Tehnički vjesnik, Vol. 16 No. 4, 2009.
Izvorni znanstveni članak
Optimization of extrusion process by genetic algorithms and conventional techniques
Zoran Jurković
orcid.org/0000-0002-7202-156X
; Department of Industrial Engineering and Management, Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia
Miran Brezočnik
; Faculty of Mechanical Engineering, University of Maribor, Smetanova 17, SI-2000 Maribor, Slovenia
Branko Grizelj
; Mechanical Engineering Faculty, J. J. Strossmayer University of Osijek, Trg Ivane Brlić Mažuranić 2, HR-35000 Slavonski Brod, Croatia
Vesna Mandić
; Mechanical Engineering Faculty, University of Kragujevac, S. Janjić 6, RS-34000 Kragujevac, Serbia
Sažetak
The purpose of this research is the determination of the optimal cold forward extrusion parameters with the minimization of tool load as objective. This paper deals with different optimization approaches in order to determine optimal values of logarithmic strain, die angle and friction factor with the purpose to find minimal tool loading obtained by cold forward extrusion process. Two experimental plans based on factorial design of experiment and orthogonal array have been carried out. Classical optimization, according to the response model of extrusion forming force, and the Taguchi approach are presented. The obtained extrusion force model as the fitness function was used to carry out genetic algorithm optimization. Experimental verification of optimal forming parameters with their influences on the forming forces was also performed. The experimental results show an improvement in the minimization of tool loading. The results of optimal forming parameters obtained with different optimization approaches have been compared and based on that the characteristics analysis (features and limitations) of presented techniques.
Ključne riječi
metal forming; forward extrusion force optimization; design of experiments; Taguchi approach; genetic algorithm
Hrčak ID:
45722
URI
Datum izdavanja:
29.12.2009.
Posjeta: 2.691 *