Validation and Generalization of Key Building Blocks for Cyber-Physical Systems in Manufacturing: Insights from Automotive Inspection and Assembly Use Cases

A key technological challenge for automotive manufacturers is producing multiple vehicle variants on a single production line. At the body-in-white shop of Magna’s complete vehicle plant in Graz, this is addressed through transportable positioning devices that serve as part carriers and adapters between different products, while ensuring consistent geometric alignment throughout the process. Geometrical deviations in these devices can adversely impact product quality along the entire vehicle assembly chain. This paper presents the development and implementation of two patented use cases: a cyber-physical inspection system, fully operational in serial production and a cyber-physical assembly system, tested successfully in the prototype phase. The first actively mitigates the effects of device deviations in real time, while the second enables on-demand configuration of flexible, advanced positioning devices via precision part matching, effectively preventing systematic deviations. Challenges and insights from both systems are discussed. Four previously introduced building blocks for automating quality control processes are validated and generalized for broad applicability across manufacturing processes and project phases via cross-system comparative analysis: integrated capture of process and product data, automated data analytics, automated decision-making, and autonomous process intervention. This work proposes a validated, scalable framework integrating design and implementation of cyber-physical systems to support zero-defect manufacturing.