Evaluating CNC milling performance for machining AISI 316 stainless steel with carbide cutting tool insert
Document Type
Article
Publication Date
11-1-2022
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.
Keywords
computer numerical control machine, material removal rate, milling, multi-response optimization, surface roughness
Publication Title
MATERIAL
Recommended Citation
Equbal, Azhar; Equbal, Md Asif; Equbal, Md Israr; Ravindrannair, Pranav; Khan, Zahid A.; Badruddin, Irfan Anjum; Kamangar, Sarfaraz; Tirth, Vineet; Javed, Syed; and Kittur, M., "Evaluating CNC milling performance for machining AISI 316 stainless steel with carbide cutting tool insert" (2022). Research Publications (2021 to 2025). 1548.
https://knova.um.edu.my/research_publications_2021_2025/1548
Divisions
mechanical
Funders
King Khalid University
Volume
15
Issue
22
Publisher
MDPI
Publisher Location
ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND