In Circular.TECH we develop validation strategies to secure the novel and self-learning automation. These strategies aim to ensure the reliability and efficiency of the automated processes. In addition, we can help to derive the requirements for the robots to be used, including grippers and sensors, and thus support the selection and optimization of existing systems. This includes, for example, improving the robots used in SDL to meet the special requirements of the biomedical environment. CAE-supported adaptations and optimizations of the mechanical structure of the robot and gripper systems are conceivable here, including the implementation of systemic lightweight construction.