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| dc.contributor.author | Tanvir, Mahamudul Hasan | |
| dc.contributor.author | Hussain, Afzal | |
| dc.contributor.author | Rahman, M.M. Towfiqur | |
| dc.contributor.author | Zishan, Khandoker | |
| dc.contributor.author | Ishraq, Sakib | |
| dc.date.accessioned | 2020-11-01T11:04:35Z | |
| dc.date.available | 2020-11-01T11:04:35Z | |
| dc.date.issued | 2018-11-15 | |
| dc.identifier.citation | Kalpakjian, S., Schmid, S.R., 2001. Manufacturing Engineering and Technology, International, Fourth ed. Prentice Hall Co., New Jersey, pp. 536–681 Yang, W.H., Tarng, Y.S., 1998. Design optimization of cuttingparameters for turning operations based on the Taguchi method. J. Mater. Process Technol. 84, 122–129 Davim, J.P., 2003. Design of optimization of cutting parameters forturning metal matrix composites based on the orthogonal arrays. J. Mater. Process. Technol. 132, 340–344 Manna, A., Bhattacharyya, B., 2004. investigation for optimal parametric combination for achieving better surface finish during turning of Al/SiC-MMC. Int. J. Adv. Manuf. Technol. 23, 658–665 Aslan, E., Camuscu, N., Birgoren, B., 2007. Design optimization of cutting parameters when turning hardened AISI 4140 steel (63 HRC) with Al2O3 +TiCN mixed ceramic tool. Mater. Des. 28, 1618– 1622. Nalbant, M., Gokkaya, H., Sur, G., 2007. 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Evolutionary Computation 8, 125–147 Abbass, H.A., Sarker, R., Newton, Ch., 2001. PDE: A Pareto–frontier differential evolution approach for multi objective optimization problems. Proceedings of the Congress on Evolutionary Appendix B Computation, Vol. 2, Piscataway NJ, pp. 971–978 Soodamani, R., Liu, Z.Q., 2000. GA-based learning for a model-based object recognition system. International Journal of Approximate Reasoning 23, 85–109 | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/632 | |
| dc.description | Supervised by Prof. Dr. Mohammad Ahsan Habib | en_US |
| dc.description.abstract | This work is the optimization of machining parameters in steel turning operation. In this study, the experimental work was carried out by turning Stainless Steel 304 by using carbide inserts. There were three main purposes of this study. First was to explain and demonstrate a systemic procedure to collect a combination of data of parameters and then apply when the turning operation is performed. The second was to find the optimal combination by using Optimization Algorithm- WOA and Grey Analysis. The main conclusion drawn from this study is that efficient turning operations can be performed on 304 SS which will save power and time. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Department of Mechanical and Production Engineering, Islamic University of Technology, Board Bazar, Gazipur, Bangladesh | en_US |
| dc.title | Multi Objective Optimization of Turning Process Using Whale Algorithm | en_US |
| dc.type | Thesis | en_US |
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