This thesis presents a comprehensive framework for managing risks in automotive engineering projects, with a specific focus on braking systems. It effectively integrates established quality tools like FMEA, APQP, ISO 9001, and IATF 16949 to identify, assess, and mitigate failure modes throughout the product lifecycle. The work also introduces the AIAG-VDA Action Priority system as a more accurate method for prioritizing risks compared to the traditional RPN approach. Notably, the thesis explores the innovative integration of artificial intelligence for real-time monitoring, anomaly detection, and predictive maintenance, showing foresight into future industry trends. Case-based FMEA on braking system components strengthens the practical application of the proposed framework. Overall, the thesis is technically sound, forward-looking, and highly relevant to modern automotive quality and safety practices.