Enhancing surface quality of en31 steel using Taguchi robust design

  • Authors

    • Fayaz Ahmad Mir Department of Mechanical Engineering, NIT Srinagar (J&K)-190006
    • Sheikh Shahid Ul Islam Department of Mechanical Engineering, NIT Srinagar (J&K)-190006
    • Mohammad Irfan Hajam Department of Mechanical Engineering, NIT Srinagar (J&K)-190006
    • Lubaid Nisar Department of Mechanical Engineering, NIT Srinagar (J&K)-190006
    2023-11-30
    https://doi.org/10.14419/ijet.v12i2.32423
  • This study employs Taguchi's robust design and regression to investigate how milling process parameters affect EN31 steel machin-ability. Three parameters—cutting speed, feed per tooth, and depth of cut—underwent nine experiments using Taguchi's L9 or-thogonal plan on a CNC milling center. Optimal settings were determined through mean analysis (ANOM), while analysis of vari-ance (ANOVA) with 95% confidence assessed parameter impact on surface roughness. Notably, feed per tooth displayed substantial influence (75.351%) on surface roughness. Regression analysis effectively aligned predictions with experimental outcomes, and a confirmation test validated successful Taguchi optimization.

  • References

    1. A. Baburaj, K. B. S. S. Chaudhary, R. K. Khatirkar, and S. G. Sapate, “Abrasive wear behaviour of heat treated En31 steel,” ISIJ Inter-national, vol. 53, no. 8, pp. 1471–1478, 2013, https://doi.org/10.2355/isijinternational.53.1471.
    2. M. Hanief and M. F. Wani, “Effect of surface roughness on wear rate during running-in of En31-steel: Model and experimental valida-tion,” Mater Lett, vol. 176, pp. 91–93, 2016, https://doi.org/10.1016/j.matlet.2016.04.087.
    3. K. J. Franklin, S. Joshy, R. Midhun, and N. A. N, “Microstructural study of quenched EN 31 steel in biodegradable oils,” vol. 4, no. 1, pp. 85–94, 2019.
    4. B. P. Harichandra, M. Prashanth, M. Mahapathi, and S. V. Prakash, “Evaluation of mechanicalProperties of EN31 steel heat treated us-ing bio-degradable oils,” International Journal of Applied Engineering Research, vol. 10, no. 50, pp. 1248–1252, 2015.
    5. M. K. Das, T. K. Barman, K. Kumar, and P. Sahoo, “Effect of Process Parameters on MRR and Surface Roughness in ECM of EN 31 Tool Steel Using WPCA,” International Journal of Materials Forming and Machining Processes, vol. 4, no. 2, pp. 45–63, 2017, https://doi.org/10.4018/IJMFMP.2017070104.
    6. Debasish Mohanty and N C Nayak, “Effect of Process Parameters on Performance of EN-31 Steel using WEDM: Experimentation and Optimi-zation,” International Journal of Engineering Research and, vol. V5, no. 07, pp. 536–547, 2016. https://doi.org/10.1016/S0898-1221(03)90006-X.
    7. S. K. Chary Nalbandet al., “Evaluation of Surface Roughness and Cutting Temperature of EN31 Steel with Varying MQSL Parameters,” IOP Conf Ser Mater Sci Eng, vol. 895, no. 1, 2020, https://doi.org/10.1088/1757-899X/895/1/012003.
    8. P. C. Chandra, V. Kumar, and S. Mukherjee, “Investigation of Surface Roughness in High-Speed Turning of EN 31 Steel,” International Journal of Current Research and Modern Education, vol. 2, no. 2, pp. 138–152, 2017.
    9. X. Shen, D. Zhang, C. Yao, L. Tan, and H. Yao, “Formation mechanism of surface metamorphic layer and influence rule on milling TC17 titani-um alloy,” International Journal of Advanced Manufacturing Technology, vol. 112, no. 7–8, pp. 2259–2276, 2021. https://doi.org/10.1007/s00170-020-06382-8.
    10. M. W. Safeen and P. R. Spena, “Main issues in quality of friction stir welding joints of aluminum alloy and steel sheets,” Metals (Ba-sel), vol. 9, no. 5, 2019, https://doi.org/10.3390/met9050610.
    11. J. Chen and M. Zhang, “Three-dimensional simulation of tool parameters for ultrasonic elliptical vibration turning of titanium alloy,” Perva-siveHealth: Pervasive Computing Technologies for Healthcare, no. 1, pp. 336–340, 2019, https://doi.org/10.1145/3366194.3366253.
    12. Z. Wang and L. Li, “Optimization of process parameters for surface roughness and tool wear in milling TC17 alloy using Taguchi with grey relational analysis,” Advances in Mechanical Engineering, vol. 13, no. 2, pp. 1–8, 2021, https://doi.org/10.1177/1687814021996530.
    13. I. D. Palacio-Caro, P. N. Alvarado-Torres, and L. F. Cardona-Sepúlveda, “Numerical Simulation of the Flow and Heat Transfer in an Electric Steel Tempering Furnace,” Energies 2020, Vol. 13, Page 3655, vol. 13, no. 14, p. 3655, Jul. 2020, https://doi.org/10.3390/en13143655.
    14. G. Bolar, A. Das, and S. N. Joshi, “Measurement and analysis of cutting force and product surface quality during end-milling of thin-wall com-ponents,” Measurement, vol. 121, pp. 190–204, 2018. https://doi.org/10.1016/j.measurement.2018.02.015.
    15. S. Vijay and V. Krishnaraj, “Machining parameters optimization in end milling of Ti-6Al-4 V,” Procedia Engineering, vol. 64, pp. 1079–1088, 2013. https://doi.org/10.1016/j.proeng.2013.09.186.
    16. V. Sathyamoorthy, S. Deepan, S. P. Sathya Prasanth, and L. Prabhu, “Optimization of machining parameters for surface roughness in end mill-ing of magnesium AM60 alloy,” Indian Journal of Science and Technology, vol. 10, no. 32, pp. 1–7, 2017. https://doi.org/10.17485/ijst/2017/v10i32/104651.
    17. B. Title et al., “Metadata of the chapter that will be visualized in SpringerLink,” 2022.
    18. S. L. Campanelli, G. Casalino, N. Contuzzi, and A. D. Ludovico, “Taguchi optimization of the surface finish obtained by laser ablation on selec-tive laser molten steel parts,” Procedia CIRP, vol. 12, pp. 462–467, 2013, https://doi.org/10.1016/j.procir.2013.09.079.
    19. M. Syahmi, N. Mat, Y. Ahmad, and R. Yusoffa, “Taguchi Method Approach on Effect of Lubrication Condition on Surface Roughness in Mill-ing Operation,” vol. 53, pp. 594–599, 2013, https://doi.org/10.1016/j.proeng.2013.02.076.
    20. J. S. Pang, M. N. M. Ansari, O. S. Zaroog, M. H. Ali, and S. M. Sapuan, “Taguchi design optimization.n of machining parameters on the CNC end milling process of halloysite nanotube with aluminium reinforced epoxy matrix ( HNT / Al / Ep ) hybrid composite,” HBRC Journal, vol. 10, no. 2, pp. 138–144, 2014, https://doi.org/10.1016/j.hbrcj.2013.09.007.
    21. J. Z. Zhang, J. C. Chen, and E. D. Kirby, “Surface roughness optimization in an end-milling operation using the Taguchi design method,” vol. 184, pp. 233–239, 2007, https://doi.org/10.1016/j.jmatprotec.2006.11.029.
    22. J. Kopac and P. Krajnik, “Robust design of flank milling parameters based on grey-Taguchi method,” vol. 191, pp. 400–403, 2007, https://doi.org/10.1016/j.jmatprotec.2007.03.051.
    23. S. H. Tomadi, J. A. Ghani, C. H. C. Haron, H. M. Ayu, and R. Daud, “Effect of Cutting Parameters on Surface Roughness in End Mill-ing of AlSi / AlN Metal Matrix Composite,” Procedia Eng, vol. 184, pp. 58–69, 2017, https://doi.org/10.1016/j.proeng.2017.04.071.
    24. A. Noor, Z. A. Khan, P. Goel, and M. Kumar, “Optimization of Deep Drilling Process Parameters of AISI 321 Steel using Taguchi Method,” MSPRO, vol. 6, no. Icmpc, pp. 1217–1225, 2014, https://doi.org/10.1016/j.mspro.2014.07.195.
    25. K. Venkata, “A study on performance characteristics and multi response optimization of process parameters to maximize performance of micro milling for Ti-6Al-4V,” Journal of Alloys and Compounds, vol. 781, pp. 773–782, 2019, https://doi.org/10.1016/j.jallcom.2018.12.105.
    26. A. K. Roy and K. Kumar, “Effect and Optimization of Machine Process Parameters on MRR for EN19 & EN41 materials using Taguchi,” Pro-cedia Technology, vol. 14, pp. 204–210, 2014, https://doi.org/10.1016/j.protcy.2014.08.027.
    27. H. C. Wu, “Linear regression analysis for fuzzy input and output data using the extension principle,” Computers and Mathematics with Applica-tions, vol. 45, no. 12, pp. 1849–1859, 2003, https://doi.org/10.1016/S0898-1221(03)90006-X.
    28. K. Stapor, “Linear Regression and Correlation,” Intelligent Systems Reference Library, vol. 176, pp. 133–149, 2020, doi: 10.1007/978-3-030-45799-0_3. https://doi.org/10.1007/978-3-030-45799-0_3.
    29. M. R. Rabiei, M. Arashi, and M. Farrokhi, “Fuzzy ridge regression with fuzzy input and output,” Soft Computing, vol. 23, no. 23, pp. 12189–12198, 2019, https://doi.org/10.1007/s00500-019-04164-3.
  • Downloads

  • How to Cite

    Fayaz Ahmad Mir, Sheikh Shahid Ul Islam, Mohammad Irfan Hajam, & Lubaid Nisar. (2023). Enhancing surface quality of en31 steel using Taguchi robust design. International Journal of Engineering & Technology, 12(2), 102-108. https://doi.org/10.14419/ijet.v12i2.32423