Friction

, Volume 5, Issue 2, pp 155–170 | Cite as

Surface roughness measurements in NFMQL assisted turning of titanium alloys: An optimization approach

Open Access
Research Article

Abstract

The prediction and optimization of surface roughness values remain a critical concern in nano-fluids based minimum quantity lubrication (NFMQL) turning of titanium (grade-2) alloys. Here, we discuss an application of response surface methodology with Box–Cox transformation to determine the optimal cutting parameters for three surface roughness values, i.e., Ra, Rq, and Rz, in turning of titanium alloy under the NFMQL condition. The surface roughness prediction model has been established based on the selected input parameters such as cutting speed, feed rate, approach angle, and different nano-fluids used. Then the multiple regression technique is used to find the relationship between the given responses and input parameter. Further, the experimental data were optimized through the desirability function approach. The findings from the current investigation showed that feed rate is the most effective parameter followed by cutting speed, different nano-fluids, and approach angle on Ra and Rq values, whereas cutting speed is more effective in the case of Rz under NFMQL conditions. Moreover, the predicted results are comparatively near to the experimental values and hence, the established models of RSM using Box-Cox transformation can be used for prediction satisfactorily.

Keywords

nano-fluids optimization surface roughness turning titanium alloy 

Notes

Acknowledgments

The authors are extremely grateful to Dr. Vishal S. Sharma, NIT Jalandhar for providing the research facilities. Authors also acknowledge the MHRD, Govt. of India and Central Workshop NIT Hamirpur (H.P.) for the financial support.

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© The Author(s) 2016

Open Access: The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http:// creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.NITHamirpur (H.P.)India

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