How to cite this paper
Kesarwani, S., Verma, R & Dave, H. (2022). An integrated approach of VIKOR and teaching learning based optimization algorithm for milling machinability computations.Management Science Letters , 12(4), 263-282.
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Abhishek, K., Rakesh Kumar, V., Datta, S., & Mahapatra, S. S. (2017). Parametric appraisal and optimization in machining of CFRP composites by using TLBO (teaching–learning based optimization algorithm). Journal of Intelligent Manufacturing, 28(8), 1769–1785. https://doi.org/10.1007/s10845-015-1050-8
Agrawal, S., Singh, K. K., & Sarkar, P. (2014). Impact damage on fibre-reinforced polymer matrix composite – A review. Journal of Composite Materials, 48(3), 317–332. https://doi.org/10.1177/0021998312472217
Ajith Arul Daniel, S., Pugazhenthi, R., Kumar, R., & Vijayananth, S. (2019). Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi -grey relational analysis. Defence Technology, 15(4), 545–556. https://doi.org/10.1016/j.dt.2019.01.001
Akinlabi, E. T., Mathoho, I., Mubiayi, M. P., Mbohwa, C., & Makhatha, M. E. (2018). Effect of process parameters on surface roughness during dry and flood milling of Ti-6A-l4V. 2018 IEEE 9th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT), 2018-Janua, 144–147. https://doi.org/10.1109/ICMIMT.2018.8340438
Ali, I., Basheer, A. A., Kucherova, A., Memetov, N., Pasko, T., Ovchinnikov, K., Pershin, V., Kuznetsov, D., Galunin, E., Grachev, V., & Tkachev, A. (2019). Advances in carbon nanomaterials as lubricants modifiers. Journal of Molecular Liquids, 279, 251–266. https://doi.org/10.1016/j.molliq.2019.01.113
Andrew, J. J., Srinivasan, S. M., Arockiarajan, A., & Dhakal, H. N. (2019). Parameters influencing the impact response of fiber-reinforced polymer matrix composite materials: A critical review. Composite Structures, 224, 111007. https://doi.org/10.1016/J.COMPSTRUCT.2019.111007
Babu, N. S. M., Mathivanan, N. R., & Kumar, K. V. (2019). Influence of machining parameters on the response variable during drilling of the hybrid laminate. Australian Journal of Mechanical Engineering. https://doi.org/10.1080/14484846.2019.1704492
Bagci, E., & Yüncüoğlu, E. U. (2017). The effects of milling strategies on forces, material removal rate, tool deflection, and surface errors for the rough machining of complex surfaces. Strojniski Vestnik/Journal of Mechanical Engineering, 63(11), 643–656. https://doi.org/10.5545/sv-jme.2017.4450
Bucholz, E. W., Phillpot, S. R., & Sinnott, S. B. (2012). Molecular dynamics investigation of the lubrication mechanism of carbon nano-onions. Computational Materials Science, 54(1), 91–96. https://doi.org/10.1016/j.commatsci.2011.09.036
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Cha, J., Kim, J., Ryu, S., & Hong, S. H. (2019). Comparison to mechanical properties of epoxy nanocomposites reinforced by functionalized carbon nanotubes and graphene nanoplatelets. Composites Part B: Engineering, 162, 283–288. https://doi.org/10.1016/j.compositesb.2018.11.011
Chandrasekhar, S., & Prasad, N. (2020). Multi-response optimization of electrochemical machining parameters in the micro-drilling of AA6061-TiB2in situ composites using the Entropy–VIKOR method: Https://Doi.Org/10.1177/0954405420911539, 234(10), 1311–1322. https://doi.org/10.1177/0954405420911539
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Chau, N. Le, Nguyen, M.-Q., Dao, T.-P., Huang, S.-C., Hsiao, T.-C., Dinh-Cong, D., & Dang, V. A. (2018). An effective approach of adaptive neuro-fuzzy inference system-integrated teaching learning-based optimization for use in machining optimization of S45C CNC turning. Optimization and Engineering 2018 20:3, 20(3), 811–832. https://doi.org/10.1007/S11081-018-09418-X
Chen, J., Tuo, W., Wei, P., Okabe, Y., Xu, M., & Xu, M. (2017). Characteristics of the shear mechanical properties and the influence mechanism of short basalt fiber reinforced polymer composite materials: Https://Doi.Org/10.1177/1099636217716466, 21(4), 1520–1534. https://doi.org/10.1177/1099636217716466
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Dhand, V., Yadav, M., Kim, S. H., & Rhee, K. Y. (2021). A comprehensive review on the prospects of multi-functional carbon nano onions as an effective, high- performance energy storage material. Carbon, 175, 534–575. https://doi.org/10.1016/j.carbon.2020.12.083
Ebrahimnejad, S., Mousavi, S. M., Tavakkoli-Moghaddam, R., & Heydar, M. (2012). Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment. International Journal of Industrial Engineering Computations, 3(3), 463–476. https://doi.org/10.5267/J.IJIEC.2011.12.001
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Agrawal, S., Singh, K. K., & Sarkar, P. (2014). Impact damage on fibre-reinforced polymer matrix composite – A review. Journal of Composite Materials, 48(3), 317–332. https://doi.org/10.1177/0021998312472217
Ajith Arul Daniel, S., Pugazhenthi, R., Kumar, R., & Vijayananth, S. (2019). Multi objective prediction and optimization of control parameters in the milling of aluminium hybrid metal matrix composites using ANN and Taguchi -grey relational analysis. Defence Technology, 15(4), 545–556. https://doi.org/10.1016/j.dt.2019.01.001
Akinlabi, E. T., Mathoho, I., Mubiayi, M. P., Mbohwa, C., & Makhatha, M. E. (2018). Effect of process parameters on surface roughness during dry and flood milling of Ti-6A-l4V. 2018 IEEE 9th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT), 2018-Janua, 144–147. https://doi.org/10.1109/ICMIMT.2018.8340438
Ali, I., Basheer, A. A., Kucherova, A., Memetov, N., Pasko, T., Ovchinnikov, K., Pershin, V., Kuznetsov, D., Galunin, E., Grachev, V., & Tkachev, A. (2019). Advances in carbon nanomaterials as lubricants modifiers. Journal of Molecular Liquids, 279, 251–266. https://doi.org/10.1016/j.molliq.2019.01.113
Andrew, J. J., Srinivasan, S. M., Arockiarajan, A., & Dhakal, H. N. (2019). Parameters influencing the impact response of fiber-reinforced polymer matrix composite materials: A critical review. Composite Structures, 224, 111007. https://doi.org/10.1016/J.COMPSTRUCT.2019.111007
Babu, N. S. M., Mathivanan, N. R., & Kumar, K. V. (2019). Influence of machining parameters on the response variable during drilling of the hybrid laminate. Australian Journal of Mechanical Engineering. https://doi.org/10.1080/14484846.2019.1704492
Bagci, E., & Yüncüoğlu, E. U. (2017). The effects of milling strategies on forces, material removal rate, tool deflection, and surface errors for the rough machining of complex surfaces. Strojniski Vestnik/Journal of Mechanical Engineering, 63(11), 643–656. https://doi.org/10.5545/sv-jme.2017.4450
Bucholz, E. W., Phillpot, S. R., & Sinnott, S. B. (2012). Molecular dynamics investigation of the lubrication mechanism of carbon nano-onions. Computational Materials Science, 54(1), 91–96. https://doi.org/10.1016/j.commatsci.2011.09.036
Camisasca, A., & Giordani, S. (2017). Carbon nano-onions in biomedical applications: Promising theranostic agents. In Inorganica Chimica Acta (Vol. 468, pp. 67–76). Elsevier S.A. https://doi.org/10.1016/j.ica.2017.06.009
Cha, J., Kim, J., Ryu, S., & Hong, S. H. (2019). Comparison to mechanical properties of epoxy nanocomposites reinforced by functionalized carbon nanotubes and graphene nanoplatelets. Composites Part B: Engineering, 162, 283–288. https://doi.org/10.1016/j.compositesb.2018.11.011
Chandrasekhar, S., & Prasad, N. (2020). Multi-response optimization of electrochemical machining parameters in the micro-drilling of AA6061-TiB2in situ composites using the Entropy–VIKOR method: Https://Doi.Org/10.1177/0954405420911539, 234(10), 1311–1322. https://doi.org/10.1177/0954405420911539
Chate, G. R., Patel, G. C. M., Bhushan, S. N. B., Parappagoudar, M. B., & Deshpande, A. S. (2019). Comprehensive modelling, analysis and optimization of furan resin-based moulding sand system with sawdust as an additive. Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41(4), 0–24. https://doi.org/10.1007/s40430-019-1684-0
Chau, N. Le, Nguyen, M.-Q., Dao, T.-P., Huang, S.-C., Hsiao, T.-C., Dinh-Cong, D., & Dang, V. A. (2018). An effective approach of adaptive neuro-fuzzy inference system-integrated teaching learning-based optimization for use in machining optimization of S45C CNC turning. Optimization and Engineering 2018 20:3, 20(3), 811–832. https://doi.org/10.1007/S11081-018-09418-X
Chen, J., Tuo, W., Wei, P., Okabe, Y., Xu, M., & Xu, M. (2017). Characteristics of the shear mechanical properties and the influence mechanism of short basalt fiber reinforced polymer composite materials: Https://Doi.Org/10.1177/1099636217716466, 21(4), 1520–1534. https://doi.org/10.1177/1099636217716466
Cheng, D. J., Xu, F., Xu, S. H., Zhang, C. Y., Zhang, S. W., & Kim, S. J. (2020). Minimization of Surface Roughness and Machining Deformation in Milling of Al Alloy Thin-Walled Parts. International Journal of Precision Engineering and Manufacturing, 21(9), 1597–1613. https://doi.org/10.1007/s12541-020-00366-0
Davim, J. P., & Reis, P. (2005). Damage and dimensional precision on milling carbon fiber-reinforced plastics using design experiments. Journal of Materials Processing Technology, 160(2), 160–167. https://doi.org/10.1016/j.jmatprotec.2004.06.003
Desai, C. K., & Shaikh, A. (2012). Prediction of depth of cut for single-pass laser micro-milling process using semi-analytical, ANN and GP approaches. International Journal of Advanced Manufacturing Technology, 60(9–12), 865–882. https://doi.org/10.1007/s00170-011-3677-8
Dhand, V., Mittal, G., Rhee, K. Y., Park, S. J., & Hui, D. (2015). A short review on basalt fiber reinforced polymer composites. Composites Part B: Engineering, 73, 166–180. https://doi.org/10.1016/j.compositesb.2014.12.011
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