Predictive modeling of surface roughness and material removal rate in turning of UD-GFRP composites using carbide (K10) tool

Subject Areas : Mechanical Engineering

Received: 2012-05-08 Accepted : 2017-10-31 Published : 2013-06-01

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Abstract :

This work presents an experimental investigation of the influence of the six important machining parameters (tool nose radius, tool rake angle, feed rate, cutting speed, cutting environment (dry, wet and cooled) and depth of cut) on surface roughness & material removal rate in the machining unidirectional glass fiber reinforced plastics (UD-GFRP) composite using carbide (K10) cutting tool during turning operation. Orthogonal L18 array in Taguchi method was employed to carry out the experimental work. ANOVA is performed for significant parameter and later Regression model is developed for the significant parameters. Validation (confirmatory) results indicate that the model is suitable for surface roughness & material removal rate during the study

References:

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Genetic Algorithm and ANN for Estimation of SPIV of Micro Beams
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Estimation of Surface Roughness in Turning by Considering the Cutting Tool Vibration, Cutting Force and Tool Wear
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An Experimental Investigation on Comparison of the Similar and Dissimilar Resistance Spot Welding of St12 and Galvanized Steel using Design of Experiments
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Experimental Study on Magnetic Abrasive Honing of Inner Surface of Tube AISI304
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Corrosion Behavior Characterization of the Nugget Zone in Copper/Brass Metals of Dissimilar Friction Stir Welded Lap Joints
Print Date : 2018-03-01

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Predictive modeling of surface roughness and material removal rate in turning of UD-GFRP composites using carbide (K10) tool