Towards Cognitive Forming Machines: Utilization of Digital Twin-Based Virtual Sensors

Abstract

The high degree of individuality as well as complexity in metal-forming technology is still challenging regarding the development, integration, and operation of cognitive IoT technologies, such as sensors. In particular, the requirements for these systems in terms of robustness and sensitivity are often in conflict and prevent the widespread use of such systems. In this paper, a method for creating digital twin-based virtual sensors is introduced, which can resolve this target conflict. Furthermore, the method is linked to an approach for developing and identifying the digital twin representing the elasto-mechanical behavior of the machine under process condition to sensing technology. The resulting approach is demonstrated by creating virtual sensors to monitor the elasto-mechanical behavior of a servo-mechanical-forming press.