OPTIMIZATION OF TOOL WEAR IN HARD TURNING OF EN 24 STEEL USING DoE AND VERIFICATION THROUGH ANOVA AND RSM
Author(s):
G. Ragul, Dr.S.Sankar
Keywords:
Tool Wear, Hard Turning, Minitab, Response Surface methodology, Analysis of Variance.
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).
Article Details
Unique Paper ID: 142774
Publication Volume & Issue: Volume 2, Issue 6
Page(s): 147 - 151
Article Preview & Download
Share This Article
Conference Alert
NCSST-2023
AICTE Sponsored National Conference on Smart Systems and Technologies
Last Date: 25th November 2023
SWEC- Management
LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT