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Modelling surface roughness in the function of torque when drilling
ID Krivokapić, Zdravko (Avtor), ID Vučurević, Radoslav (Avtor), ID Kramar, Davorin (Avtor), ID Jovanović, Jelena (Avtor)

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Izvleček
Given the application of a multiple regression and artificial neural networks (ANNs), this paper describes development of models for predicting surface roughness, linking an arithmetic mean deviation of a surface roughness to a torque as an input variable, in the process of drilling enhancement steel EN 42CrMo4, thermally treated to the hardness level of 28 HRC, using cruciform blade twist drills made of high speed steel with hardness level of 64-68 HRC. The model was developed using process parameters (nominal diameters of twist drills, speed, feed, and angle of installation of work pieces) as input variables varied at three levels by Taguchi design of experiment and measured experimental data for a torque and arithmetic mean deviation of a surface roughness for different values of flank wear of twist drills. The comparative analysis of the models results and the experimental data, acquired for the inputs at the moment when a wear span reaches a limit value corresponding to a moment of the drills blunting, demonstrates that the neural network model gives better results than the results obtained in the application of multiple linear and nonlinear regression models.

Jezik:Angleški jezik
Ključne besede:drilling, torque, roughness, models
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FS - Fakulteta za strojništvo
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Leto izida:2020
Št. strani:15 str.
Številčenje:Vol. 10, iss. 3, art. 337
PID:20.500.12556/RUL-133202 Povezava se odpre v novem oknu
UDK:621.941:620.191.35(045)
ISSN pri članku:2075-4701
DOI:10.3390/met10030337 Povezava se odpre v novem oknu
COBISS.SI-ID:17169435 Povezava se odpre v novem oknu
Datum objave v RUL:17.11.2021
Število ogledov:540
Število prenosov:126
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Gradivo je del revije

Naslov:Metals
Skrajšan naslov:Metals
Založnik:MDPI AG
ISSN:2075-4701
COBISS.SI-ID:15976214 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.
Začetek licenciranja:03.03.2020

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:vrtanje, moment, hrapavost, modeli

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