Application of response surface methodology in describing the performance of coated carbide tools when turning AISI 1045 steel

By M. Noordin, V. C. Venkatesh, Safian Sharif, S. Elting, A. Abdullah. 2004

774 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/c727f6b5da6857a758986afd484e71c351167280

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. Y. Şahin
2. A. Hussein
3. K. V. Sharma
4. Dilbag Singh
5. P. Venkateswara Rao
6. A. Motorcu
7. K. Kadirgama
8. E. Turkes

In Electrical and Electronic Engineering

1. Y. Şahin
2. Dilbag Singh
3. P. Venkateswara Rao
4. A. Motorcu

In Mechanical Engineering

1. Y. Şahin
2. A. Hussein
3. K. V. Sharma
4. Dilbag Singh
5. P. Venkateswara Rao
6. A. Motorcu
7. K. Kadirgama
8. E. Turkes

Citations in the corpus

• A surface roughness prediction model for hard turning process (2007, background): “[11] studied the application of response surface methodology in describing the performance of coated carbide tools when turning AISI 1045 steel.”
• Surface roughness model in machining hardened steel with cubic boron nitride cutting tool (2008, methodology): “In metal cutting process, extensive attention has been given to machining of hard and hardened steels in an experimental way and theoretical method [10–35].”
• Heat transfer enhancement using nanofluids in an automotive cooling system (2014, positive): “The observed heat-transfer enhancements using TiO2–W and SiO2–W in the cooling system were in good agreement with the experimental data reported by [24,25] and correlate with that of [22] with a deviation of approximately 2–4%.”
• Optimization of tool geometry parameters for turning operations based on the response surface methodology (2011, methodology): “Design and methods such as factorial design, response surface methodology (RSM) and Taguchi methods are now widely in use in place of one-factor-at-a-time experimental approach which is time consuming and exorbitant in cost [13].”