Sensor-Based Data Acquisition and Real-Time Process Monitoring for Traceability in Automotive Manufacturing

The paper presents a framework for sensor-based data collection and real-time monitoring of manufacturing processes in the automotive industry within the context of Industry 4.0. The framework integrates identification technologies, including RFID and Data Matrix Code (DMC) scanning, with defined data collection points to support continuous process monitoring and product traceability. The research was conducted as a case study of a shock absorber assembly line, with particular focus on adaptive shock absorber technology. The proposed solution addresses the complexity of multivariant production and emphasizes interoperability between manufacturing systems, data sources, and information layers. An initial test measurement was performed under real production conditions on 30 consecutively manufactured shock absorbers. The recorded process parameters remained within the defined limits, and all tested products were classified as compliant (OK), providing preliminary validation of the proposed framework. The results demonstrate the feasibility of the proposed approach, while further research will focus on extended validation using larger datasets and long-term monitoring under real industrial conditions.