Indian Journal of Science and Technology
Year: 2013, Volume: 6, Issue: 9, Pages: 1-6
A. Poursafar1 *, A. Amrollahi2 and H. Barghikar3
1, 3Department of Mechanical Engineering, [email protected]
2 Department of Mechanical Engineering, [email protected]
*Author For Correspondence
Department of Mechanical Engineering,
The machining model in the turning of 34CrMo4 steel was developed in terms of cutting speed, feed rate and depth of cut and tool nose radius using response surface methodology. Machining tests were carried out using several tools with several tool radiuses (0.4, 0.8 and 1.2 mm) under different cutting conditions such as feed rate (0.08, 0.12, 0.14, 0.16, and 0.20 mm/ rev), cutting speed (250, 355, and 500 RPM) and depth of cut (0.5, 1.0, and 1.5 mm). The roughness equations of cutting tools when machining the steels were achieved by using the experimental data. The results are presented in terms of mean values and confidence levels; as a result minimum surface roughness achieved by the machining model was 2.5 micrometer. The established equation and graphs show that the feed rate (0.18 mm/rev) and cutting speed (90 m/min) were found to be main influencing factor on the surface roughness. It increased with increasing the feed rate and depth of cut (1.5 mm), but decreased with increasing the cutting speed, respectively. The variance analysis for the second-order model shows that the interaction terms and the square terms were statistically insignificant as a result linear function was used for local model. The rsme (root square mean error) for local model in interaction terms and square terms was 0.22. Finally, experimentation was carried out to identify the effectiveness of the proposed method. However, it could be seen that the first-order effect of feed rate was significant while cutting speed and depth of cut was insignificant. The predicted and optimized surface roughness model of the samples was found to lie close to that of the experimentally observed ones with 95% confident intervals.
Keywords: Response Surface Methodology, 34CrMo4 Steel, Optimized Surface Roughness, Turning.
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