TY - GEN
T1 - Hybrid Optimization for Machinability Enhancement during Green Machining of Stainless Steel
AU - Gupta, Kapil
N1 - Publisher Copyright:
© 2022 Trans Tech Publications Ltd, Switzerland.
PY - 2022
Y1 - 2022
N2 - Stainless steel 304 is one of the most promising materials for many industrial applications. Its machinability is poor whether machined in any environment. Conventional machining causes environmental degradation as well. In this paper, sustainable machining of SS304 using green lubricant is presented. Experiments have been conducted on Taguchi’s robust design of experiment technique. For machinability enhancement, a hybrid optimization technique VIKOR-Regression-PSO is employed. Machinability indicators that have been considered are tool wear, surface roughness, and chip reduction coefficient. Cutting speed, depth of cut, and feed rate have been considered as the variable machining parameters in this work. The hybrid optimization has been found very effective and provided a set of optimum machining parameters i.e. cutting speed-70m/min; feed rate-0.1mm/rev; depth of cut-0.5mm for the best values of machinability indicators i.e. tool wear-249.22 µm, roughness-11.08 µm, chip reduction coefficient-2.26.
AB - Stainless steel 304 is one of the most promising materials for many industrial applications. Its machinability is poor whether machined in any environment. Conventional machining causes environmental degradation as well. In this paper, sustainable machining of SS304 using green lubricant is presented. Experiments have been conducted on Taguchi’s robust design of experiment technique. For machinability enhancement, a hybrid optimization technique VIKOR-Regression-PSO is employed. Machinability indicators that have been considered are tool wear, surface roughness, and chip reduction coefficient. Cutting speed, depth of cut, and feed rate have been considered as the variable machining parameters in this work. The hybrid optimization has been found very effective and provided a set of optimum machining parameters i.e. cutting speed-70m/min; feed rate-0.1mm/rev; depth of cut-0.5mm for the best values of machinability indicators i.e. tool wear-249.22 µm, roughness-11.08 µm, chip reduction coefficient-2.26.
KW - Green machining
KW - PSO
KW - Stainless steel
KW - VIKOR
KW - hybrid optimization
UR - http://www.scopus.com/inward/record.url?scp=85127135033&partnerID=8YFLogxK
U2 - 10.4028/p-3w62bv
DO - 10.4028/p-3w62bv
M3 - Conference contribution
AN - SCOPUS:85127135033
SN - 9783035716917
T3 - Key Engineering Materials
SP - 411
EP - 420
BT - Modern Trends in Materials Processing - Selected peer-reviewed full text papers from the 5th International Conference on Modern Trends in Manufacturing Technologies and Equipment, ICMTMTE 2021
A2 - Bratan, Sergey
A2 - Roshchupkin, Stanislav
PB - Trans Tech Publications Ltd
T2 - 5th International Conference on Modern Trends in Manufacturing Technologies and Equipment, ICMTMTE 2021
Y2 - 6 September 2021 through 10 September 2021
ER -
