Modeling and optimization of wire electrical discharge machining of γ-TiAl in trim cutting operation

By S. Sarkar, M. Sekh, S. Mitra, Bijoy Bhattacharyya. 2008

174 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/0ac44dc63742da93abbe9f1975123b2aff2117d4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Anish Kumar
2. Jatinder Kumar
3. R. Karthikeyan
4. Vinod Kumar
5. A. Velayudham
6. M. Seeman
7. G. Ganesan

In Electrical and Electronic Engineering

1. Anish Kumar
2. A. Velayudham
3. M. Seeman
4. G. Ganesan
5. Jatinder Kumar
6. R. Karthikeyan
7. M. Ghasemi Baboly
8. R. Bagherian Azhiri

In Mechanical Engineering

1. Anish Kumar
2. A. Velayudham
3. M. Seeman
4. G. Ganesan
5. Jatinder Kumar
6. R. Karthikeyan
7. M. Ghasemi Baboly
8. R. Bagherian Azhiri

Citations in the corpus

• Multi-response optimization of process parameters based on response surface methodology for pure titanium using WEDM process (2013, methodology): “[20] modeling and optimization of wire electrical discharge machining of γ-TiAl in trim cutting operation.”
• Application of Taguchi, ANFIS and grey relational analysis for studying, modeling and optimization of wire EDM process while using gaseous media (2014, methodology): “E-Gallab and Sklad [2–4] conducted vast research on turning of Al/SiC to find optimum tool and process conditions in which higher tool life and surface integrity are obtained.”
• Study on tool wear and surface roughness in machining of particulate aluminum metal matrix composite-response surface methodology approach (2010, methodology): “Finally, the individual desirability functions are combined to provide a measure of the composite or overall desirability of the multiresponse system [ 29 ].”