. Materials were cut using the Taguchi experimental design plan and the L18 orthogonal array for the experiment design. As a result, the machined surface hardness and the regenerated white layer thickness were investigated. According to the ANOVA method, the most effective parameter on the white layer thickness is the commercial and heat-treated sample parameter with 57,236%. In the cut surface hardness values, the most effective parameter was the sample parameter at the rate of 98.627%.

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Surface Microstructure Evolution and Mechanical Property Investigation of Inconel 718 Alloy Using Multiple Trimmings and WEDM

Sun,

Shi,

et al. 2024

Exp Tech

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Prediction of white layer formation in μ-WEDM process of NiTi shape memory superalloy: FEM with experimental verification

Cited by 5 publications

References 28 publications

Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods

Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods

The Effect of Cutting Parameters on White Layer Thickness and Surface Hardness in Wire EDM of Heat-treated D2 Cold Work Tool Steel

Surface Microstructure Evolution and Mechanical Property Investigation of Inconel 718 Alloy Using Multiple Trimmings and WEDM

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