Application of Neuro-Fuzzy Systems for Modeling Surface Roughness Parameters for Difficult-to-Cut-Steel
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Published:2017-08
Issue:
Volume:261
Page:277-284
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ISSN:1662-9779
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Container-title:Solid State Phenomena
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language:
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Short-container-title:SSP
Author:
Kovač Pavel1,
Savković Borislav1,
Rodić Dragan1,
Gostimirović Marin1,
Sekulić Milenko1,
Ješić Dušan2
Affiliation:
1. University of Novi Sad
2. International Technology Management Academy
Abstract
The objective of this study is to examine the influence of machining parameters on surface finish in turning difficult-to-cut-steel. A new approach in modeling surface roughness which uses design of experiments is described in this paper. The values of surface roughness predicted by different models are then compared. Adaptive-neuro-fuzzy-inference system (ANFIS) was used. The results showed that the proposed system can significantly increase the accuracy of the product profile when compared to the conventional approaches. The results indicate that the design of experiments with central composition plan modeling technique can be effectively used for the prediction of the surface roughness for difficult-to-cut-steel.
Publisher
Trans Tech Publications, Ltd.
Subject
Condensed Matter Physics,General Materials Science,Atomic and Molecular Physics, and Optics
Cited by
1 articles.
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