2004
DOI: 10.1007/s00170-003-2045-8
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Modeling and analysis of white layer depth in a wire-cut EDM process through response surface methodology

Abstract: A white layer is considered a major flaw on a workpiece surface machined with wire-cut electrical discharge machining (WEDM). In this paper, an attempt has been made to model the white layer depth through response surface methodology (RSM) in a WEDM process comprising a rough cut followed by a trim cut. An experimental plan for rotatable central composite design of second order involving four variables with five levels has been employed to carry out the experimental investigation and subsequently to establish … Show more

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Cited by 120 publications
(51 citation statements)
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“…Single and multiple statistical regression models are found for texture parameters [31].Heat transfer model was analyzed for EDM parameters such as pulse duration,pulse energy,MRR and crater shape [32].Thermal model was illustrated by data dependent system [33].Online wire rupture monitoring system was carried out by sparking frequency monitor [34].variable mass cylindrical plasma models was introduced [35].EDM process modeling was done by artificial neural network [36].ANN provides more accurate results of the parameters such as pulse on time, pulse off time and discharge current [37]. Tangent sigmoid multi-layered perceptron(TANMLP),radial basis function network(RBFN) are used to predict the surface finish [38].More accurate result was found by this model during machining process to predict MRR [39].Surface methodology was observed for pulse on time and pulse of time which shows the optimum speed cutting of 3mm/min [40]. Fig 4. Shows the various simulating model for input and output parameters for EDM research.…”
Section: VImentioning
confidence: 99%
“…Single and multiple statistical regression models are found for texture parameters [31].Heat transfer model was analyzed for EDM parameters such as pulse duration,pulse energy,MRR and crater shape [32].Thermal model was illustrated by data dependent system [33].Online wire rupture monitoring system was carried out by sparking frequency monitor [34].variable mass cylindrical plasma models was introduced [35].EDM process modeling was done by artificial neural network [36].ANN provides more accurate results of the parameters such as pulse on time, pulse off time and discharge current [37]. Tangent sigmoid multi-layered perceptron(TANMLP),radial basis function network(RBFN) are used to predict the surface finish [38].More accurate result was found by this model during machining process to predict MRR [39].Surface methodology was observed for pulse on time and pulse of time which shows the optimum speed cutting of 3mm/min [40]. Fig 4. Shows the various simulating model for input and output parameters for EDM research.…”
Section: VImentioning
confidence: 99%
“…In order to examine the extent of surface damage (Recast layer) on machined surface, specimen were polished to have mirror finish on the transverse section and observation through scanning electron microscope (SEM) was made. Recast layer (RCL) is a hard skin on the work surface formed due to the re-solidification of melted residual material which was not completely expelled during the process (Puri & Bhattacharyya, 2005). The morphology of recast layer is much different from bulk material and it adversely affects the working life of machined component (Liao et al, 2004;Soo et al, 2013) Fig.…”
Section: Analysis Of Surface Roughness (Sr)mentioning
confidence: 99%
“…It consists of recast layer or white layer having hollow cavities and several micro-cracks due to thermal residual stresses (Lee & Li, 2003;Wang et al, 2009). Recast layer is a hard skin on the work surface formed due to the re-solidification of melted residual material which was not completely expelled during the process (Puri & Bhattacharyya, 2005).…”
Section: Introductionmentioning
confidence: 99%