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MULTI-OBJECTIVE OPTIMIZATION OF MQLC TURNING PROCESS PARAMETERS USING GREY-FUZZY APPROACH

By
Mario Dragičević ,
Mario Dragičević
Contact Mario Dragičević

Faculty of Mechanical, Computing and Electrical engineering, University of Mostar , Mostar , Bosnia and Herzegovina

Edin Begović ,
Edin Begović

Faculty of Mechanical engineering, University of Zenica , Zenica , Bosnia and Herzegovina

Ivan Peko
Ivan Peko

University of Split , Split , Croatia

Abstract

In this paper the influence of different machining parameters on the surface roughness, cutting force and material removal rate during turning process using MQLC (minimum quantity lubrication and cooling) system was investigated. The experimental plan was defined using Taguchi’s method. Orthogonal array L9 (34) was selected for four input parameters varied on three levels. Parameters that were varied in experiments are: cutting speed (vc), depth of cut (ap), feed rate (f) as well as workpiece steel material. The
grey relational analysis in combination with fuzzy logic technique was used to find out the input parameters levels that lead to optimal process responses values.

References

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Citation

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

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