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https://doi.org/10.17559/TV-20181013122208

Multi-objective Optimization of Hard Milling Using Taguchi Based Grey Relational Analysis

Djordje Cica ; Univeristy of Banja Luka, Faculty of Mechanical Engineering, Stepe Stepanovića 71, 78 000 Banja Luka, Bosnia and Herzegovina
Halil Caliskan ; Ozaylar Machinery Industry, Ankara, Turkey
Peter Panjan ; Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
Davorin Kramar ; Univeristy of Ljubljana, Faculty of Mechanical Engineering, Aškerčeva 6, 1000 Ljubljana, Slovenia


Puni tekst: engleski pdf 689 Kb

str. 513-519

preuzimanja: 644

citiraj


Sažetak

The influence of hard coatings and machining parameters, in particular cutting speed, feed per tooth and depth of cut on specific cutting energy, productivity and surface quality in milling of hardened cold work tool steel, were investigated in this paper. Taguchi's design of experiments was employed for planning of experiments using L27 orthogonal array. Optimal setting of machining parameters for multi-objective characteristics was determined using grey relational analysis. The principal component analysis was used to define the corresponding weight factors of each quality characteristics under optimization. Analysis of variance was conducted and it was revealed that feed per tooth is the most significant parameter affecting quality characteristics. Finally, results of confirmation test with the optimal machining parameters settings have shown that the proposed model improves overall performance of hard milling process.

Ključne riječi

grey relational analysis; hard milling; optimization; Taguchi

Hrčak ID:

236806

URI

https://hrcak.srce.hr/236806

Datum izdavanja:

15.4.2020.

Posjeta: 1.303 *