The Effect of Process Parameters and Tool Geometrical Parameters on the Tool Peak Temperature in Machining Process

الموضوعات :

Maziar Mahdipour Jalilian ¹ , Amir Ghiasvand ² , Hasan Kheradmandan ³

1 - Department of Mechanical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran
2 - Department of Mechanical Engineering, University of Tabriz, Iran
3 - Department of Mechanical Engineering, Kermanshah Branch, Islamic Azad University, Arak, Iran

تاريخ الإرسال : 27 الجمعة , ربيع الأول, 1442 تاريخ التأكيد : 24 الجمعة , صفر, 1443 تاريخ الإصدار : 24 الأربعاء , محرم, 1443

الکلمات المفتاحية: Tool Temperature, Machining, Geometrical parameters, Tool Shape,

ملخص المقالة :

In the present study, the effects of process and geometrical parameters on the maximum temperature of tool have been investigated. Simulation of mild steel machining process in different cutting depths, speed of rotation (SOR), feeding rates, and different rake angles was performed. To verify the simulation, numerical results were compared with experimental results. Based on the results, it was found that by increasing the speed of rotation at a constant cutting depth and a constant feed rate, the maximum temperature of the process experiences a significant increase. By increasing the depth of the cut, the geometric location of the workpiece maximum temperature was transmitted to the edge of the tool and surface changes occurred, which it was accompanied with increment in the depth of the cut. The tool with the rake angle of -10° and the depth of cutting of 2 mm had the highest recorded temperature due to the lack of sufficient space for removing chips from the work surface.

المصادر:

• Hashmi, K. H., Zakria, G., Raza, M. B., and Khalil, S., Optimization of Process Parameters for High Speed Machining of Ti-6Al-4V Using Response Surface Methodology, The International Journal of Advanced Manufacturing Technology, Vol. 85, No. 5-8, 2016, pp. 1847-1856.


• D’addona, S. J. Raykar, and M. Narke, "High speed machining of Inconel 718: tool wear and surface roughness analysis," Procedia CIRP, vol. 62, 2017, pp. 269-274.


• Wang, B., Liu, Z., Evaluation on Fracture Locus of Serrated Chip Generation with Stress Triaxiality in High Speed Machining of Ti6Al4V, Materials & Design, Vol. 98, 2016, pp. 68-78.


• Bordin, S., Sartori, S., Bruschi, and Ghiotti, A., Experimental Investigation On the Feasibility of Dry and Cryogenic Machining as Sustainable Strategies When Turning Ti6Al4V Produced by Additive Manufacturing, Journal of cleaner production, Vol. 142, 2017, pp. 4142-4151.


• Umbrello, D., Caruso, S., and Imbrogno, S., Finite Element Modelling of Microstructural Changes in Dry and Cryogenic Machining AISI 52100 steel, Materials Science and Technology, Vol. 32, No. 11, 2016, pp. 1062-1070.


• Özel, T., Zeren, E., Finite Element Modeling the Influence of Edge Roundness On the Stress and Temperature Fields Induced by High-Speed Machining, The International Journal of Advanced Manufacturing Technology, Vol. 35, No. 3-4, 2007, pp. 255-267.


• Karpat, Y., Temperature Dependent Flow Softening of Titanium Alloy Ti6Al4V: An Investigation Using Finite Element Simulation of Machining, Journal of Materials Processing Technology, Vol. 211, No. 4, 2011, pp. 737-749.


• Ghiasvand, S. Hassanifard, Numerical Simulation of FSW and FSSW with Pinless Tool of AA6061-T6 Al Alloy by CEL Approach, Journal of Solid and Fluid Mechanics, Vol. 8, No. 3, 2018, pp. 65-75.


• Cavaliere, P., De Santis, A., Panella, F., and Squillace, A., Effect of Welding Parameters On Mechanical and Microstructural Properties of Dissimilar AA6082–AA2024 Joints Produced by Friction Stir Welding, Materials & Design, Vol. 30, No. 3, 2009, pp. 609-616.


• Schmidt, H., Hattel, J., and Wert, J., An Analytical Model for The Heat Generation in Friction Stir Welding, Modelling and Simulation in Materials Science and Engineering, Vol. 12, No. 1, 2003, pp. 143.


• Arrazola, P. J., Investigations on the Effects of Friction Modeling in Finite Element Simulation of Machining, International Journal of Mechanical Sciences, Vol. 52, No. 1, 2010, pp. 31-42.


• Marimuthu, P. K., Prasada, T. H., and Kumar, C., 3d Finite Element Model to Predict Machining Induced Residual Stresses Using Arbitrary Lagrangian Eulerian Approach, Journal of Engineering Science and Technology, Vol. 13, No. 2, 2018, pp. 309-320.


• Jafarian, F., Ciaran, M. I., Umbrello, D., Arrazola, P., Filice, L. and Amirabadi, H., Finite Element Simulation of Machining Inconel 718 Alloy Including Microstructure Changes, International Journal of Mechanical Sciences, Vol. 88, 2014, pp. 110-121.


• Akhil M. H., Akhil C K, Afeez, C. K., Akhilesh, P. M., and Rahul Rajan, R., Measurement of Cutting Temperature During Machining, IOSR Journal of Mechanical and Civil Engineering, Research Paper, Vol. 13, No. 2, 2016, pp. 108-122.


• Mousavi, S., Kelishami, A. R., Experimental and Numerical Analysis of the Friction Welding Process for the 4340 Steel and Mild Steel Combinations, Welding Journal New York, Vol. 87, No. 7, 2008, pp. 178.


• MatWeb, L., MatWeb: Material Property Data, línea]. Available: http://www.matweb. com/search/DataSheet. aspx, 2013.


• Johnson, G. R., Cook, W. H., Fracture Characteristics of Three Metals Subjected to Various Strains, Strain Rates, Temperatures and Pressures, Engineering fracture mechanics, Vol. 21, No. 1, 1985, 1985, pp. 31-48.


• Duan, C., Dou, T., Cai, Y., and Li, Y., Finite Element Simulation and Experiment of Chip Formation Process During High Speed Machining of AISI 1045 Hardened Steel, International Journal of Recent Trends in Engineering, Vol. 1, No. 5, 2009, pp. 46-50.


• Iqbal, M., Senthil, K., Bhargava, P., and Gupta, N., The Characterization and Ballistic Evaluation of Mild Steel, International Journal of Impact Engineering, Vol. 78, 2015, pp. 98-113.


• Hibbit, H., Karlsson, B., and Sorensen, E., ABAQUS User Manual, Vol. 6.12, Simulia, Providence, RI, 2012.