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E. Bayraktar

Bio: E. Bayraktar is an academic researcher. The author has contributed to research in topics: Electrical discharge machining & Surface integrity. The author has an hindex of 1, co-authored 1 publications receiving 24 citations.

Papers
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Journal ArticleDOI
TL;DR: In this article, a simple and easily understandable model was proposed for predicting the relative importance of different factors (composition of the steels and Electro Discharge Machining processing conditions) in order to obtain an efficient pieces.
Abstract: Electrical discharge machining (EDM) is one of the earliest non-traditional machining processes. EDM process is based on thermoelectric energy between the work piece and an electrode. There are various types of products which can be produced by using the EDM such as dies and moulds. Today many parts used in aerospace and automotive industry and also final processes of surgical components can be finished by EDM process. A simple and easily understandable model was proposed for predicting the relative importance of different factors (composition of the steels and Electro Discharge Machining processing conditions) in order to obtain an efficient pieces. A detail application on the tool steels machined by EDM was given in this study. This model is based on thermal, metallurgical and mechanical and also in situ test conditions. It gives detail information on the effect of electrochemical parameters on the surface integrity and sub-surface damage of the material (Heat Affected Zone, HAZ), the level of residual stresses, and the surface texture. This approach is an efficient way to separate the responsibilities of the steel maker and machining process designer for increasing the reliability of the machined structures.

25 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, the performance of the electrical discharge machining (EDM) process is evaluated in terms of material removal rate, relative wear ratio and surface roughness of the work piece.

116 citations

Journal ArticleDOI
TL;DR: In this paper, an attempt is made to relate the globule formation on the machined surface, with the machining current, and the white layer thickness, globule diameter and interglobule distance are found to increase with the increase in electric current.
Abstract: Electric discharge machining (EDM) produces a recast/white layer on the surface of the machined workpiece. Machining with EDM generally produces a higher surface roughness as compared to conventional machining processes. The operating parameters in EDM, i.e., “current”, “voltage”, “on time” and “off time” are directly related with the white layer formation, its thickness, morphology and roughness. Machining of Al 6061 T6 cylinders is performed on die-sinking EDM machine with varying electric current values to determine its effect on surface morphology in the case of aluminum alloy. Material removal rate versus current is determined for different current values. An attempt is made to relate the globule formation on the machined surface, with the machining current. Scanning electron microscopy, optical microscopy and material composition study through energy dispersive spectrography are performed. The white layer thickness, globule diameter and inter-globule distance are found to increase with the increase in electric current.

66 citations

Journal ArticleDOI
TL;DR: In this article, the authors used the same value of fraction of energy transferred to electrodes for all machining parameters in their models for numerically calculating the volume and geometry of the crater formed.

35 citations

Journal ArticleDOI
TL;DR: In this paper, the effects of electrical parameters: pulse-on-time and current on three performance measures (material removal rate, microstructures and electrode wear rate), using distilled water and kerosene as dielectrics was performed.
Abstract: Electrical discharge machining is a non-traditional machining method broadly employed in industries for machining of parts that have typical profiles and require great accuracy. This paper investigates the effects of electrical parameters: pulse-on-time and current on three performance measures (material removal rate, microstructures and electrode wear rate), using distilled water and kerosene as dielectrics. A comparison between dielectrics for the machining of aluminum 6061 T6 alloy material in terms of performance measures was performed. Aluminum 6061 T6 alloy material was selected, because of its growing use in the automotive and aerospace industrial sectors. The experimental sequence was designed using Taguchi technique of L9 orthogonal array by changing three levels of pulse-on-time and current, and test runs were performed separately for each dielectric. The results obtained show that greater electrode wear rate (EWR) and higher material removal rate (MRR) were achieved with distilled water when compared with kerosene. These greater EWR and MRR responses can be attributed to the early breakage of the weak oxide and carbide layers formed on the tool and alloy material surfaces, respectively. The innovative contributions of this study include, but are not limited to, the possibility of machining of aluminum 6061 T6 alloy with graphite electrode to enhance machinability and fast cutting rate employing two different dielectrics.

19 citations

Journal ArticleDOI
TL;DR: In this article, the optimization of surface roughness and recast layer thickness of a WEDM process of AISI D2 steel was investigated by using Taguchi method, grey relational analysis and fuzzy logic.
Abstract: In this paper, the optimization of surface roughness and recast layer thickness of a WEDM process of AISI D2 steel was investigated by using Taguchi method, grey relational analysis and fuzzy logic. The experiments were conducted under varying flushing pressure, on time, open voltage, off time and servo voltage. An orthogonal array, signal-to-noise (S/N) ratio, grey relational analysis, grey-fuzzy reasoning grade and analysis of variance were employed to the study of the multiple performance characteristics. Experimental results have shown that machining performance characteristics in WEDM process of AISI D2 steel can be improved effectively through the combination of Taguchi method, grey relational analysis and fuzzy logic.

12 citations