Experimental Investigation of Surface Roughness and Temperature on Surface Grinding of HC-Hcr Steel Using Dry and MQL Techniques
Keywords:
MQL, Al2O3 nanoparticles, RSM, multiresponse optimization, surface grinding
Abstract
In machining of metals, application of cutting fluids improves machinability and tool life due to their cooling and lubrication characteristics. The traditional methods of cutting fluid applications may create problems for the operator and not Eco-friendly. Minimum quantity lubrication (MQL) Technique can minimize these problems to a considerable extent. The use of nano-material and nanotechnology can improve the performance of cutting fluids. In the present work, an attempt has been made with MQL to investigate the performance of vegetable oil along with different volume proportions of Al2O3 nanoparticles on surface grinding of HCHCr workpiece. The influence of oil is evaluated regarding surface finish and Temperature of the workpiece. According to central composite design, sixteen experiments are conducted in dry and MQL with nanoparticles. Experimental results of surface roughness and temperature are evaluated using response surface methodology (RSM) and analysis of variance to identify significant parameters. A multi-response optimization technique is used to optimize processes parameters for minimum surface roughness and temperature. The optimal values of % of Nanoparticles, cutting speed, table feed and depth of cut are found to be 0.3636%, 9.166 m/s, 7.12m/min and 10?m respectively.
Downloads
- Article PDF
- TEI XML Kaleidoscope (download in zip)* (Beta by AI)
- Lens* NISO JATS XML (Beta by AI)
- HTML Kaleidoscope* (Beta by AI)
- DBK XML Kaleidoscope (download in zip)* (Beta by AI)
- LaTeX pdf Kaleidoscope* (Beta by AI)
- EPUB Kaleidoscope* (Beta by AI)
- MD Kaleidoscope* (Beta by AI)
- FO Kaleidoscope* (Beta by AI)
- BIB Kaleidoscope* (Beta by AI)
- LaTeX Kaleidoscope* (Beta by AI)
How to Cite
Published
2017-05-15
Issue
Section
License
Copyright (c) 2017 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.