Experimental optimisation of the tribological behaviour of Al/SiC/Gr hybrid composites based on Taguchi's method and artificial neural network
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2018
Članak u časopisu (Objavljena verzija)
Metapodaci
Prikaz svih podataka o dokumentuApstrakt
This paper presents the investigation of tribological behaviour of aluminium hybrid composites with Al-Si alloy A356 matrix, reinforced with 10 wt% silicon carbide and 0, 1 and 3 wt% graphite (Gr) with the application of Taguchi's method. Tribological investigations were realized on block-on-disc tribometer under lubricated sliding conditions, at three sliding speeds (0.25, 0.5 and 1 m/s), three normal loads (40, 80 and 120 N) and at sliding distance of 2400 m. Wear rate and coefficient of friction were measured within the research. Analysis of the results was conducted using ANOVA technique, and it showed that the smallest values of wear and friction are observed for hybrid composite containing 3 wt% Gr. The prediction of wear rate and coefficient of friction was performed with the use of artificial neural network (ANN). After training of the ANN, the regression coefficient was obtained and it was equal to 0.98905 for the network with architecture 3-20-30-2.
Ključne reči:
Wear / Taguchi method / Lubricated sliding / Hybrid composites / Friction / Compocasting / Artificial neural network / Analysis of variance / A356Izvor:
Journal of The Brazilian Society of Mechanical Sciences and Engineering, 2018, 40, 6Izdavač:
- Springer Heidelberg, Heidelberg
Finansiranje / projekti:
- bilateral project No. 451-03-02294/2015-09/9 between Republic of Serbia and Hungary
- Razvoj triboloških mikro/nano dvokomponentnih i hibridnih samopodmazujućih kompozita (RS-MESTD-Technological Development (TD or TR)-35021)
- Istraživanje i optimizacija tehnoloških i funkcionalnih performansi ventilacionog mlina termoelektrane Kostolac B (RS-MESTD-Technological Development (TD or TR)-34028)
DOI: 10.1007/s40430-018-1237-y
ISSN: 1678-5878
WoS: 000434450600042
Scopus: 2-s2.0-85047507551
Kolekcije
Institucija/grupa
Mašinski fakultetTY - JOUR AU - Stojanović, Blaža AU - Vencl, Aleksandar AU - Bobić, Ilija AU - Miladinović, Slavica AU - Skerlić, Jasmina PY - 2018 UR - https://machinery.mas.bg.ac.rs/handle/123456789/2772 AB - This paper presents the investigation of tribological behaviour of aluminium hybrid composites with Al-Si alloy A356 matrix, reinforced with 10 wt% silicon carbide and 0, 1 and 3 wt% graphite (Gr) with the application of Taguchi's method. Tribological investigations were realized on block-on-disc tribometer under lubricated sliding conditions, at three sliding speeds (0.25, 0.5 and 1 m/s), three normal loads (40, 80 and 120 N) and at sliding distance of 2400 m. Wear rate and coefficient of friction were measured within the research. Analysis of the results was conducted using ANOVA technique, and it showed that the smallest values of wear and friction are observed for hybrid composite containing 3 wt% Gr. The prediction of wear rate and coefficient of friction was performed with the use of artificial neural network (ANN). After training of the ANN, the regression coefficient was obtained and it was equal to 0.98905 for the network with architecture 3-20-30-2. PB - Springer Heidelberg, Heidelberg T2 - Journal of The Brazilian Society of Mechanical Sciences and Engineering T1 - Experimental optimisation of the tribological behaviour of Al/SiC/Gr hybrid composites based on Taguchi's method and artificial neural network IS - 6 VL - 40 DO - 10.1007/s40430-018-1237-y ER -
@article{ author = "Stojanović, Blaža and Vencl, Aleksandar and Bobić, Ilija and Miladinović, Slavica and Skerlić, Jasmina", year = "2018", abstract = "This paper presents the investigation of tribological behaviour of aluminium hybrid composites with Al-Si alloy A356 matrix, reinforced with 10 wt% silicon carbide and 0, 1 and 3 wt% graphite (Gr) with the application of Taguchi's method. Tribological investigations were realized on block-on-disc tribometer under lubricated sliding conditions, at three sliding speeds (0.25, 0.5 and 1 m/s), three normal loads (40, 80 and 120 N) and at sliding distance of 2400 m. Wear rate and coefficient of friction were measured within the research. Analysis of the results was conducted using ANOVA technique, and it showed that the smallest values of wear and friction are observed for hybrid composite containing 3 wt% Gr. The prediction of wear rate and coefficient of friction was performed with the use of artificial neural network (ANN). After training of the ANN, the regression coefficient was obtained and it was equal to 0.98905 for the network with architecture 3-20-30-2.", publisher = "Springer Heidelberg, Heidelberg", journal = "Journal of The Brazilian Society of Mechanical Sciences and Engineering", title = "Experimental optimisation of the tribological behaviour of Al/SiC/Gr hybrid composites based on Taguchi's method and artificial neural network", number = "6", volume = "40", doi = "10.1007/s40430-018-1237-y" }
Stojanović, B., Vencl, A., Bobić, I., Miladinović, S.,& Skerlić, J.. (2018). Experimental optimisation of the tribological behaviour of Al/SiC/Gr hybrid composites based on Taguchi's method and artificial neural network. in Journal of The Brazilian Society of Mechanical Sciences and Engineering Springer Heidelberg, Heidelberg., 40(6). https://doi.org/10.1007/s40430-018-1237-y
Stojanović B, Vencl A, Bobić I, Miladinović S, Skerlić J. Experimental optimisation of the tribological behaviour of Al/SiC/Gr hybrid composites based on Taguchi's method and artificial neural network. in Journal of The Brazilian Society of Mechanical Sciences and Engineering. 2018;40(6). doi:10.1007/s40430-018-1237-y .
Stojanović, Blaža, Vencl, Aleksandar, Bobić, Ilija, Miladinović, Slavica, Skerlić, Jasmina, "Experimental optimisation of the tribological behaviour of Al/SiC/Gr hybrid composites based on Taguchi's method and artificial neural network" in Journal of The Brazilian Society of Mechanical Sciences and Engineering, 40, no. 6 (2018), https://doi.org/10.1007/s40430-018-1237-y . .