Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert
Autor: | Azhar Equbal, Md. Asif Equbal, Md. Israr Equbal, Pranav Ravindrannair, Zahid A. Khan, Irfan Anjum Badruddin, Sarfaraz Kamangar, Vineet Tirth, Syed Javed, M. I. Kittur |
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Jazyk: | angličtina |
Rok vydání: | 2022 |
Předmět: |
computer numerical control machine
material removal rate milling multi-response optimization surface roughness Technology Electrical engineering. Electronics. Nuclear engineering TK1-9971 Engineering (General). Civil engineering (General) TA1-2040 Microscopy QH201-278.5 Descriptive and experimental mechanics QC120-168.85 |
Zdroj: | Materials, Vol 15, Iss 22, p 8051 (2022) |
Druh dokumentu: | article |
ISSN: | 1996-1944 |
DOI: | 10.3390/ma15228051 |
Popis: | 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. |
Databáze: | Directory of Open Access Journals |
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