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

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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.

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Acknowledgements

I would like to thank NITK, Surathkal, for providing facilities to carry out my research work.

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, NITK, Surathkal, 575025, India

    M. C. Karthik Rao, Shrikantha S. Rao & Mervin A. Herbert

  2. Department of Computer Science Engineering, Madanapalle Institue of Technology and Science, Madanapalle, 517325, India

    Rashmi L. Malghan

  3. Department of Mechatronics Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India

    S. ArunKumar

Authors
  1. M. C. Karthik Rao
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  2. Rashmi L. Malghan
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  3. S. ArunKumar
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  4. Shrikantha S. Rao
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  5. Mervin A. Herbert
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Corresponding author

Correspondence to Rashmi L. Malghan.

Appendix: Test Cases

Appendix: Test Cases

SL. no.

Process variables

Experimental

S

F

D

CT

Wear rate

Surface roughness

1

2100

465

1.1

− 1

2.27

2.13

2

2800

379

0.7

0

2.41

2.62

3

1700

364

0.9

1

1.93

1.91

4

1200

420

1.3

1

1.74

1.73

5

2000

457

0.8

0

2.24

2.09

6

1500

500

1.2

1

1.99

1.83

7

2600

440

0.7

1

1.13

2.47

8

1285

520

1.3

1

0.62

1.71

9

2300

500

0.8

0

2.13

2.26

10

1392

390

0.9

1

1.66

1.77

11

2500

485

1

− 1

2.32

2.35

12

1850

510

1.4

1

2.01

1.99

13

2720

400

1.1

− 1

2.66

2.56

14

2200

380

0.8

0

2.17

2.22

15

2450

510

0.6

− 1

2.38

2.31

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Karthik Rao, M.C., Malghan, R.L., ArunKumar, S. et al. An Efficient Approach to Optimize Wear Behavior of Cryogenic Milling Process of SS316 Using Regression Analysis and Particle Swarm Techniques. Trans Indian Inst Met 72, 191–204 (2019). https://doi.org/10.1007/s12666-018-1473-y

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  • DOI: https://doi.org/10.1007/s12666-018-1473-y

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