Digitization of roll forming and its application

Abstract

With the rapid development of metaverse and intelligent manufacturing, the requirement for the digitization of the traditional manufacturing process is a challenging task for industries. Roll forming is a highly efficient sheet metal forming process which can be widely been applied in a wide range of sectors, such as automotive, transportation, building other key sectors. However, this forming process is highly dependent on the experience of the on-site engineers. This paper presents a highly intelligent, flexible and self-adaption roll forming machine co-developed by the University of Electronic Science and Technology of China and data M. The machine consists of several flexible moving units controlled by codded stepper motors with a decent control system. Moreover, a high-performing artificial intelligence algorithm achieved from a systematic machine learning training process is integrated into this machine. The algorithm has already been use to predict and control the forming process to achieve a high-quality product. Data collection on a large scale and integrated sensors lead to an increased understanding of the process and provide the basis to develop self-optimizing roll forming machines, increasing the productivity, quality and predictability of the roll forming process. The application of digital twin and machine learning techniques is used to predict and reduce the amount of springback in the product. The first high-strength steel parts successfully manufactured with this new forming concept are presented.