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Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert
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 paramete...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696204/ https://www.ncbi.nlm.nih.gov/pubmed/36431537 http://dx.doi.org/10.3390/ma15228051 |
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author | Equbal, Azhar Equbal, Md. Asif Equbal, Md. Israr Ravindrannair, Pranav Khan, Zahid A. Badruddin, Irfan Anjum Kamangar, Sarfaraz Tirth, Vineet Javed, Syed Kittur, M. I. |
author_facet | Equbal, Azhar Equbal, Md. Asif Equbal, Md. Israr Ravindrannair, Pranav Khan, Zahid A. Badruddin, Irfan Anjum Kamangar, Sarfaraz Tirth, Vineet Javed, Syed Kittur, M. I. |
author_sort | Equbal, Azhar |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9696204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96962042022-11-26 Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert Equbal, Azhar Equbal, Md. Asif Equbal, Md. Israr Ravindrannair, Pranav Khan, Zahid A. Badruddin, Irfan Anjum Kamangar, Sarfaraz Tirth, Vineet Javed, Syed Kittur, M. I. Materials (Basel) Article 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. MDPI 2022-11-15 /pmc/articles/PMC9696204/ /pubmed/36431537 http://dx.doi.org/10.3390/ma15228051 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Equbal, Azhar Equbal, Md. Asif Equbal, Md. Israr Ravindrannair, Pranav Khan, Zahid A. Badruddin, Irfan Anjum Kamangar, Sarfaraz Tirth, Vineet Javed, Syed Kittur, M. I. Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert |
title | Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert |
title_full | Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert |
title_fullStr | Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert |
title_full_unstemmed | Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert |
title_short | Evaluating CNC Milling Performance for Machining AISI 316 Stainless Steel with Carbide Cutting Tool Insert |
title_sort | evaluating cnc milling performance for machining aisi 316 stainless steel with carbide cutting tool insert |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9696204/ https://www.ncbi.nlm.nih.gov/pubmed/36431537 http://dx.doi.org/10.3390/ma15228051 |
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