The cylinder head is a complex, intricate cast part with numerous hard-to-reach surfaces, small threads, drill holes, and zone-specific tolerances. The metal surface reflects light in varying ways, and at the same time, dozens of different features must be evaluated simultaneously. Conventional camera systems reach their limits in this scenario and, in practice, generate too many false positives.

Furthermore, human inspectors can judge based on context, react adaptively to borderline cases, and reliably distinguish between relevant defects and harmless deviations. This combination of experience, judgment, and flexibility has historically been the hurdle for automation approaches and sets the bar for any new solution.

AI and deep learning, modern imaging techniques, and automated robotic handling now make it possible to fully capture complex components and precisely detect defect patterns. This makes economically viable automation realistic for the first time.