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Statistical analysis and modelization of tool life and vibration in dry face milling of AISI 52100 STEEL in annealed and hardened conditions

  • Benghersallah, Mohieddine (Research Laboratory of Advanced Technologies in Mechanical Production (LRTAPM), BadjiMokhtar Annaba University) ;
  • Medjber, Ali (Research Laboratory of Advanced Technologies in Mechanical Production (LRTAPM), BadjiMokhtar Annaba University) ;
  • Zahaf, Mohamed Zakaria (Research Laboratory of Advanced Technologies in Mechanical Production (LRTAPM), BadjiMokhtar Annaba University) ;
  • Tibakh, Idriss (Research Laboratory of Advanced Technologies in Mechanical Production (LRTAPM), BadjiMokhtar Annaba University) ;
  • Amirat, Abdelaziz (Research Laboratory of Advanced Technologies in Mechanical Production (LRTAPM), BadjiMokhtar Annaba University)
  • 투고 : 2019.08.23
  • 심사 : 2020.08.29
  • 발행 : 2020.09.25

초록

The objective of the present work is to investigate the effect of cutting parameters (Vc, fz and ap) on tool life and the level of vibrations velocity in the machined part during face milling operation of hardened AISI 52100 steel. Dry-face milling has been achieved in the annealed (28 HRc) and quenched (55 HRc) conditions using multi-layer coating micro-grain carbide inserts. Statistical analysis based on the Response surface methodology (RSM) and ANOVA analysis have been conducted through a plan of experiments methodology using a reduced Taguchi table (L9) in order to obtain engineering models for tool life and vibration velocity in the workpiece for both heat treatment conditions. The results show that the cutting speed has a dominant influence on tool life for both soft and hard part. Cutting speed and feed per tooth is the most significant parameters for vibration levels. Comparing the experimental values with those predicted by the developed engineering models of tool life and levels of vibrations velocity, a good correlation has been obtained (between 97% and 99%) in annealed and hard conditions.

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참고문헌

  1. Abou-El-Hossein, K.A., Kadirgama, K., Hamdi, M. and Benyounis, K.Y. (2007), "Prediction of cutting force in end-milling operation of modified AISI P20 tool steel", J. Mater. Process. Technol., 182, 241-247. https://doi.org/10.1016/j.jmatprotec.2006.07.037
  2. Alauddin, M., El Baradie, M.A. and Hashmi, M.S.J. (1997), "Prediction of tool life in end milling by response surface methodology", J. Mater. Process Technol., 71, 456-465. https://doi.org/10.1016/S0924-0136(97)00111-8
  3. Alok, A. and Das, M. (2019), "White layer analysis of hard turned AISI 52100 steel with the fresh tip of newly developed $HSN^2$ coated insert", J. Manuf. Processes, 46, 16-25. https://doi.org/10.1016/j.jmapro.2019.08.016
  4. Aouici, H., Yallese, M.A., Chaoui, K., Mabrouki, T. and Rigal, J.F. (2012), "Analysis of surface roughness and cutting force components in hard turning with CBN tool: Prediction model and cutting conditions optimization", 45, 344-353. https://doi.org/10.1016/j. Measurement.2011.11.011
  5. Aouici, H., Bouchelaghem, H., Yallese, M.A., Elbah, M. and Fnides, B. (2014), "Machinability investigation in hard turning of AISI D3 cold work steel with ceramic tool using response surface methodology", The International Journal of Advanced Manufacturing Technoloy, 73(9-12), 1775-1788. https://doi.org/10.1007/s00170-014-5950-0
  6. Basu, A., Chakraborty, J., Shariff, S.M., Padmanabham, G., Joshi, S.V., Sundararajan, G., Majumdar, J.D. and Manna, I. (2007), "Laser surface hardening of austempered bainitic ball bearing steel", Scripta Materialia, 56, 887-890. https://doi.org/10.1016/j.scriptamat.2007.01.029
  7. Benghersallah, M., Benchiheub, S. and Amirat, A. (2018), "Statistical characterisation of end milling of AISI 52100 annealed bearing steel", Adv. Mater. Res., Int. J., 7(2), 137-148. https://doi.org/10.12989/amr.2018.7.2.137
  8. Cakir, M.C., Ensarioglu, C. and Demirayak, I. (2009), "Mathematical modeling of surface roughness for evaluating the effects of cutting parameters and coating material", J. Mater. Process. Technol., 209, 102-109. https://doi.org/10.1016/j.jmatprotec.2008.01.050
  9. Chakraborty, J. and Manna, I. (2012), "Development of ultrafine ferritic sheaves/plates in SAE 52100 steel for enhancement of strength by controlled thermomechanical processing", Materials Science and Engineering A, 548, 33-42. https://doi.org/10.1016/j.msea.2012.03.056
  10. Chomsamutr, K. and Jongprasithporn, S. (2012), "Optimization parameters of tool life model using the Taguchi approach and response surface methodology", IJCSI Int. J. Comput. Sci. Issues, 9(3), p. 120.
  11. Choudhury, I.A. and El-Baradie, M.A. (1998), "Tool life prediction model by design of experiments for turning high strength steel", J. Mater. Process. Technol., 77, 319-326. https://doi.org/10.1016/S0924-0136(97)00435-4
  12. Coromant, S. (2009), Milling: Main Catalogue, AB Sandvik Coromant, Sandviken, Sweden, p. 197.
  13. Da Silva, R.B., Vieira, J.M., Cardoso, R.N., Carvalho, H.C., Costa, E.S., Machado, A.R. and De A vila, R.F. (2011), "Tool wear analysis in milling of medium carbon steel with coated cemented carbide inserts using different machining lubrication/cooling systems", Wear, 271, 2459-2465. https://doi.org/10.1016/j.wear.2010.12.046
  14. Paturi, U.M.R., Devarasetti, H. and Narala, S.K.R. (2018), "Application of regression and artificial neural network analysis in modelling of surface roughness in hard turning of AISI 52100 Steel", Mater. Today: Proceedings, 5, 4766-4777. https://doi.org/10.1016/j.matpr.2017.12.050
  15. Pawar, S., Salve, A., Chinchanikar, S., Kulkarni, A. and Lamdhade, G. (2017), "Residual stresses during hard turning of AISI 52100 steel: Numerical modelling with experimental validation", Proceedings of the 5th International Conference of Materials Processing and Characterization (ICMPC 2016); Mater. Today: Proceedings, 4, 2350-2359. https://doi.org/10.1016/j.matpr.2017.02.084
  16. Selaimia, A.A., Yallese, M.A., Bensouilah, H., Meddour, I., Khattabi, R. and Mabrouki, T. (2017), "Modeling and optimization in dry face milling of X2CrNi18-9 austenitic stainless steel using RMS and desirability approach", Measurement, 107, 53-67. https://doi.org/10.1016/j.measurement.2017.05.012
  17. Siraj, S., Dharmadhikari, H.M. and Gore, N. (2018), "Modeling of roughness value from tribological parameters in hard turning of AISI 52100 steel", Proceedings of 2nd International Conference on Materials Manufacturing and Design Engineering; Procedia Manuf., 20, 344-349. https://doi.org/10.1016/j.promfg.2018.02.050
  18. Umamaheswarrao, P., Raju, D.R., Suman, K.N.S. and Sankar, B.R. (2018), "Multi objective optimization of Process parameters for hard turning of AISI 52100 steel using Hybrid GRA-PCA", Procedia Comput. Sci., 133, 703-710. https://doi.org/10.1016/j.procs.2018.07.129