Machine state inference and traceability of manu-factured products are the key challenges in assessing the quality of a manufacturing assembly line. Detection of assembly line stoppages and estimation of machine utilization durations require deployment of sensors, a data flow architecture, and signal inference algorithms. We present a case study deployment of a manufacturing assembly line for automated traceability. We highlight the sensors used in the deployment, the deployed signal processing and multisensor fusion algorithms, the methods of machine state identification, leading eventually to data association and traceability of manufactured products. We also present the metrics to assess the utilization of the machines in the assembly line which can assist the factory manager in assembly line optimization. The entire framework was replicated in second factory as proof of concept.