Creating a Virtual Shadow of the Manufacturing of Automotive Components

Abstract

Abstract Within the automotive industry, there is an increasing demand for a paradigm shift in terms of which materials are used for the manufacturing of the automotive body. Global climate goals are forcing a rapid adaption of new, advanced, sustainable material grades such as the fossil free steels and materials containing higher scrap content. With the introduction of these new and untested materials, methods for accounting for variation in material properties are needed directly in the press lines. The following study will focus on creating an initial virtual shadow of the manufacturing of a Volvo XC90 inner door panel through the application of Artificial Neural Networks (ANN). The virtual shadow differs from the concept of the digital twin by only being a virtual representation of the production line, with training data generated exclusively by numerical simulations, and having no automated communication with the physical press line control system. The virtual shadow can be used as an assistance to the press line operators to see how different press line settings and material parameter variations will impact the quality of the stamped component. The study aims to validate the virtual shadow through accurate predictions of the material draw-in measured in the physical press line.