Development of a Transformer-Based Inductive Sensor for Monitoring Deep Drawing Processes

Abstract This article presents the development of a robust inductive microsensor based on the transformer principle for monitoring of the quality of drawn parts during a deep drawing process. Initially, a sensor system comprising an inductive sensor and a sensor insert was designed and simulated. Subsequently, a 2D-finite-element simulation was employed to determine optimized parameters for the sensor coils. Based on the simulation, the sensor was manufactured using thin-film technology processes, a combination of photolithographic processes, copper electroplating, and embedding in light-sensitive polyimide. Subsequently, the sensor system was installed in a forming tool to monitor the process and test the sensor system. The deep drawing process was conducted with a variety of sheet materials, including diamagnetic, paramagnetic, and ferromagnetic metals. The findings revealed that the fabricated sensor system is capable of determining the position of the drawing sheet in real-time with a latency of approximately 87 ms and an accuracy of ± 250 μm. This enables the identification of rejects and the adjustment of parameters for the subsequent process. Adapting the sensor to the specific application could potentially reduce the latency, enabling real-time monitoring of the process and the control of forming hydraulics.