Juergen-Albrecht Fassmann

Papers

Total Citations

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About

Juergen-Albrecht Fassmann is a researcher at the intersection of process mining, manufacturing informatics, and industrial data engineering. His work addresses a critical bottleneck in smart manufacturing: the semantic gap between raw shop-floor data—collected from machines, robots, and autonomous guided vehicles (AGVs)—and the high-level orchestration software that coordinates production workflows. Fassmann’s most cited contribution, “Conformance Checking and Classification of Manufacturing Log Data” (2019, 12 citations), introduces novel methods to align low-level resource logs with process models, enabling automated conformance checking and anomaly classification on the factory floor. This work has direct implications for improving production transparency, reducing downtime, and enabling real-time quality control in Industry 4.0 environments. While his citation count reflects a focused, emerging impact rather than broad recognition, Fassmann’s research is highly relevant for practitioners and scholars working on digital twin integration, process mining in cyber-physical systems, and data-driven manufacturing optimization. His contributions help bridge the divide between operational technology and information technology, making him a valuable voice in applied process analytics.