Prediction of Surface Roughness in End Milling Process Using Intelligent Systems : A Comparative Study
Author
Source
Applied Computational Intelligence and Soft Computing
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-18, 18 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-10-26
Country of Publication
Egypt
No. of Pages
18
Main Subjects
Information Technology and Computer Science
Abstract EN
A study is presented to model surface roughness in end milling process.
Three types of intelligent networks have been considered.
They are (i) radial basis function neural networks (RBFNs), (ii) adaptive neurofuzzy inference systems (ANFISs), and (iii) genetically evolved fuzzy inference systems (G-FISs).
The machining parameters, namely, the spindle speed, feed rate, and depth of cut have been used as inputs to model the workpiece surface roughness.
The goal is to get the best prediction accuracy.
The procedure is illustrated using experimental data of end milling 6061 aluminum alloy.
The three networks have been trained using experimental training data.
After training, they have been examined using another set of data, that is, validation data.
Results are compared with previously published results.
It is concluded that ANFIS networks may suffer the local minima problem, and genetic tuning of fuzzy networks cannot insure perfect optimality unless suitable parameter setting (population size, number of generations etc.) and tuning range for the FIS, parameters are used which can be hardly satisfied.
It is shown that the RBFN model has the best performance (prediction accuracy) in this particular case.
American Psychological Association (APA)
Sharkawy, Abdel Badie. 2011. Prediction of Surface Roughness in End Milling Process Using Intelligent Systems : A Comparative Study. Applied Computational Intelligence and Soft Computing،Vol. 2011, no. 2011, pp.1-18.
https://search.emarefa.net/detail/BIM-452631
Modern Language Association (MLA)
Sharkawy, Abdel Badie. Prediction of Surface Roughness in End Milling Process Using Intelligent Systems : A Comparative Study. Applied Computational Intelligence and Soft Computing No. 2011 (2011), pp.1-18.
https://search.emarefa.net/detail/BIM-452631
American Medical Association (AMA)
Sharkawy, Abdel Badie. Prediction of Surface Roughness in End Milling Process Using Intelligent Systems : A Comparative Study. Applied Computational Intelligence and Soft Computing. 2011. Vol. 2011, no. 2011, pp.1-18.
https://search.emarefa.net/detail/BIM-452631
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-452631