| Prediction of tool wear using regression and ANN models in end-milling operation P Palanisamy, I Rajendran, S Shanmugasundaram The International Journal of Advanced Manufacturing Technology 37, 29-41, 2008 | 214 | 2008 |
| Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations P Palanisamy, I Rajendran, S Shanmugasundaram The International Journal of Advanced Manufacturing Technology 32, 644-655, 2007 | 192 | 2007 |
| Prediction of cutting force and temperature rise in the end-milling operation P Palanisamy, I Rajendran, S Shanmugasundaram, R Saravanan Proceedings of the Institution of Mechanical Engineers, Part B: Journal of …, 2006 | 55 | 2006 |
| Prediction of surface roughness for AISI 304 steel with solid carbide tools in end milling process using regression and ANN models S Kalidass, P Palanisamy Arabian Journal for Science and Engineering 39, 8065-8075, 2014 | 28 | 2014 |
| Modelling of tool wear and surface roughness in hard turning using regression and artificial neural network P Palanisamy, S Shanmugasundaram International Journal of Machining and Machinability of Materials 4 (1), 76-94, 2008 | 19 | 2008 |
| Prediction of tool wear using regression and artificial neural network models in end milling of AISI 304 austenitic stainless steel S Kalidass, P Palanisamy, V Muthukumaran International Journal of Engineering and Innovative Technology 1 (2), 29-35, 2012 | 18 | 2012 |
| Experimental investigation on the effect of tool geometry and cutting conditions using tool wear prediction model for end milling process S Kalidass, P Palanisamy Journal of Advanced Manufacturing Systems 13 (01), 41-54, 2014 | 15 | 2014 |
| Prediction and optimisation of tool wear for end milling operation using artificial neural networks and simulated annealing algorithm S Kalidass, P Palanisamy, V Muthukumaran International Journal of Machining and Machinability of Materials 14 (2 …, 2013 | 12 | 2013 |
| I. Rajendran. S. Shanmugasundaram,“Optimization of machining parameters using genetic algorithm and experimental validation for end-milling operations,” P Palanisamy International Journal of Advanced Manufacturing Technology, 2007 | 9 | 2007 |
| Investigations on end-milling process by artificial neural network, finite element analysis and experimental studies P Palanisamy, I Rajendran, S Shanmugasundaram International Journal of Machining and Machinability of Materials 1 (2), 233-257, 2006 | 5 | 2006 |
| Effect of machining parameters on surface roughness in end milling of AISI 304 steel using uncoated solid carbide tools S Kalidass, P Palanisamy Australian Journal of Mechanical Engineering 12 (2), 223-232, 2014 | 4 | 2014 |
| Fuzzy logic model to predict hot corrosion in molten salt of steel-SA213T92 coated by plasma sprayed YSZ M Makesh, P Palanisamy, K Devakumaran Int. J. Mech. Mechatron. Eng. 14, 44-50, 2014 | 3 | 2014 |
| An analytical method of prediction of stability and experimental validation using FFT analyzer in end milling process P Palanisamy, M Subramanian, NP Manojkumar Int J Appl Eng Res 13 (7), 5260-5264, 2018 | 2 | 2018 |
| Prediction and optimization of surface roughness for end milling operation using artificial neural networks and genetic algorithm S Kalidass, P Palanisamy, V Muthukumaran Journal of Manufacturing Engineering 8 (1), 028-037, 2013 | 2 | 2013 |
| High-Temperature Oxidation And Hot Corrosion Behaviour Of Plasma Sprayed YSZ Coating On Sa213 T92 Steel In Air And Salt At 900 C Under Cyclic Condition M Makesh, P Palanisamy, K Devakumaran ARPN Journal of Engineering and Applied Sciences 10 (1), 235-241, 2015 | 1 | 2015 |
| Use of Artificial Neural Network for Prediction of Tool Wear in End Milling Process P Palanisamy, I Rajendran, S Shanmugasundaram Manufacturing Technology Today, 9-12, 2006 | | 2006 |
| Studies on cutting force stability and tool wear in end milling process P Palanisamy Coimbatore, 0 | | |
