Equbal, Azhar and Equbal, Md Asif and Equbal, Md Israr and Ravindrannair, Pranav and Khan, Zahid A. and Badruddin, Irfan Anjum and Kamangar, Sarfaraz and Tirth, Vineet and Javed, Syed and Kittur, M. (2022) Evaluating CNC milling performance for machining AISI 316 stainless steel with carbide cutting tool insert. MATERIAL, 15 (22). ISSN 1996-1944, DOI https://doi.org/10.3390/ma15228051.
Full text not available from this repository.Abstract
The present study investigates the CNC milling performance of the machining of AISI 316 stainless steel using a carbide cutting tool insert. Three critical machining parameters, namely cutting speed (v), feed rate (f) and depth of cut (d), each at three levels, are chosen as input machining parameters. The face-centred central composite design (FCCCD) of the experiment is based on response surface methodology (RSM), and machining performances are measured in terms of material removal rate (MRR) and surface roughness (SR). Analysis of variance, response graphs, and three-dimensional surface plots are used to analyse experimental results. Multi-response optimization using the data envelopment analysis based ranking (DEAR) approach is used to find the ideal configuration of the machining parameters for milling AISI 316 SS. The variables v = 220 m/min, f = 0.20 mm/rev and d = 1.2 mm were obtained as the optimal machine parameter setting. Study reveals that MRR is affected dominantly by d followed by v. For SR, f is the dominating factor followed by d. SR is found to be almost unaffected by v. Finally, it is important to state that this work made an attempt to successfully machine AISI 316 SS with a carbide cutting tool insert, to investigate the effect of important machining parameters on MRR and SR and also to optimize the multiple output response using DEAR method.
Item Type: | Article |
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Funders: | King Khalid University |
Uncontrolled Keywords: | computer numerical control machine; material removal rate; milling; multi-response optimization; surface roughness |
Subjects: | T Technology > TJ Mechanical engineering and machinery |
Divisions: | Faculty of Engineering > Department of Mechanical Engineering |
Depositing User: | Ms Koh Ai Peng |
Date Deposited: | 25 Oct 2024 01:16 |
Last Modified: | 25 Oct 2024 01:16 |
URI: | http://eprints.um.edu.my/id/eprint/46197 |
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