Citations in impact factor journals
Predicting surface roughness of hardened AISI 1040 based on cutting parameters using neural networks and multiple regression The International Journal of Advanced Manufacturing Technology |
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Al-Hazza, M.H.F., E.Y.T. Adesta, A.M. Ali, D. Agusman and M.Y. Suprianto, 2011. Energy cost modeling for high speed hard turning. J. Applied Sci., 11: 2578-2584. CrossRefDirect Link |
Ali, A.M., E.Y.T. Adesta, D. Agusman, S.N.M. Badari and M.H.F. Al-Hazza, 2011. Development of surface roughness prediction model for high speed end milling of hardened tool steel. Asian J. Scientific Res., 4: 255-263. CrossRefDirect Link |
Tian, Y., Y. Sun, Y. Su, Z. Wang and C. Tang, 2012. Neural network-based constant current control of dynamic wireless power supply system for electric vehicles. Inform. Technol. J., 11: 876-883. CrossRefDirect Link |
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Investigation of the Effects of Smart Ultrasound Wave on Surface Roughness during Turning Operation of Mild Steel Manufacturing Technology Vol. 16, Issue 4, 757, 2016 |
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Multiple Response Optimization of machining parameters on turning of AA 6063 T6 aluminum alloy which established on Taguchi L9 orthogonal array coupled with Grey relational analysis International Journal of Scientific Research in Science and Technology |
Effects of Trace Elements on the Microstructural and Machinability Characteristics of Al–Si–Cu–Mg Castings Materials Vol. 15, Issue 1, 377, 2022 |
Development of Surface Roughness Prediction Model for High Speed End Milling of Hardened Tool Steel Asian Journal of Scientific Research Vol. 4, Issue 3, 255, 2011 |
Energy Cost Modeling for High Speed Hard Turning Journal of Applied Sciences Vol. 11, Issue 14, 2578, 2011 |
Simultaneous Optimization of Correlated Multiple Surface Quality
Characteristics of Mild Steel Turned Product Intelligent Information Management Vol. 02, Issue 01, 26, 2010 |
How to cite this article
B. Sidda Reddy, G. Padmanabhan and K. Vijay Kumar Reddy, 2008. Surface Roughness Prediction Techniques for CNC Turning. Asian Journal of Scientific Research, 1: 256-264.
DOI: 10.3923/ajsr.2008.256.264
URL: https://scialert.net/abstract/?doi=ajsr.2008.256.264
DOI: 10.3923/ajsr.2008.256.264
URL: https://scialert.net/abstract/?doi=ajsr.2008.256.264