Marcin Sadurski

Projects

• Dr. Chiller - Immersive AR Framework for First-Level Maintenance Support / Project leader / ongoing
• PRIME – Process Refinement for Improved Manufacturing Efficiency / Project leader / ongoing
• SmartAssets - Digital Transformation in Industry 4.0 / Project leader / ongoing
• From Supply Chain Data to Digital Twins: A GS1–AAS Interoperability Bridge / Project leader / completed
• Human-Robot Teaming Cobotic Base Cell for Industrial Applications / Co-project leader / completed
• MaintAIn - AI supported hybrid Predictive Maintenance / Project leader / completed
• Predictive Process Tuning - PreTune / Project leader / completed

Publications

Written conference contributions, peer-reviewed

• Fathi, K., Sadurski, M., Waskow, S., Kleinert, T., & van de Venn, H. W. (2026). Next-gen contextual anomaly detection for sustainable and efficient production in Industry 4.0 (J. Barata, K. Madani, & H. Panetto, Eds.; pp. 191–203) [Conference paper]. Springer. https://doi.org/10.1007/978-3-032-15576-4_13
• Fathi, K., Sadurski, M., Waskow, S., Kleinert, T., & van de Venn, H. W. (2025). Towards Industry 5.0 : AAS/MLOps-driven model maintenance for data-centric production [Conference paper]. 495–502. https://doi.org/10.5220/0013716300003982
• Braunisch, N., Serikov, D., Ristin, M., Otto, B., Sadurski, M., van de Venn, H. W., & Wollschlaeger, M. (2025, November 6). Recognizing and integrating legacy assembly diagrams into Industry 4.0. IECON 2025 – 51st Annual Conference of the IEEE Industrial Electronics Society. https://doi.org/10.1109/iecon58223.2025.11221583
• Perez Olaya, S. S., Cavegn, D., Braunisch, N., Ristin, M., Sadurski, M., van de Venn, H. W., & Wollschlaeger, M. (2025). Digital twin in Industrie 4.0 implementation for embedded systems [Conference paper]. 2025 IEEE 21st International Conference on Automation Science and Engineering (CASE), 1760–1765. https://doi.org/10.1109/case58245.2025.11163805
• Braunisch, N., Schmidt, U., Gneuß, T., Ristin, M., Sadurski, M., van de Venn, H. W., & Wollschlaeger, M. (2025, August 25). Leveraging software development of I4.0 digital twins for PLC programming. 2025 IEEE 34th International Symposium on Industrial Electronics (ISIE). https://doi.org/10.1109/isie62713.2025.11124616
• Braunisch, N., Soler Perez Olaya, S., Gneuß, T., Schmidt, U., Ristin, M., Sadurski, M., van de Venn, H. W., & Wollschlaeger, M. (2025, June 3). The link between programmable logic controllers and Industry 4.0 digital twins [Conference paper]. https://doi.org/10.1109/icecet63943.2025.11472600
• Fathi, K., Stramaglia, M., Ristin, M., Sadurski, M., Kleinert, T., Schönfelder, R., & van de Venn, H. W. (2024). Sustainability in semiconductor production via interpretable and reliable predictions [Conference paper]. IFAC-PapersOnLine, 58(4), 174–179. https://doi.org/10.1016/j.ifacol.2024.07.213
• Fathi, K., Corradini, F., Sadurski, M., Silvestri, M., Ristin, M., Laghaei, A., Valtorta, D., Kleinert, T., & van de Venn, H. W. (2024). Domain adaptation via simulation parameter and data perturbation for predictive maintenance [Conference paper]. In P. Do & C. Ezhilarasu (Eds.), Proceedings of the PHM Society European Conference 2024 (Vol. 8, Issue 1, pp. 389–399). PHM Society. https://doi.org/10.36001/phme.2024.v8i1.3985
• Fathi, K., Ristin, M., Sadurski, M., Kleinert, T., & van de Venn, H. W. (2024). Detection of novel asset failures in predictive maintenance using classifier certainty [Conference paper]. 2024 32nd Mediterranean Conference on Control and Automation (MED), 50–56. https://doi.org/10.1109/med61351.2024.10566204
• Grivet, K., Sadurski, M., & van de Venn, H. W. (2024, June 5). Smart factory production process using virtual cost optimization. 2024 IEEE International Conference on Industrial Technology (ICIT). https://doi.org/10.1109/icit58233.2024.10540930
• Braunisch, N., Perez Olaya, S. S., Schmidt, U., Ristin, M., Sadurski, M., van de Venn, H. W., & Wollschlaeger, M. (2024, May 31). Digital twin in Industrie 4.0 for embedded systems. 2024 IEEE 20th International Conference on Factory Communication Systems (WFCS). https://doi.org/10.1109/wfcs60972.2024.10540968
• Fathi, K., Sadurski, M., Kleinert, T., & van de Venn, H. W. (2023). Source component shift detection & classification for improved remaining useful life estimation in alarm-based predictive maintenance [Conference paper]. 2023 23rd International Conference on Control, Automation and Systems (ICCAS), 975–980. https://doi.org/10.23919/iccas59377.2023.10316874

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