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Optimization of Surface Roughness for EN 1010 Low Alloy Steel on WEDM Using Response Surface Methodology
( Vol-4,Issue-7,July 2018 )


Munish Giri, Manjeet Bohat, Ravinder Chaudhary, Anish Taneja


ANOVA, CCD, EN 1010, RSM, Surface Roughness, Wire EDM.


The term steel is used for many different alloys of iron. All steels cover small amounts of carbon and manganese. There do exist many types of steels which are(among others) plain carbon steel, stainless steel, alloysteel and tool steel. Carbon steel is the most extensively used kind of steel. The properties of carbon steel depend mainly on the amount of carbon it contains. Maximum carbon steel has a carbon content of less than 1%. Carbon steel is made into an extensive range of products, including structural beams, car bodies. In fact, there are 3 types of plain carbon steel namely low carbon steel, medium carbon steel, high carbon steel. It is good to exact that plain carbon steel is a type of steel having a maximum carbon content of 1.5% along with small percentages of silica, Sulphur, phosphorus and manganese. EN 1010 is a lowest amount of carbonalloy steel alloy with carbon content of 0.10%. Machineability of EN 1010 carbon steel is measured to be fairly good. EN 1010 is usually used for rivets and bolts, construction and automotive applications such as pans, nails and transmission cover. The objective of paper is to study the effect of process parameters namely pulse on time, pulse off time, peak current and servo voltage on surface roughness(SR).The effect of process parameters on productivity and accuracy facts is material dependent. To study parametric effect on Surface Roughness a Central Composite design approach of response surface methodology (RSM) is used to plan and study the experiments. The mathematical relationships between WEDM input process parameters and response parameter namely surface roughness is established to determine optimal values of surface roughness mathematically and graphically.The Analysis of variance (ANOVA) is performed to find statistically significant process parameters. Interaction effects of process parameters on surface roughness are analysed using statistical and graphical representations.

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