Sensor integration for process control in deep drawing

Abstract

In the context of increasing resource efficiency and profitability, deep drawing can be improved using a digital twin and closed-loop process control. Cyber-physical production systems (CPPS) enable data capture and analysis for an autonomous optimization of the manufacturing process. In this work reference sensor signals are used to control the force and material flow with hydraulic actuators between the blank holder and the die. A novel model-based optimization method is proposed to determine the best sensor location, allowing for standardized evaluation and reduced integration time. FE simulations and forming trials are conducted for validation. The findings indicate time and resource savings through an efficient sensor implementation in deep drawing tools for process control.