Please use this identifier to cite or link to this item:
https://open.uns.ac.rs/handle/123456789/3615
Title: | Application of neuro-fuzzy systems for modeling surface roughness parameters for difficult-to-cut-steel | Authors: | Kovač P. Savković, Borislav Rodić, Dragan Gostimirović, Marin Sekulić, Mirjana Ješić D. |
Issue Date: | 1-Jan-2017 | Journal: | Solid State Phenomena | 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. | URI: | https://open.uns.ac.rs/handle/123456789/3615 | ISBN: | 9783035711998 | DOI: | 10.4028/www.scientific.net/SSP.261.277 |
Appears in Collections: | FTN Publikacije/Publications |
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