<p>Proces glodanja tvrdih (kaljenih) čelika, vretenastim loptastim glodalima,<br />najčešće se primenjuje u operacijama završne obrade kompleksnih<br />površina. Modelovanje ovog procesa i optimizacija njegovih parametara su<br />veoma važni, kao pomoć za razumevanje samog procesa tako i za rešavanje<br />praktičnih problema. Za modelovanje izlaznih performansi procesa obrade<br />i nalaženje optimalnih vrednosti ulaznih parametara, korišteno je<br />nekoliko klasičnih i prirodom-inspirisanih metoda. Od klasičnih metoda<br />modelovanja i optimizacije, u radu su primenjene: metodologija odzivne<br />površine-RSM, Taguči metoda i Taguči metoda sa sivom relacionom<br />analizom. Korištene prirodom-inspirisane metode modelovanja i<br />optimizacije su: genetski algoritam–GA, sivi vuk optimizer–GWO i<br />nedominantno sortirajući genetski algoritam II–NSGA II. Dobijeni pouzdani<br />matematički modeli izlaznih performansi procesa obrade i optimalni<br />ulazni parametri obrade, potvrđuju opravdanost primene svih navedenih<br />metoda u procesu glodanja vretenastim loptastim glodalima tvrdih<br />(kaljenih) čelika. Posebno treba izdvojiti rezultate dobijene pomoću metode<br />sivi vuk optimizer–GWO. Ova prirodom-inspirisana metoda je potpuno nova<br />metoda i do sada nije bilo literaturnih informacija o mogućnostima njene<br />primene u procesima obrade rezanjem.</p> / <p>The ball end milling process of hard (hardened) steel, is usually applied in the<br />finishing operations of machining comlex surfaces. Modeling of this process and<br />optimization of its parameters are very important as an aid to understanding the<br />processes and to solve practical problems. Several classic and nature-inspired<br />methods were used for modeling of the output process performances and finding<br />the optimal values of input parameters. From traditional methods of modeling and<br />optimization Response Surface Methodology-RSM, Taguchi method and Taguchi<br />method with Gray Relational Analysis, and nature-inspired methods of modeling<br />and optimization Genetic Algorithm-GA, Gray Wolf Optimizer-GWO and Nondominant<br />Sorting Genetic Algorithm II- NSGA-II, were applied in the paper. Reliable<br />mathematical models of the output process performances and the optimal input<br />parameters, confirm the validity of the application of these methods in the process<br />of ball end milling hard (hardened) steel. The results obtained by the method of the<br />Gray Wolf Optimizer-GWO should be particulary noted. This nature-inspired<br />method is quite a new method, and so far there was no literature information on<br />the possibilities of its application in the cutting processes.</p>
| Identifer | oai:union.ndltd.org:uns.ac.rs/oai:CRISUNS:(BISIS)100916 |
| Date | 20 July 2016 |
| Creators | Pejić Vlastimir |
| Contributors | Sekulić Milenko, Kovač Pavel, Gostimirović Marin, Brezočnik Miran, Hadžistević Miodrag |
| Publisher | Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, University of Novi Sad, Faculty of Technical Sciences at Novi Sad |
| Source Sets | University of Novi Sad |
| Language | Serbian |
| Detected Language | Unknown |
| Type | PhD thesis |
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