Application of fuzzy logic and regression analysis for modeling surface roughness in face milliing

  • Authors:

  • P. Kovac;D. Rodic;V. Pucovsky;B. Savkovic;M. Gostimirovic

  • Affiliations:

  • Department of Production Engineering, Faculty of Technical Science, University of Novi Sad, Novi Sad, Serbia 21000;Department of Production Engineering, Faculty of Technical Science, University of Novi Sad, Novi Sad, Serbia 21000;Department of Production Engineering, Faculty of Technical Science, University of Novi Sad, Novi Sad, Serbia 21000;Department of Production Engineering, Faculty of Technical Science, University of Novi Sad, Novi Sad, Serbia 21000;Department of Production Engineering, Faculty of Technical Science, University of Novi Sad, Novi Sad, Serbia 21000

  • Venue:
  • Journal of Intelligent Manufacturing
  • Year:
  • 2013

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Abstract

The objective of this study is to examine the influence of machining parameters on surface finish in face milling. A new approach in modeling surface roughness which uses artificial intelligence tools is described in this paper. This paper focuses on developing empirical models using fuzzy logic and regression analysis. The values of surface roughness predicted by these models are then compared. The results showed that the proposed system can significantly increase the accuracy of the product profile when compared to the conventional approaches, like regression analysis. The results indicate that the fuzzy logic modeling technique can be effectively used for the prediction of surface roughness in dry machining.