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Application of Taguchi coupled Fuzzy Multi Attribute Decision Making (FMADM) for optimizing surface quality in turning austenitic and duplex stainless steels.

Authors :
Koyee, Rastee D.
Eisseler, Rocco
Schmauder, Siegfried
Source :
Measurement (02632241). Dec2014, Vol. 58, p375-386. 12p.
Publication Year :
2014

Abstract

In the present study, Taguchi approach is coupled with fuzzy-multiple attribute decision making methods for achieving better surface quality in constant cutting speed face turning of EN 1.4404 austenitic, EN 1.4462 standard duplex and EN 1.4410 super duplex stainless steels. Two typical multiple attribute decision making techniques were simultaneously adopted to determine multi-surface quality characteristics indices. The differences in rankings among derived indices are solved through converting each crisp values into trapezoidal fuzzy number and unifying them using fuzzy simple additive weight method. The fuzzy numbers are then deffuzified into crisp values employing techniques like; the spread, mode and area between centroid of centroids. Through this procedure, the decision maker is provided with necessary decision tools to optimize the cutting conditions with less sensitivity to the change of weights and no difference in ranking among the deffuzification techniques. Additionally, results of analyses of means and the validation experiments confirm that the optimum cutting conditions derived by this method produce far better surface finish than the best finish obtained during the course of experimentation. Analyses of variance results have shown the predominant effect of feed rate on surface quality. Finally, the collected chip at constant cutting speed and varying feed rates and depth of cuts has shown that friendlier-to-machine chips are obtained when machining austenitic stainless steels than duplex stainless steel grades. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02632241
Volume :
58
Database :
Academic Search Index
Journal :
Measurement (02632241)
Publication Type :
Academic Journal
Accession number :
99063062
Full Text :
https://doi.org/10.1016/j.measurement.2014.09.015