Multi-objective optimization on the machining parameters for bio-inspired nanocoolant
The emphasis of this paper is to evaluate the thermophysical properties of crystalline nanocellulose (CNC)-based nanofluid and the optimized machining parameters (cutting speed, feed rate and depth of cut) for machining using CNC-based nanofluid. Cutting tool temperature and formed chip temperature...
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Online Access: | http://umpir.ump.edu.my/id/eprint/22471/7/Multi-objective%20optimization%20on%20the%20machining1.pdf http://umpir.ump.edu.my/id/eprint/22471/ https://doi.org/10.1007/s10973-018-7693-x https://doi.org/10.1007/s10973-018-7693-x |
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my.ump.umpir.224712019-02-25T01:58:25Z http://umpir.ump.edu.my/id/eprint/22471/ Multi-objective optimization on the machining parameters for bio-inspired nanocoolant Keeran, Anamalai Lingenthiran, Samylingam K., Kadirgama Samykano, Mahendran G., Najafi D., Ramasamy M. M., Rahman TS Manufactures The emphasis of this paper is to evaluate the thermophysical properties of crystalline nanocellulose (CNC)-based nanofluid and the optimized machining parameters (cutting speed, feed rate and depth of cut) for machining using CNC-based nanofluid. Cutting tool temperature and formed chip temperature during machining are determined with CNC-based coolant and metal working fluid. Minimum quantity lubrication technique is used to minimize the usage of the coolant. Nanocellulose coolant with a concentration of 0.5% shows better thermal conductivity and viscosity. Total heat produced at the cutting tool and the temperature generated at the chip during machining shows significant improvement using CNCbased nanofluid. Statistical analysis reveals that feed rate and depth of cut contribute around 27.48% and 22.66% toward cutting temperature. Meanwhile, none of the parameters significantly affects the heat transfer. The multi-objective optimization reveals that the optimum parameter for machining using CNC-based nanocoolant is: cutting speed = 120, feed rate = 0.05 and depth of cut = 1.78 which produces heat transfer of 379.44 J and cutting temperature of 104.41 C. Springer 2019 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/22471/7/Multi-objective%20optimization%20on%20the%20machining1.pdf Keeran, Anamalai and Lingenthiran, Samylingam and K., Kadirgama and Samykano, Mahendran and G., Najafi and D., Ramasamy and M. M., Rahman (2019) Multi-objective optimization on the machining parameters for bio-inspired nanocoolant. Journal of Thermal Analysis and Calorimetry, 135 (2). pp. 1533-1544. ISSN 1388-6150 (print); 1588-2926 (online) https://doi.org/10.1007/s10973-018-7693-x https://doi.org/10.1007/s10973-018-7693-x |
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The emphasis of this paper is to evaluate the thermophysical properties of crystalline nanocellulose (CNC)-based nanofluid and the optimized machining parameters (cutting speed, feed rate and depth of cut) for machining using CNC-based nanofluid. Cutting tool temperature and formed chip temperature during machining are determined with CNC-based coolant and metal working fluid. Minimum quantity lubrication technique is used to minimize the usage of the coolant. Nanocellulose coolant with a concentration of 0.5% shows better thermal conductivity and viscosity. Total heat produced at the cutting tool and the temperature generated at the chip during machining shows significant improvement using CNCbased nanofluid. Statistical analysis reveals that feed rate and depth of cut contribute around 27.48% and 22.66% toward cutting temperature. Meanwhile, none of the parameters significantly affects the heat transfer. The multi-objective optimization reveals that the optimum parameter for machining using CNC-based nanocoolant is: cutting speed = 120, feed rate = 0.05 and depth of cut = 1.78 which produces heat transfer of 379.44 J and cutting temperature of 104.41 C. |
format |
Article |
author |
Keeran, Anamalai Lingenthiran, Samylingam K., Kadirgama Samykano, Mahendran G., Najafi D., Ramasamy M. M., Rahman |
author_facet |
Keeran, Anamalai Lingenthiran, Samylingam K., Kadirgama Samykano, Mahendran G., Najafi D., Ramasamy M. M., Rahman |
author_sort |
Keeran, Anamalai |
title |
Multi-objective optimization on the machining parameters for bio-inspired nanocoolant |
title_short |
Multi-objective optimization on the machining parameters for bio-inspired nanocoolant |
title_full |
Multi-objective optimization on the machining parameters for bio-inspired nanocoolant |
title_fullStr |
Multi-objective optimization on the machining parameters for bio-inspired nanocoolant |
title_full_unstemmed |
Multi-objective optimization on the machining parameters for bio-inspired nanocoolant |
title_sort |
multi-objective optimization on the machining parameters for bio-inspired nanocoolant |
publisher |
Springer |
publishDate |
2019 |
url |
http://umpir.ump.edu.my/id/eprint/22471/7/Multi-objective%20optimization%20on%20the%20machining1.pdf http://umpir.ump.edu.my/id/eprint/22471/ https://doi.org/10.1007/s10973-018-7693-x https://doi.org/10.1007/s10973-018-7693-x |
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1643669389145276416 |
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13.18916 |