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OPTIMIZATION OF TOOL WEAR IN HARD TURNING OF EN 24 STEEL USING DoE AND VERIFICATION THROUGH ANOVA AND RSM

  • Unique Paper ID: 142774
  • Volume: 2
  • Issue: 6
  • PageNo: 147-151
  • Abstract:
  • This paper describes prediction of tool wear in hard turning of 817M40 (EN 24) steel material with 48 HRC at conventional lathe using Multicoated hard metal inserts with sculptured rake face geometry. Also, an attempt was made to fuse cutting force, cutting temperature and tool vibration (displacement), along with cutting velocity, feed and depth of cut to predict tool wear. In this work, based on Taguchi L18 orthogonal array (mixed design) using Minitab software was used to optimize the various cutting parameters such as cutting velocity, feed and depth of cut. In addition, the results obtained from Design of Experiment are compared with Analysis of Variance (ANOVA) Response surface methodology (RSM). The result obtained from Response surface methodology (RSM) and Analysis of Variance (ANOVA) confirms very closely with the result given by Design of Experiment (DoE).
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 2
  • Issue: 6
  • PageNo: 147-151

OPTIMIZATION OF TOOL WEAR IN HARD TURNING OF EN 24 STEEL USING DoE AND VERIFICATION THROUGH ANOVA AND RSM

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