BibTeX:

@article{IJIRSTV2I2018,
     title={Surface Roughness Prediction of AL2014T4 by Responsive Surface Methodology},
     author={B.Suresh babu and P.Suresh Babu},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={2},
     number={2},
     pages={40--46},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV2I2018.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Now a day’s research is prominent to improve surface roughness on mechanical elements has become quite significant in the operational point of view. To enhance accuracy and precision in manufacturing firms are adopting automated systems in order to achieve manufacturing excellence. In this paper the optimizing conditions for best surface roughness on Aluminum alloy 2014T4 and its effect on various parameters spindle speed, tool feed and depth of cut on the surface roughness in precision turning process will be investigated by using response surface methodology(RSM). Three factor-three levels are used, as per the Box-Behnken design matrix. The coefficients are calculated by using Regression analysis and further the model is constructed. Adequacy of developed model is checked by using ANOVA. Interaction effect of various process parameters on surface roughness are studied by using mathematical modeling. This paper is useful for automobile manufacturers, air craft, marine, industries for machining the Aluminum alloys to get optimized surface roughness.

Surface Roughness (Ra), Response Surface Methodology (RSM), CNC Turning, Box-Behnken Design Matrix, ANOVA