Pregled bibliografske jedinice broj: 1220012
Fuzzy Logic Modelling of Dross Height in Plasma Jet Cutting of Shipbuilding Aluminium Alloy 5083
Fuzzy Logic Modelling of Dross Height in Plasma Jet Cutting of Shipbuilding Aluminium Alloy 5083 // Proceedings of the 10th International Scientific and Expert Conference TEAM 2022 / Damjanović, Darko ; Stojšić, Josip ; Mirosavljević, Krunoslav ; Sivrić, Hrvoje (ur.).
Slavonski Brod: Sveučilište u Slavonskom Brodu, 2022. str. 267-274 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1220012 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Fuzzy Logic Modelling of Dross Height
in Plasma Jet Cutting of Shipbuilding
Aluminium Alloy 5083
Autori
Peko, Ivan ; Marić, Dejan ; Šolić, Tomislav ; Matić, Tomislav ; Samardžić, Mijat ; Samardžić, Ivan
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 10th International Scientific and Expert Conference TEAM 2022
/ Damjanović, Darko ; Stojšić, Josip ; Mirosavljević, Krunoslav ; Sivrić, Hrvoje - Slavonski Brod : Sveučilište u Slavonskom Brodu, 2022, 267-274
Skup
10th International Scientific and Expert Conference TEAM2022
Mjesto i datum
Slavonski Brod, Hrvatska, 21.09.2022. - 22.09.2022
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
plasma jet cutting ; shipbuilding aluminium ; dross height ; fuzzy logic modelling
Sažetak
In this paper experimentations were made on shipbuilding aluminium alloy EN AW 5083 thickness of 8 mm in order to investigate influence of variable plasma jet cutting process parameters such as gas pressure, cutting speed, arc current and cutting height on formation of dross on the exit of the plasma jet from the workpiece material. Dross is significant cut quality response in plasma jet cutting process. It can be defined as blown molten metal concentrated on the bottom side of the sheet. Artificial intelligence method fuzzy logic was applied to model relations between input parameters and analysed response. Prediction accuracy of developed fuzzy logic model was checked by comparison between experimental and predicted data. Mean absolute percentage error (MAPE) and coefficient of determination (R2) were used as prediction accuracy measures. After prediction accuracy was proved it was concluded that such defined fuzzy logic model represents good basis for further more detailed experimental research in this area. Furtherly, it allows creation of fuzzy expert system that will enable deeper understanding of process parameters effects on dross formation and quite better response prediction.
Izvorni jezik
Engleski
Znanstvena područja
Strojarstvo
POVEZANOST RADA
Ustanove:
Prirodoslovno-matematički fakultet, Split,
Sveučilište u Slavonskom Brodu
Profili:
Ivan Peko
(autor)
Tomislav Šolić
(autor)
Ivan Samardžić
(autor)
Mijat Samardžić
(autor)
Dejan Marić
(autor)
Tomislav Matić
(autor)