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Personal profile

Research Interests

Mechatronics

External positions

Fingerprint Dive into the research topics where Arun Kumar Shettigar is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

  • 1 Similar Profiles
Composite materials Engineering & Materials Science
Friction Engineering & Materials Science
Machining Engineering & Materials Science
Friction stir welding Engineering & Materials Science
Milling (machining) Engineering & Materials Science
friction Physics & Astronomy
Neural networks Engineering & Materials Science
Particle swarm optimization (PSO) Engineering & Materials Science

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Research Output 2010 2019

  • 61 Citations
  • 4 h-Index
  • 12 Article
  • 2 Conference contribution
  • 2 Conference article

Microstructure evolution and mechanical properties of friction stir welded AA6061/rutile composite

Prabhu, S. R. B., Shettigar, A. K., Herbert, M. A. & Rao, S. S., 21-06-2019, In : Materials Research Express. 6, 8, 0865I7.

Research output: Contribution to journalArticle

Friction
Mechanical properties
Friction stir welding
Microstructure
Composite materials

Reinforcement of titanium dioxide nanoparticles in aluminium alloy AA 5052 through friction stir process

Mathur, V., B, S. R. P., Patel G. C, M. & Shettigar, A. K., 03-04-2019, In : Advances in Materials and Processing Technologies. 5, 2, p. 329-337 9 p.

Research output: Contribution to journalArticle

Open Access
Titanium dioxide
Aluminum alloys
Reinforcement
Friction
Nanoparticles
1 Citation (Scopus)

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, R. L., ArunKumar, S., Rao, S. S. & Herbert, M. A., 30-01-2018, (Accepted/In press) In : Transactions of the Indian Institute of Metals. 72, 1, p. 191-204 14 p.

Research output: Contribution to journalArticle

Regression analysis
Cryogenics
Wear of materials
Particle swarm optimization (PSO)
Milling (machining)
2 Citations (Scopus)

A systematic approach to model and optimize wear behaviour of castings produced by squeeze casting process

Patel G C, M., Shettigar, A. K. & Parappagoudar, M. B., 01-04-2018, In : Journal of Manufacturing Processes. 32, p. 199-212 14 p.

Research output: Contribution to journalArticle

Squeeze casting
Wear of materials
Neural networks
Backpropagation
Particle swarm optimization (PSO)
2 Citations (Scopus)

Effect of process parameters in face milling operation and analysis of cutting force using indirect method

malghan, R. L., Rao, K. M. C., ArunKumar, S., Rao, S. S. & D’Souza, R. J., 03-10-2018, In : Materials and Manufacturing Processes. 33, 13, p. 1406-1414 9 p.

Research output: Contribution to journalArticle

Milling (machining)
Machining
Metal cutting
Analysis of variance (ANOVA)
Local area networks