Abstract
Currently, to meet tension stiffness target of the hood, CAE is used repeatedly to determine suitable mastic sealer arrangement. Several complex constraints and combination of the constraints needed for manufacturing require numerous cases of simulation. In this research, we developed a design technology that can rapidly generate multiple arrangement patterns using machine learning. Using this technology, it is expected to reduce simulation costs which will improve the efficiency of the hood development process.