Please use this identifier to cite or link to this item: https://open.uns.ac.rs/handle/123456789/12049
Title: Modelling and Optimization of Surface Roughness Parameters of Stainless Steel by Artificial Intelligence Methods
Authors: Kovač P.
Savković, Borislav 
Rodić D.
Aleksić A.
Gostimirović, Marin 
Sekulić M.
Kulundžić, Nenad 
Issue Date: 1-Jan-2020
Journal: Lecture Notes in Mechanical Engineering
Abstract: © 2020, Springer Nature Switzerland AG. The objective of this study is to examine the influence of machining parameters on surface finish in turning of medical 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. Used were adaptive-neuro-fuzzy-inference system (ANFIS). 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 medical steel difficult to machining. Optimizations of surface roughness parameters was done by use of ant colony method.
URI: https://open.uns.ac.rs/handle/123456789/12049
ISBN: 9783030313425
ISSN: 21954356
DOI: 10.1007/978-3-030-31343-2_1
Appears in Collections:FTN Publikacije/Publications

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