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Optimization of aluminum extrusion and die design using neural networks and genetic algorithms


Lozina, Željan; Duplančić, Igor; Lela, Branimir
Optimization of aluminum extrusion and die design using neural networks and genetic algorithms // Aluminium Two Thousand
Rim, 2003. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Optimization of aluminum extrusion and die design using neural networks and genetic algorithms

Autori
Lozina, Željan ; Duplančić, Igor ; Lela, Branimir

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Aluminium Two Thousand / - Rim, 2003

Skup
5th World Congress on Aluminium, Aluminium Two Thousand

Mjesto i datum
Rim, Italija, 18-22.03.2003

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
extrusion; aluminum; genetic algorithms; artificial neural network; optimization

Sažetak
The approach to the optimization of aluminum extrusion process and die design, based on artificial neural network and genetic algorithms, is presented. The artificial neural network is trained on extrusion experiments data to be able to describe complex dependencies between extrusion influence parameters and section properties. Therefore, it can be applied in analysis of different problems in extrusion practice. Two examples in extrusion of hollow sections by means of hollow die were analyzed by using this procedure. The length of the charge welds as a function of billet temperature, extrusion ration and the height of welding chamber were analyzed in the first example. Experiments were performed durin extrusion of tubes of 1000 aluminum alloy by means if bridge die in laboratory conditions. The second example was connected to extrusion of thick walled hollow section of AlZnMg4.5 aluminum alloy by means of porthole die in real conditions. The longitudinal welds strength was analyzed as the function of billet temperature, extrusion rate, and Zr content. In both examples composite plans of experiment were used. Trained artificial neural network forward pass was implanted in genetic algorithms were researched out and presented in the paper. The results of the performed optimization were compared with methods that are more conservative. Proposed approach is proved as efficient, robust and very reliable.

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Projekt / tema
0023012

Ustanove
Fakultet elektrotehnike, strojarstva i brodogradnje, Split

Profili:

Avatar Url Igor Duplančić (autor)

Avatar Url Branimir Lela (autor)

Avatar Url Željan Lozina (autor)

Citiraj ovu publikaciju

Lozina, Željan; Duplančić, Igor; Lela, Branimir
Optimization of aluminum extrusion and die design using neural networks and genetic algorithms // Aluminium Two Thousand
Rim, 2003. (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Lozina, Ž., Duplančić, I. & Lela, B. (2003) Optimization of aluminum extrusion and die design using neural networks and genetic algorithms. U: Aluminium Two Thousand.
@article{article, year = {2003}, pages = {38}, keywords = {extrusion, aluminum, genetic algorithms, artificial neural network, optimization}, title = {Optimization of aluminum extrusion and die design using neural networks and genetic algorithms}, keyword = {extrusion, aluminum, genetic algorithms, artificial neural network, optimization}, publisherplace = {Rim, Italija} }