This paper focuses on the application of a computer vision system for the detection of interlacing bricks within a robotic handling system, highlighting the challenges and solutions related to transitioning these systems from controlled laboratory environments to dynamic industrial manufacturing conditions. By addressing practical problems encountered in industrial settings, we emphasize the reliability issues of image-based object detection systems when integrated into automated robotic manipulation processes. The study includes the development and testing of various modified U-Net architectures for brick detection and evaluates their performance in both laboratory and industrial environments.