Potential of part quality monitoring for deep drawing processes by integrating sensors into drawbeads

Abstract. The sheet metal material flow in deep drawing is the result of the prevailing blank restraining forces that occur due to frictional interactions between the workpiece and the active tool components. Therefore, monitoring the restraining forces during deep drawing is an indirect way of recording the material flow and thus the performance of the ongoing sheet metal forming operation. A common tool adjustment that is frequently implemented in industrial applications for controlling the material flow during deep drawing is the integration of drawbeads. While the effect of such drawbeads can be modelled numerically, it is still a great challenge to track and thus verify the acting restraining forces experimentally. Against this background, this paper deals with novel sensor concepts for drawbeads to online monitor the restraining forces acting on the sheet metal material and thus determine the quality of the deep drawn part. For this study, two monitoring methods were evaluated, considering two types of sensors that can be integrated into drawbeads, namely fibre Bragg grating and thin film sensors. For both types of sensors, the operating principle was numerically simulated. Furthermore, the application of FBG was experimentally investigated. In conclusion, the numerical results highlight the promising potential of integrating FBG and thin-film sensors. While the FBG setup showed a minor correlation with part defects, further work is needed to resolve uncertainties in sensor integration and bonding.