Modeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression method

By Ilhan Asiltürk, Mehmet Çunkas. Expert systems with applications, 2011

402 citations recorded by the source corpus.

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

View Paper: https://www.semanticscholar.org/paper/a7e18e4ef655d22a6e3eb9ff4a36fd3deb6a570d

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. T. Kıvak
2. Ș. Karabulut

In Electrical and Electronic Engineering

1. T. Kıvak
2. Ș. Karabulut

In Mechanical Engineering

1. T. Kıvak
2. Ș. Karabulut

Citations in the corpus

• Optimization of surface roughness and flank wear using the Taguchi method in milling of Hadfield steel with PVD and CVD coated inserts (2014, background): “Good surface roughness provides important improvements in the tribologic characteristics, fatigue strength, corrosion resistance and aesthetic appearance of the product [13–15].”