Investigation of the effect of machinability parameters by voice activated ultrasonic sound wave device during turning process of pre-heated mild steel

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dc.contributor.author Latif, Md. Sharafat
dc.contributor.author Neelav, Afzal Hossain
dc.date.accessioned 2021-09-17T09:30:24Z
dc.date.available 2021-09-17T09:30:24Z
dc.date.issued 2014-11-15
dc.identifier.citation [1] Johnson, K. L., Contact Mechanics, Cambridge University Press, ISBN 0-521- 34796-3,pp.407,(1985). [2] Stachowiak, G. W. and Batchelor, A. W., Engineering tribology , Boston: Butterworth-Heinemann, ISBN 0-7506-7304-4, pp. 450, (2001). [3] Kalpakjian, S., and Schmid, S.R., Manufacturing Processes for Engineering Materials”,5th ed. ,India: Dorling Kindersley Pvt. Ltd.(under license from Pearson Educationin South Asia), pp. 440-447, (2009). [4] Silberschmidta, V.V, Mahdyb, S.M.A., Goudab, M.A., Naseera, A., Agostino Maurottoa, A. and Roya, A., Surface-roughness improvement in ultrasonically assisted turning ,2nd CIRP Conference on Surface Integrity (CSI), Procedia CIRP, Volume 13, pp. 49 – 54, ( 2014). [5] Mahdy, S.M.A., Gouda, M.A. and Silberschmidt, V.V., Study of ultrasonically assisted turning of stainless steel and brass alloys ,Journal of Physics: Conference Series 451, paper 012037, (2013). [6] Muhammad, R., Maurotto, A., Roy, A. and Silberschmidt, V.V., Ultrasonically assisted turning of Ti-6Al-2Sn-4Zr-6Mo ,Journal of Physics: Conference Series 382, paper 012016, (2012). [7] Rimkeviciene, J., Ostaševicius,V., Jurenas, V. and Gaidys, R., Experiments and simulations of ultrasonically assisted turning tool ,MECHANIKA,ISSN 1392 – 1207, Volume 1, Issue 75, (2009). [8] Maurotto, A., Muhammad, R., Roy, A. and Silberschmidt, V.V., Enhanced ultrasonically assisted turning of a ß-titanium alloy ,Ultrasonics 53, pp. 1242, (2013) . [9] Patil, S., Joshi, S., Tewari, A. and Joshi, S.S., Modeling and simulation of effect of ultrasonic vibrations on machining of Ti6Al4V ,Ultrasonics, Volume 54, Issue 2, pp. 694–705, ( 2014). [10] Braghini, A. Jr., and Coelho, R.T, An Investigation of the Wear Mechanisms of Polycrystalline Cubic Boron Nitride (PCBN) Tools When End Milling Hardened Steels At Low/ Medium Cutting Speeds ,International Journal on Advanced Manufacturing Technology ,Volume 17, pp. 244-257, (2001). Page | 75 [11] Chien, W.T. and Tsai, C.S, The investigation on the prediction of tool wear and the determination of optimum cutting conditions in machining 17-4PH stainless steel , Journal of Materials Processing Technology, Volume 140, pp. 340–345, (2003). [12] Ghani, J.A., Choudhury, I.A. and Hassan, H.H., Application of taguchi method in the optimization of end milling parameters, Journal of Materials Processing Technology, Volume 145, pp. 84-92, (2004). [13] Özel, T. and Kar pat, Y., Predictive modeling of surface roughness and tool wear in hard turning using regression and neural networks ,International Journal of Machine Tools and Manufacture, Volume 45, pp. 467–479, (2005). [14] Mahmoud, E. A. E. and Abdelkarim, H. A., Optimum Cutting Parameters in Approach Angle ,Turning Operations using HSS Cutting Tool with 45Sudan0 Engineering Society Journal, Volume 53, Number 48, pp. 25-30, (2006). [15] Al-Ahmar i, A. M. A., Predictive machinability models for a selected hard material in turning operations ,Journal of Materials Processing Technology, Volume190, pp. 305–311, (2007). [16] Oxley, P.L.B., The Mechanics of Machining: An Analytical Approach to Assessing Machinability”,Ellis Horwood, Chichester, (1989). [17] Fnides, B., Aouici, H. and Yallese, M.A., Cutting forces and surface roughness in hard turning of hot work steel X38CrMoV5-1 using mixed ceramic , Mechanika, Volume 2, Number 70, pp. 73-78, (2008). [18] Wang, M.Y. and Lan, T.S, Parametric Optimization on Multi-Objective Precision Turning Using Grey Relational Analysis ,Information Technology Journal, Volume 7, pp.1072-1076, ( 2008). [19] Lin, W.S., Lee, B.Y. and Wu, C.L., Modeling the surface roughness and cutting, Journal of Materials Processing Technology force for turning, Volume 108, pp. 286- 293, ( 2001). [20] Feng, C.X. and Wang, X., Development of Empirical Models for Surface Roughness Prediction in Finish Turning ,International Journal of Advanced Manufacturing Technology, Volume 20, pp. 348–356, (2002). Page | 76 [21] Suresh, P.V.S., Rao, P.V. and Deshmukh, S.G, A genetic algorithmic approach for optimization of surface roughness prediction model ,International Journal of Machine Tools and Manufacture, Volume 42, pp. 675–680, (2002). [22] Lee, S.S. and Chen, J.C, Online surface roughness recognition system using artificial neural networks system in turning operations ,International Journal of Advanced Manufacturing Technology, Volume 22, pp. 498–509, (2003). [23] Kirby, E.D., Zhang, Z. and Chen, J.C., Development of An Accelerometer based surface roughness Prediction System in Tur ning Operation Using Multiple Regression Techniques ,Journal of Industrial Technology, Volume 20, Number 4, pp. 1-8, (2004). [24] Eze, S.C., Izelu, C.O., Oreko, B.U. and Edward, B.A., Experimental Study of Induced Vibration and Work Surface Roughness in the Turning of 41Cr4 Alloy Steel using Response Surface Methodology ,International Journal of Innovative Research in Science, Engineering and Technology, ISSN: 2319-8753, Volume 2, Issue 12, (2013). [25] Kumar , K.A., Ratnam, C., Murthy, B.S.N., Ben, B.S. and Reddy, K.R.R.M., Optimization of Sur face Roughness in Face Turning Operation in Machining Of En-8 , International Journal of Engineering Science & Advanced Technology, ISSN: 2250–3676, Volume 2, Issue 4, pp. 807 – 812, (2012) . [26] Basha, N.Z. and Vivek, S., Optimization of CNC Turning Process Parameters on Aluminium 6061 Using Response Surface Methodology ,Engineering Science and Technology: An International Journal (ESTIJ),Volume XXX, No. XXX, (2013). [27] Raghunandan, B.V., Bhandarkar, S.L. and Pankaj, K.S., An Experimental Mathematical Modeling of Sur face Roughness in Turning Operation of En19 with Carbide Tool ,International Journal of Mechanical Engineering and Research, ISSN No. 2249-0019, Volume 3, Number 5, pp. 495-502, (2013), [28] Rodrigues, L.L.R., Kantharaj, A.N., Kantharaj, B., Freitas, W.R.C. and Murthy B.R.N., Effect of Cutting Parameters on Surface Roughness and Cutting Force in Turning Mild Steel ,Research Journal of Recent Sciences,ISSN 2277- 2502, Volume , Issue 10, pp. 19-26, (2012). [29] Kohli, A. and Dixit, U.S., A neural-network-based methodology for the prediction of sur face roughness in a turning process ,International Journal of Advanced Manufacturing Technology, Volume 25, pp.118–129, (2005). Page | 77 [30] Pal, S.K. and Chakraborty, D., Surface roughness prediction in turning using artificial neural network ,Neural Computing and Application, Volume 14, pp. 319– 324, ( 2005). [31] Singh, H. and Kumar, P., Optimizing Feed Force for Turned Parts through the Taguchi Technique , Sadhana,Volume 31, Number 6, pp. 671–681, (2006). [32] Ahmed, S.G, Development of a Pr ediction Model for Surface Roughness in Finish Turning of Aluminium ,Sudan Engineering Society Journal, Volume 52, Number 45, pp. 1- 5, (2006). [33] Abburi, N.R. and Dixit, U.S, A knowledge-based system for the prediction of surface roughness in turning process , Robotics and Computer- Integrated Manufacturing , Volume 22, pp. 363–372, (2006). [34] Zhong, Z.W., Khoo, L.P. and Han, S.T, Prediction of surface roughness of turned surfaces using neural networks ,International Journal of Advance Manufacturing Technology, Volume 28, pp. 688–693, (2006). [35] Kumanan, S., Saheb, S.K.N. and Jesuthanam, C.P, Prediction of Machining Forces using Neural Networks Trained by a Genetic Algorithm ,Institution of Engineers (India) Journal, Volume 87, pp. 11-15, (2006). [36] Doniavi, A., Eskanderzade, M. and Tahmsebian, M., Empirical Modeling of Surface Roughness in Turning Process of 1060 steel using Factorial Design Methodology”, Journal of Applied Sciences,Volume 7, Number 17, pp. 2509-2513, (2007). [37] Kassab, S.Y. and Khoshnaw, Y.K., The Effect of Cutting Tool Vibration on Surface Roughness of Work piece in Dry Turning Operation ,Engineering and Technology, Volume 25, Number 7, pp. 879- 889, (2007). [38] Thamizhmanii, S., Sapar udin, S. and Hasan, S., Analysis of Surface Roughness by Using Taguchi Method ,Achievements in Materials and Manufacturing Engineering, Volume 20, Issue 1-2, pp. 503-505, (2007). [39] Srikanth, T. and Kamala, V., A Real Coded Genetic Algorithm for Optimization of Cutting Parameters in Turning I JCSNS ,International Journal of Computer Science and Network Security, Volume 8, Number 6, pp. 189-193, (2008). [40] Arif, M.D., Patwari, A.U. and Chowdhury, N.A., Surface roughness characterization using digital image processing technique ,Proceedings of the 13th Annual Paper Meet (APM), Mechanical Engineering Division, The Institution of Engineers, Bangladesh, Volume 13, pp. 29- 35, (2010). Page | 78 [41] Patwari, A.U., Arif, M.D., Chowdhury, N.A. and Chowdhury, S. I., 3- D Contour generation and determination of surface roughness of shaped and horizontally milled plates using digital image processing, International Journal of Engineering, Annals of Faculty of Engineering, Hunedoara , Issue: 3, Issn: 1584-2673, (2011). [42] Sahoo, P., Barman, T.K. and Routara, B.C., Taguchi based practical dimension modeling and optimization in CNC turning ,Advance in Production Engineering and Management, Volume 3, Number 4, pp. 205-217, (2008). [43] Reddy, B.S., Padmanabhan, G. and Reddy, K.V.K., Surface Roughness Prediction Techniques for CNC turning ,Asian Journal of Scientific Research, Volume 1, Number 3, pp. 256-264, (2008). [44] Lan, T.S., Lo, C.Y., Wang M.Y. and Yen, A.Y., Multi Quality Prediction Model ”, Information Technology Journal, of CNC Turning Using Back Propagation Network Volume 7, Number 6, pp. 911-917, (2008). [45] Thamma, R., Comparison between Multiple Regression Models to Study Effect of Turning Parameters on the Surface Roughness ,Proceedings of the 2008 IAJC-IJME International Conference, ISBN 978-1-60643-379-9,Paper 133, ENG 103, pp. 1-12,(2008). [46] Shetty, R., Pai, R., Kamath, V. and Rao, S.S, Study on Surface Roughness Minimization in Turning of DRACs using Surface Roughness Methodology and Taguchi under Pressured Steam Jet Approach ,ARPN Journal of Engineering and Applied Sciences, Volume 3, Number 1, pp. 59-6, (2008). en_US
dc.identifier.uri http://hdl.handle.net/123456789/1038
dc.description Supervised by Dr. Md. Anayet Ullah Patwari, Professor, Department of Mechanical and Chemical Engineering (MCE), Islamic University of Technology, (IUT), Board Bazar, Gazipur-1704, Bangladesh. en_US
dc.description.abstract Surface roughness represents the dimensional accuracy of the finished product and is one of the most important quality requirements of the finished product. Surface roughness is generally detrimental to the efficient performance of machined parts, especially where relative motion between parts is concerned. For improvement of the surface quality several techniques like magnetic field, ultrasonic assisted turning etc has been introduced. Ultrasonically Assisted Turning (UAT) has been one of the techniques which showed great promise. It is a hybrid technique based on superimposition of ultrasonic vibration on a movement of a cutting tool in turning process. A sonotrode is usually used for applying the ultrasound frequency. But this is expensive and difficult. However, the present study investigates a new technique of application of ultrasonic sound waves. Instead of superimposing the ultrasound on the tool movement, ultrasonic sound waves have been applied into the turning cutting process externally. For making it more comfortable ultrasonic sound wave has been applied by voice it works through voice rather than manual controller. It is cost effective and easy to introduce. en_US
dc.language.iso en en_US
dc.publisher Department of Mechanical and Production Engineering (MPE),Islamic University of Technology(IUT), Board Bazar, Gazipur, Bangladesh en_US
dc.title Investigation of the effect of machinability parameters by voice activated ultrasonic sound wave device during turning process of pre-heated mild steel en_US
dc.type Thesis en_US


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