Application of Taguchi and response surface methodologies for geometric error in surface grinding process

By J. Kwak. 2005

417 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/2ef087d9def8984727678b1e0efd48d8a078418a

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. L. Karunamoorthy
2. S. Ramesh
3. C. Sahu
4. M. Garg
5. Nikolaos M. Vaxevanidis
6. John (Ioannis) D. Kechagias
7. K. Palanikumar
8. George P. Petropoulos

In Mechanical Engineering

1. L. Karunamoorthy
2. S. Ramesh
3. K. Palanikumar
4. C. Sahu
5. M. Garg
6. Nikolaos M. Vaxevanidis
7. John (Ioannis) D. Kechagias
8. George P. Petropoulos

Citations in the corpus

• Application of Taguchi design for quality characterization of abrasive water jet machining of TRIP sheet steels (2012, methodology): “8 can be obtained by a matrix approach [20].”
• Mathematical modeling and analysis of WEDM machining parameters of nickel-based super alloy using response surface methodology (2017, methodology): “The design procedure of RSM is as follows [22]:”
• Surface Roughness Analysis in Machining of Titanium Alloy (2008, methodology): “Kwak [12] has applied Taguchi response surface methodologies for optimizing geometric errors in surface grinding process.”
• Optimization of tool geometry parameters for turning operations based on the response surface methodology (2011, background): “In this way, the factor values that are not actually tested using fewer experimental combinations and the combinations themselves can be estimated [28,29].”