Flexibility and individuality in product portfolios are increasingly important in manufacturing, necessitating highly adaptable production systems. Industrial robots, despite their potential, are often underutilized due to limited autonomy and programming challenges. This paper presents a modular software toolbox designed for cognitive robotics while addressing the research question of how a modular software toolbox can enhance the cognitive capabilities and autonomy of industrial robots to improve adaptability and efficiency in automated manufacturing processes, particularly in the context of small to medium batch inspections, alongside the increase in efficiency during commissioning and application. The toolbox features reconfigurable algorithms for object recognition, handling, and quality inspections using machine learning methods such as CNNs and SVMs. Optimized for standard industrial computers, the system ensures efficient resource use, achieving object recognition at 20 frames per second. The setup includes a six-axis robot with a CNC controller and high-precision sensors, offering significant cost and time savings for small- to medium-batch inspections. Validation demonstrates the toolbox's potential to enhance flexibility and intelligence in manufacturing systems.