DELİKANLI, Kamil Süleyman Demirel Üniversitesi - Mühendislik Fakültesi - Makine Mühendisliği Bölümü, Turkey , AKSOY, Bekir Süleyman Demirel Üniversitesi - Senirkent Meslek Yüksekokulu (Senirkent MYO) - Bilgisayar Teknolojileri Programı, Turkey

Predicting the Earing Using Gene Expressive Programming at Deep Drawing of Technical Aluminium AA1100

41285

It is emphasized that, earing problem which is one of the material origin problems that occurs during deep drawing of cold rolled AA1100 aluminium sheets and effects of the heat treating parameters to take away or minimize the earing problem were investigated. In recent years, artificial intelligence methods are widely used to estimate the results. In this study, Gene Expressive Programming (GEP) is used to estimate the height of earings. Annealing temperature and annealing time are approved as input parameters; earing height is approved as output parameter. Results are estimated with the ratio of 95,89 % at the GEP environment using only four arithmetical operation variables with the help of these parameters.

30

Deep drawing , Earing , Gen Expressive Programming

Sdu Journal Of Technical Sciences

36