Ireneusz Zagorski (Avtor), Monika Kulisz (Avtor), Anna Szczepaniak (Avtor)

Povzetek

The paper presents the results of a study investigating the roughness parameters Rq, Rt, Rv, and Rp of finished-milled magnesium alloys AZ91D and AZ31B. Carbide end mills with varying edge helix angles were used in the study. Statistical analysis was additionally performed for selected machining conditions. In addition, modelling of selected roughness parameters on the end face for the AZ91D alloy was carried out using artificial neural networks. Results have shown that the tool with λs = 20° is more suitable for the finish milling of magnesium alloys because its use leads to a significant reduction in surface roughness parameters with increased cutting speed. Increased feed per tooth leads to increased surface roughness parameters. Both radial and axial depth of cut has an insignificant effect on surface roughness parameters. It has been proven that finish milling is an effective finishing treatment for magnesium alloys. In addition, it was shown that artificial neural networks are a good tool for the prediction of selected surface roughness parameters after finishing milling of the magnesium alloy AZ91D.

Ključne besede

magnesium alloys;finish milling;roughness;surface quality;statistical analysis;artificial neural networks;

Podatki

Jezik: Angleški jezik
Leto izida:
Tipologija: 1.01 - Izvirni znanstveni članek
Organizacija: UL FS - Fakulteta za strojništvo
UDK: 620.1
COBISS: 187155203 Povezava se bo odprla v novem oknu
ISSN: 0039-2480
Št. ogledov: 27
Št. prenosov: 7
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Slovenski jezik
Sekundarni naslov: Uporaba statistične analize in modeliranja za določitev parametrov hrapavosti po končni obdelavi magnezijevih zlitin z orodji z variabilnim kotom vijačnice
Sekundarne ključne besede: magnezijeve zlitine;končna obdelava;hrapavost;kakovost površin;statistična analiza;umetne nevronske mreže;
Vrsta dela (COBISS): Članek v reviji
Strani: str. 27-41
Letnik: ǂVol. ǂ70
Zvezek: ǂno. ǂ1/2
Čas izdaje: Jan.-Feb. 2024
DOI: 10.5545/sv-jme.2023.596
ID: 23032900