edm

1180 Words3 Pages

During EDM process, the discharged energy produces very high temperatures at the point of the spark, causing a minute part of the sample to melt and vaporizes. With each discharge, a crater was formed on the machined surface. It was observed from Figure 5.4 SEM micrographs that, EDM surface produces irregular topography and defects included globules of debris, spherical particle, varying size craters and micro-cracks [29]. The surface topography was altered owing to significant electrical parameters such as Pulse on Time, Pulse off Time and Peak Current. The Pulse on Time and Peak Current are the most significant parameters that lead to deterioration of the surface texture. When Pulse on Time was increased then surface texture of the machined surface is composed of varying sizes of deep craters. These deep and overlapping craters were formed owing to successive electrical discharge, intense heat and local melting or vaporization of work material. Some of the molten material produced by the discharge was carried away by the kerosene. The remaining melt re-solidifies to form lumps of debris. Under shorter pulse on-time, the electrical sparks generate smaller craters on the work surface. Whereas the high pulsed current caused frequent cracking of dielectric fluid, which cause more melt expulsions and larger tensile stresses. These effects resulted in poor surface finish. At higher Peak Current, the impact of discharge energy on the surface of workpiece becomes greater and thus resulting erosion leads to the increase in deterioration of surface roughness.
The recast layer is the outer region of the heat affected zone and consists of superimposed strata derived from melted and resolidified workpiece material as seen in Figure 5. This l...

... middle of paper ...

... if ŷ < Ai di = 0 if ŷ > Bi
If the importance is same for each response, the composite desirability (DG), the geometric mean of all desirability functions, is given by
DG = (d1 x d2 x … x dnwn)1/n = (∏di)1/n where n = number of responses = 3.
It can be extensive to reflect the possible difference in the importance of different responses by giving weights. Where the weight wi satisfies 0 < wi < 1 and w1 + w2 + … + wn = 1
DG = (d1w1 x d2w2 x … x dnwn)1/n
Table 5.6 shows the constraints of input parameters and that of responses and the goal and weights assigned to each parameter. Table 5.8 shows the values of 36 levels of combinations of process parameters that will give a high value of composite desirability (ranged from 0.79 to 0.94). Table 5.7 gives the optimal input process parametric setting for multi-response optimization.

Open Document