| Surface roughness prediction using artificial neural network in hard turning of AISI H13 steel with minimal cutting fluid application BA Beatrice, E Kirubakaran, PRJ Thangaiah, KLD Wins Procedia Engineering 97, 205-211, 2014 | 92 | 2014 |
| Innovative potential of additive friction stir deposition among current laser based metal additive manufacturing processes: A review V Gopan, KLD Wins, A Surendran CIRP Journal of Manufacturing Science and Technology 32, 228-248, 2021 | 75 | 2021 |
| Effect of tungsten carbide, silicon carbide and graphite particulates on the mechanical and microstructural characteristics of AA 5052 hybrid composites DSEJ Dhas, C Velmurugan, KLD Wins, KP BoopathiRaja Ceramics International 45 (1), 614-621, 2019 | 53 | 2019 |
| Optimization of cutting parameters and fluid application parameters during turning of OHNS steel RDJ Johnson, KLD Wins, A Raj, BA Beatrice Procedia Engineering 97, 172-177, 2014 | 41 | 2014 |
| Effect of nano cupric oxide coating on the forced convection performance of a mixed-mode flat plate solar dryer S Sivakumar, C Velmurugan, DSEJ Dhas, AB Solomon, KLD Wins Renewable energy 155, 1165-1172, 2020 | 39 | 2020 |
| Integrated ANN-GA approach for predictive modeling and optimization of grinding parameters with surface roughness as the response V Gopan, KLD Wins, A Surendran Materials today: proceedings 5 (5), 12133-12141, 2018 | 31 | 2018 |
| Investigations on the effect of tungsten carbide and graphite reinforcements during spark erosion machining of aluminium alloy (AA 5052) hybrid composite DSEJ Dhas, C Velmurugan, KLD Wins Silicon 10 (6), 2769-2781, 2018 | 23 | 2018 |
| Quantitative analysis of grinding wheel loading using image processing V Gopan, KLD Wins Procedia Technology 25, 885-891, 2016 | 22 | 2016 |
| Artificial neural network assisted sensor fusion model for predicting surface roughness during hard turning of H13 steel with minimal cutting fluid application JGA Arulraj, KLD Wins, A Raj Procedia Materials Science 5, 2338-2346, 2014 | 21 | 2014 |
| Optimization of surface milling of hardened AISI4340 steel with minimal fluid application using a high velocity narrow pulsing jet of cutting fluid W K Leo Dev, V AS Engineering 2010, 2010 | 21 | 2010 |
| Effect of carbide ceramics and coke on the properties of dispersion strengthened aluminium‐silicon7‐magnesium hybrid composites D Dhas, R Raja, S Jannet, KLD Wins, JM Thomas, SR Kandavalli Materialwissenschaft und Werkstofftechnik 54 (2), 147-157, 2023 | 15 | 2023 |
| Mathematical modelling of machining performance during dry face milling of AA5052/tungsten carbide/graphite hybrid composite DS Dhas, C Velmurugan, K Wins, S Senthilkumaran, SR Kandavalli AIP Conference Proceedings 2446 (1), 2022 | 15 | 2022 |
| Optimization of cutting parameters of hybrid metal matrix composite AA6061/ZrB2 and ZrC during dry turning SR Ruban, JDR Selvam, KLD Wins, SR Kandavalli IOP conference series: materials science and engineering 993 (1), 012135, 2020 | 15 | 2020 |
| Experimental investigation for the multi-objective optimization of machining parameters on AISI D2 steel using particle swarm optimization coupled with artificial neural network V Gopan, KLD Wins, G Evangeline, A Surendran Journal of Advanced Manufacturing Systems 19 (03), 589-606, 2020 | 14 | 2020 |
| An environment friendly twin-jet minimal fluid application scheme for surface milling of hardened AISI4340 steel KLD Wins, AS Varadarajan International Journal of Manufacturing Systems 1 (1), 30-45, 2011 | 13 | 2011 |
| Evaluation of the performance during hard turning of OHNS steel with minimal cutting fluid application and its comparison with minimum quantity lubrication A Raj, KLD Wins, AS Varadarajan IOP Conference Series: Materials Science and Engineering 149 (1), 012021, 2016 | 11 | 2016 |
| Simulation of surface milling of hardened AISI4340 steel with minimal fluid application using artificial neural network LDK Wins, AS Varadarajan Advances in Production Engineering & Management 7 (1), 51, 2012 | 9 | 2012 |
| Simulation of surface milling of hardened AISI4340 steel with minimal fluid application using artificial neural network LDK Wins, AS Varadarajan Advances in Production Engineering & Management 7 (1), 51, 2012 | 9 | 2012 |
| Machinability, weldability and surface treatment studies of SDSS 2507 material-A review P George, KLD Wins, DSEJ Dhas, P George Materials Today: Proceedings 46, 7682-7687, 2021 | 8 | 2021 |
| ANFIS based model for surface roughness prediction for hard turning with minimal cutting fluid application RA Raj, MD Anand, KLD Wins, AS Varadarajan Indian Journal of science and technology, 2016 | 8 | 2016 |
Dr. D. S. Ebenezer Jacob DhasAssistant ProfessorVerified email at karunya.edu
