Effect of Minimum Quantity Lubrication on Surface Roughness and Temperature in Milling of EN31 Steel for Die Making

[1] Tunc, L. T., Gu, Y., Burke, M. G. “Effects Of Minimal Quantity Lubrication (MQL) On Surface Integrity In Robotic Milling Of Austenitic Stainless Steel”, Procedia CIRP 45, pp. 215 – 218, 2016. DOI: 10.1016/j.procir.2016.02.33710.1016/j.procir.2016.02.337Open DOISearch in Google Scholar

[2] Kedare S. B, Borse D.R, and Shahane P. T. “Effect of Minimum Quantity Lubrication (MQL) on Surface Roughness of Mild Steel of 15HRC on Universal Milling Machine” Procedia Materials Science 6, pp. 150 – 153, 2014. DOI: 10.1016/j.mspro.2014.07.01810.1016/j.mspro.2014.07.018Open DOISearch in Google Scholar

[3] Dhar, N. R., Islam, M. W. “A Study of Effects of MQL on Tool Wear, Job Dimension and Finish in Turning AISI-1040 Steel”, AEESEAP Journal of Engineering Education 31 (2), pp. 15 – 22, 2017.Search in Google Scholar

[4] Himanshu, P. R., Lalta, P., Mayank, P., Vineet, Ti. “An Estimating The Effect Of Process Parameters On Metal Removal Rate And Surface Roughness In Wedm Of Composite Al6063/Sic/Al2o3 By Taguchi Method“, Journal of Mechanical Engineering – Strojnícky časopis 67 (2), pp. 25 – 36, 2017. DOI: 10.1515/scjme-2017-001510.1515/scjme-2017-0015Open DOISearch in Google Scholar

[5] Beri, N., Maheshwari, S., Sharma, C., Kumar, A. “Machining Performance Evaluation During Electric Discharge Machining Of Inconel 718 Using The Taguchi Methodology“, Journal of Mechanical Engineering – Strojnícky časopis 62, (5 – 6), pp. 299 – 310, 2011.Search in Google Scholar

[6] Anand Babu, K., Vijaya Kumar, G., Venkataramaiah, P. “Prediction of Surface Roughness in Drilling of Al 7075/10% - SiCp Composite under MQL Condition using Fuzzy Logic”, Indian Journal of Science and Technology 8 (12), pp. 1 – 10, 2015. DOI: 10.17485/ijst/2015/v8i12/5407410.17485/ijst/2015/v8i12/54074Search in Google Scholar

[7] Shahriar, J. H., Md, Nafis, A. “A neuro-fuzzy approach to select cutting parameters for commercial die manufacturing”, Procedia Engineering 90, 753 – 759, 2014. DOI: https://doi.org/10.1016/j.proeng.2014.11.80910.1016/j.proeng.2014.11.809Open DOISearch in Google Scholar

[8] Andris, L., Toms, T. ”The Influence of High-Speed Milling Strategies on 3D Surface Roughness Parameters”, Procedia Engineering 100, pp. 1253 – 1261, 2015. DOI: 10.1016/j.proeng.2015.01.49110.1016/j.proeng.2015.01.491Search in Google Scholar

[9] Jurkovic, J., Korosec, M., Kopac, J. “New approach in tool wear measuring technique using CCD vision system“, International Journal of Machine Tools and Manufacture 45 (9), pp. 1023 – 1030, 2005.10.1016/j.ijmachtools.2004.11.030Search in Google Scholar

[10] Rajesh, Ch., Kumar, H., Garg, R. K. “Analysis and Evaluation of Heat Affected Zones in Electric Discharge Machining of EN 31 Die Steel”, Indian Journal of Engineering & Material Sciences 17, 91 – 98, 2010.Search in Google Scholar

[11] Dave, H. K., Patel, L. S, Raval, H. K. “Effect of machining conditions on MRR and surface roughness during CNC Turning of different Materials Using TiN Coated Cutting Tools – A Taguchi approach”, International Journal of Industrial Engineering Computations 3, pp. 925 – 930. 2012.10.5267/j.ijiec.2012.04.005Search in Google Scholar

[12] Arunkumar, N., Shareef Abdur Rawoof, H., Vivek, R. “Investigation on the Effect Of Process Parameters For Machining Of EN31 (Air Hardened Steel) By EDM”, International Journal of Engineering Research and Applications 2 (4), pp. 1111 – 1121, 2012.Search in Google Scholar

[13] Srinivasa Rao, M., Ramanaiah, N. “Optimization Of Process Parameters For Fsw Of Al-Mg-Mn-Sc-Zr Alloy Using Ccd And RSM“, Journal of Mechanical Engineering – Strojnícky časopis 68 (3), pp. 195 – 224, 2018. DOI: 10.2478/scjme-2018-003510.2478/scjme-2018-0035Open DOISearch in Google Scholar

[14] Gopalakannan, S., Senthilvelan, T., Kalaichelvan, K. “Modelling And Optimization Of Edm Process Parameters On Machining Of Al 7075/Sic Metal Matrix Composite By Applying Response Surface Method“, Journal of Mechanical Engineering – Strojnícky časopis 63 (1), pp. 37 – 54, 2012.Search in Google Scholar

[15] Ramanujam, R., Raju, R. “Process Parameter Optimization In Turning Of Al-Sic_p Composites Using Taguchi Based Desirability Function Analysis“, Journal of Mechanical Engineering – Strojnícky časopis 62 (2), 81 – 92, 2011.Search in Google Scholar

[16] Rajeswari, K., Lakshmi, P. “A Pso-Tuning of Fuzzy Logic Controller For Vehicle Suspension System“, Journal of Mechanical Engineering – Strojnícky Časopis 61 (4), pp. 215 – 232, 2010.10.1109/ARTCom.2010.22Search in Google Scholar

[17] Tsai, C. Y., Yeh, S. W. “A multiple objective particle swarm optimization approach for inventory classification”, International Journal of Production Economics 114 (2), pp. 656 – 666, 2008.10.1016/j.ijpe.2008.02.017Search in Google Scholar

[18] Sreenivasa Rao, M., Venkaiah, N. “Parametric Optimization In Machining Of Nimonic-263 Alloy Using RSM And Particle Swarm Optimization”, Procedia Materials Science 10, pp.70 – 79, 2015. DOI: https://doi.org/10.1016/j.mspro.2015.06.02710.1016/j.mspro.2015.06.027Search in Google Scholar

[19] Cus, F., Zuperl, U., Gecevska, V. “High speed end-milling optimization using Particle Swarm Intelligence”, Journal of Achievements in Materials and Manufacturing Engineering 22 (2), pp. 75 – 78, 2007.Search in Google Scholar

[20] Rajyalakshmi, G., Koushik, T., Kalyan, T. “Parametric Optimization In Wedm Using Particle Swarm Optimization Technique”, 56th IRF International Conference, Pune, India, 2016. ISBN: 978-93-86083-26-5.Search in Google Scholar

[21] Kennedy, J., Eberhart, R. “Particle Swarm Optimisation”, Proceedings of ICNN’95 - International Conference on Neural Networks, pp. 1942 – 1948, 1995. DOI:10.1109/ICNN.1995.48896810.1109/ICNN.1995.488968Open DOISearch in Google Scholar