Marcin Sadurski

Projects

• LLM-Powered Data Extraction for Digital Product Passports / Project leader / ongoing
• 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. et al. (2026) 'Next-gen contextual anomaly detection for sustainable and efficient production in Industry 4.0', in Barata, J., Madani, K., and Panetto, H. (eds). Cham: Springer, pp. 191–203. doi: 10.1007/978-3-032-15576-4_13.
• Fathi, K. et al. (2025) 'Towards Industry 5.0 : AAS/MLOps-driven model maintenance for data-centric production'. SciTePress, pp. 495–502. doi: 10.5220/0013716300003982.
• Braunisch, N. et al. (2025) 'Recognizing and integrating legacy assembly diagrams into Industry 4.0', in IECON 2025 – 51st Annual Conference of the IEEE Industrial Electronics Society. IEEE. doi: 10.1109/iecon58223.2025.11221583.
• Perez Olaya, S. S. et al. (2025) 'Digital twin in Industrie 4.0 implementation for embedded systems', in 2025 IEEE 21st International Conference on Automation Science and Engineering (CASE). IEEE, pp. 1760–1765. doi: 10.1109/case58245.2025.11163805.
• Braunisch, N. et al. (2025) 'Leveraging software development of I4.0 digital twins for PLC programming', in 2025 IEEE 34th International Symposium on Industrial Electronics (ISIE). IEEE. doi: 10.1109/isie62713.2025.11124616.
• Braunisch, N. et al. (2025) 'The link between programmable logic controllers and Industry 4.0 digital twins'. IEEE. doi: 10.1109/icecet63943.2025.11472600.
• Fathi, K. et al. (2024) 'Sustainability in semiconductor production via interpretable and reliable predictions', in IFAC-PapersOnLine. Elsevier, pp. 174–179. doi: 10.1016/j.ifacol.2024.07.213.
• Fathi, K. et al. (2024) 'Detection of novel asset failures in predictive maintenance using classifier certainty', in 2024 32nd Mediterranean Conference on Control and Automation (MED). IEEE, pp. 50–56. doi: 10.1109/med61351.2024.10566204.
• Fathi, K. et al. (2024) 'Domain adaptation via simulation parameter and data perturbation for predictive maintenance', in Do, P. and Ezhilarasu, C. (eds) Proceedings of the PHM Society European Conference 2024. PHM Society, pp. 389–399. doi: 10.36001/phme.2024.v8i1.3985.
• Grivet, K., Sadurski, M. and van de Venn, H. W. (2024) 'Smart factory production process using virtual cost optimization', in 2024 IEEE International Conference on Industrial Technology (ICIT). IEEE. doi: 10.1109/icit58233.2024.10540930.
• Braunisch, N. et al. (2024) 'Digital twin in Industrie 4.0 for embedded systems', in 2024 IEEE 20th International Conference on Factory Communication Systems (WFCS). IEEE. doi: 10.1109/wfcs60972.2024.10540968.
• Fathi, K. et al. (2023) 'Source component shift detection & classification for improved remaining useful life estimation in alarm-based predictive maintenance', in 2023 23rd International Conference on Control, Automation and Systems (ICCAS). IEEE, pp. 975–980. doi: 10.23919/iccas59377.2023.10316874.

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