An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques

M. C. Karthik Rao, Rashmi L. Malghan, S. ArunKumar, Shrikantha S. Rao, Mervin A. Herbert

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

The present work is an endeavor to carry out a machining using LN2 in face milling operations and to produce the milling samples with excellent wear resistance property. The output response (wear rate) depends on appropriate choice of speed, feed, and depth of cut. The experimental data are conducted (collected) for SS316 as per central composite design. The present work exemplifies an employment of conventional and nonconventional strategies for optimizing the milling factors of cryogenically treated samples in face milling to achieve the desired wear (response). The results of nonlinear regression (desirability strategy) and nonconventional [particle swarm optimization, (PSO)] optimization techniques are compared, and PSO is found to outperform the desirability function approach. The present work even highlights the effect and results of LN2 on wear in contrast to wet condition.

Original languageEnglish
Pages (from-to)191-204
Number of pages14
JournalTransactions of the Indian Institute of Metals
Volume72
Issue number1
DOIs
Publication statusAccepted/In press - 30-01-2018

Fingerprint

Regression analysis
Cryogenics
Wear of materials
Particle swarm optimization (PSO)
Milling (machining)
Wear resistance
Machining
Composite materials

All Science Journal Classification (ASJC) codes

  • Metals and Alloys

Cite this

Karthik Rao, M. C. ; Malghan, Rashmi L. ; ArunKumar, S. ; Rao, Shrikantha S. ; Herbert, Mervin A. / An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques. In: Transactions of the Indian Institute of Metals. 2018 ; Vol. 72, No. 1. pp. 191-204.
@article{ebda1a77315f4a5589e547ccddf54541,
title = "An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques",
abstract = "The present work is an endeavor to carry out a machining using LN2 in face milling operations and to produce the milling samples with excellent wear resistance property. The output response (wear rate) depends on appropriate choice of speed, feed, and depth of cut. The experimental data are conducted (collected) for SS316 as per central composite design. The present work exemplifies an employment of conventional and nonconventional strategies for optimizing the milling factors of cryogenically treated samples in face milling to achieve the desired wear (response). The results of nonlinear regression (desirability strategy) and nonconventional [particle swarm optimization, (PSO)] optimization techniques are compared, and PSO is found to outperform the desirability function approach. The present work even highlights the effect and results of LN2 on wear in contrast to wet condition.",
author = "{Karthik Rao}, {M. C.} and Malghan, {Rashmi L.} and S. ArunKumar and Rao, {Shrikantha S.} and Herbert, {Mervin A.}",
year = "2018",
month = "1",
day = "30",
doi = "10.1007/s12666-018-1473-y",
language = "English",
volume = "72",
pages = "191--204",
journal = "Transactions of the Indian Institute of Metals",
issn = "0972-2815",
publisher = "Springer Science + Business Media",
number = "1",

}

An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques. / Karthik Rao, M. C.; Malghan, Rashmi L.; ArunKumar, S.; Rao, Shrikantha S.; Herbert, Mervin A.

In: Transactions of the Indian Institute of Metals, Vol. 72, No. 1, 30.01.2018, p. 191-204.

Research output: Contribution to journalArticle

TY - JOUR

T1 - An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques

AU - Karthik Rao, M. C.

AU - Malghan, Rashmi L.

AU - ArunKumar, S.

AU - Rao, Shrikantha S.

AU - Herbert, Mervin A.

PY - 2018/1/30

Y1 - 2018/1/30

N2 - The present work is an endeavor to carry out a machining using LN2 in face milling operations and to produce the milling samples with excellent wear resistance property. The output response (wear rate) depends on appropriate choice of speed, feed, and depth of cut. The experimental data are conducted (collected) for SS316 as per central composite design. The present work exemplifies an employment of conventional and nonconventional strategies for optimizing the milling factors of cryogenically treated samples in face milling to achieve the desired wear (response). The results of nonlinear regression (desirability strategy) and nonconventional [particle swarm optimization, (PSO)] optimization techniques are compared, and PSO is found to outperform the desirability function approach. The present work even highlights the effect and results of LN2 on wear in contrast to wet condition.

AB - The present work is an endeavor to carry out a machining using LN2 in face milling operations and to produce the milling samples with excellent wear resistance property. The output response (wear rate) depends on appropriate choice of speed, feed, and depth of cut. The experimental data are conducted (collected) for SS316 as per central composite design. The present work exemplifies an employment of conventional and nonconventional strategies for optimizing the milling factors of cryogenically treated samples in face milling to achieve the desired wear (response). The results of nonlinear regression (desirability strategy) and nonconventional [particle swarm optimization, (PSO)] optimization techniques are compared, and PSO is found to outperform the desirability function approach. The present work even highlights the effect and results of LN2 on wear in contrast to wet condition.

UR - http://www.scopus.com/inward/record.url?scp=85058444940&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85058444940&partnerID=8YFLogxK

U2 - 10.1007/s12666-018-1473-y

DO - 10.1007/s12666-018-1473-y

M3 - Article

VL - 72

SP - 191

EP - 204

JO - Transactions of the Indian Institute of Metals

JF - Transactions of the Indian Institute of Metals

SN - 0972-2815

IS - 1

ER -