10.15660/AUOFMTE.2025-1.3703
Andrei Haidau
haidau.andrei@student.uoradea.ro
Volume XXXIV, 2025/1
This paper presents a comprehensive study on optimizing the technological parameters involved in the deformation process of thin-walled parts. The exhaust pipe manufacturing industry faces significant challenges related to precision, durability, and cost efficiency. One of the most critical aspects of this process is tube bending, where factors such as material deformation, spring back, and defects like wrinkling or thinning can negatively impact product quality. Traditional trial-and-error approaches to optimizing bending parameters are not only time-consuming but also lead to increased material waste and production costs. Recent advancements in artificial intelligence (AI) and machine learning have introduced new possibilities for improving manufacturing processes.
technological parameters, thin-walled deformation, artificial intelligence
ISSN 1583-0691, CNCSIS "Clasa B+"