Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks

Irene Buj - Corral; Piotr Sender; Carmelo J. Luis-Pérez Luis-Pérez

doi:10.3390/jmmp7010023

Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks

Abstrakt

Honing processes are abrasive machining processes which are commonly employed to improve the surface of manufactured parts such as hydraulic or combustion engine cylinders. These processes can be employed to obtain a cross-hatched pattern on the internal surfaces of cylinders. In this present study, fuzzy artificial neural networks are employed for modeling surface roughness parameters obtained in finishing honing operations. As a general trend, main factors influencing roughness parameters are grain size and pressure. Mean spacing between profile peaks at the mean line parameter, on the contrary, depends mainly on tangential and linear velocity. Grain Size of 30 and pressure of 600 N/cm 2 lead to the highest values of core roughness (Rk) and reduced valley depth (Rvk), which were 1.741 µm and 0.884 µm, respectively. On the other hand, the maximum peak-to-valley roughness parameter (Rz) so obtained was 4.44 µm, which is close to the maximum value of 4.47 µm. On the other hand, values of the grain size equal to 14 and density equal to 20, along with pressure 600 N/cm 2 and both tangential and linear speed of 20 m/min and 40 m/min, respectively, lead to the minimum values of core roughness, reduced peak height (Rpk), reduced valley depth and maximum peak-to-valley height of the profile within a sampling length, which were, respectively, 0.141 µm, 0.065 µm, 0.142 µm, and 0.584 µm.

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Autorzy (3)

Irene Buj - Corral Dr.
- Katedra Technologii Maszyn i Automatyzacji Produkcji
Piotr Sender dr inż.
Carmelo J. Luis-Pérez Luis-Pérez Dr.
- Katedra Technologii Maszyn i Automatyzacji Produkcji

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Wersja publikacji: Accepted albo Published Version
DOI:: Cyfrowy identyfikator dokumentu elektronicznego (otwiera się w nowej karcie) 10.3390/jmmp7010023
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Kategoria:

Publikacja w czasopiśmie

Typ:

artykuły w czasopismach

Opublikowano w:

Journal of Manufacturing and Materials Processing nr 7,
ISSN:

Język:

angielski

Rok wydania:

2023

Opis bibliograficzny:

Buj - Corral I., Sender P., Luis-Pérez C. J. L.: Modeling of Surface Roughness in Honing Processes by UsingFuzzy Artificial Neural Networks// Journal of Manufacturing and Materials Processing -,iss. 23 (2023),

DOI: