Enhancing surface quality of en31 steel using Taguchi robust design


  • 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






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.


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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