Design-of-experiments application in machining titanium alloys for aerospace structural components

By Navneet Khanna, J. Paulo Davim. 2015

168 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Industrial and Manufacturing Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/6c76683b0a09788cc581303f64bb1e9ba424783e

How researchers see this paper

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

In Electrical and Electronic Engineering

1. Munish Kumar Gupta
2. Yahya Hisman Çelik
3. E. Kılıçkap
4. Vishal S. Sharma
5. A. Yardımeden

In Mechanical Engineering

1. Munish Kumar Gupta
2. Yahya Hisman Çelik
3. E. Kılıçkap
4. Vishal S. Sharma
5. Piyush Sood
6. A. Yardımeden
7. Mozammel Mia

Citations in the corpus

• Mathematical Modelling and Optimization of Cutting Force, Tool Wear and Surface Roughness by Using Artificial Neural Network and Response Surface Methodology in Milling of Ti-6242S (2017, background): “Khanna and Davim [12] studied the machinability of various titanium alloys under different cutting parameters.”
• Machining Parameters Optimization of Titanium Alloy using Response Surface Methodology and Particle Swarm Optimization under Minimum-Quantity Lubrication Environment (2016, background): “For instance, amid the machining of consistently utilized materials such as aluminum and steel, a large portion of the heat developed gets transmitted to the chip, while in the machining of titanium alloys, majority of the heat developed gets transmitted to the cutting tool, hence making a prominent”