International Journal of Scientific Engineering and Technology

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Development of Fuzzy Logic Technique for Modeling Surface Roughness in Drilling of EN24 Steel with Coated Tools


Affiliations
1 Department of Mechanical Engineering, S. V. University, Tirupati, A. P., India
 

The present paper focused on the application of fuzzy logic for predicting the surface Roughness (Ra) in drilling of EN24 Steel using uncoated and coated tools. For conducting drilling experiments Taguchi L16 orthogonal array was used. The Taguchi method and Analysis of Variance (ANOVA) is employed to find out the influences of machining parameters on surface roughness for their optimization. The machining parameters used in the experiment were drilling speed, feed, tool type and coolant. The obtained experimental results were analyzed and the results revealed that coolant was the prevailing factor on the surface roughness followed by tool type, feed and speed. In addition, the fuzzy predicted values and experimental values of surface roughness are fairly close to each other. Therefore, the developed fuzzy logic model can be effectively used to predict the surface roughness in drilling of EN24 Steel.

Keywords

Drilling, Surface Roughness, Taguchi, ANOVA, Fuzzy Logic Modeling Technique, EN24 Steel.
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  • Development of Fuzzy Logic Technique for Modeling Surface Roughness in Drilling of EN24 Steel with Coated Tools

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Authors

G. Vijaya Kumar
Department of Mechanical Engineering, S. V. University, Tirupati, A. P., India
K. Anand Babu
Department of Mechanical Engineering, S. V. University, Tirupati, A. P., India
P. Venkataramaiah
Department of Mechanical Engineering, S. V. University, Tirupati, A. P., India

Abstract


The present paper focused on the application of fuzzy logic for predicting the surface Roughness (Ra) in drilling of EN24 Steel using uncoated and coated tools. For conducting drilling experiments Taguchi L16 orthogonal array was used. The Taguchi method and Analysis of Variance (ANOVA) is employed to find out the influences of machining parameters on surface roughness for their optimization. The machining parameters used in the experiment were drilling speed, feed, tool type and coolant. The obtained experimental results were analyzed and the results revealed that coolant was the prevailing factor on the surface roughness followed by tool type, feed and speed. In addition, the fuzzy predicted values and experimental values of surface roughness are fairly close to each other. Therefore, the developed fuzzy logic model can be effectively used to predict the surface roughness in drilling of EN24 Steel.

Keywords


Drilling, Surface Roughness, Taguchi, ANOVA, Fuzzy Logic Modeling Technique, EN24 Steel.