Google Scholar (papers in Order of citations)
Selected papers:
- Mihaela Mitici, Ingeborg de Pater, Anne Barros, & Zhiguo Zeng (2023). Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics: The case of turbofan engines. Reliability Engineering & System Safety, 234, 109199. Paper here: Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics
Open-source code for this paper:
When using this code, please cite "Mihaela Mitici, Ingeborg de Pater, Anne Barros, & Zhiguo Zeng (2023). Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics: The case of turbofan engines. Reliability Engineering & System Safety, 234, 109199." and mention the link to the repository: https://git.science.uu.nl/ics/algorithmic-data-analysis/Code_Dynamic2023/code_dynamic2023/-/tree/Code_Dynamic2024_CNN/src
- System-level Probabilistic Remaining Useful Life Prognostics and Predictive Inspection Planning for Wind Turbines. Davide Manna, Mihaela Mitici, and Matteo D.L. Dalla Vedova. In European Prognostics and Health Management Conference, 2024. Paper here: System-level Probabilistic Remaining Useful Life Prognostics and Predictive Inspection Planning for Wind Turbines
- Predictive Maintenance Planning For Batteries Of Electric Take- Off And Landing (eVTOL) Aircraft Using State-of-Health Prognostics. Mihaela Mitici, Leo Jenneskens, Zhiguo Zeng, and David Coit. In: European Safety and Reliability Conference (ESREL) 2024. Paper here: Predictive Maintenance Planning For Batteries Of Electric Take- Off And Landing (eVTOL) Aircraft Using State-of-Health Prognostics
- Alarm-based predictive maintenance scheduling for aircraft engines with imperfect Remaining Useful Life prognostics. Ingeborg de Pater, Arthur Reijns, and Mihaela Mitici. In: Reliability Engineering & System Safety 221 (2022), p. 108341. Paper here: Alarm-based predictive maintenance scheduling for aircraft engines with imperfect Remaining Useful Life prognostics
- Mihaela Mitici, Madalena Pereira, and Fabrizio Oliviero. “Electric flight scheduling with battery-charging and battery-swapping opportunities”. In: EURO Journal on Transportation and Logistics 11 (2022), p. 100074. Paper here: Electric flight scheduling with battery-charging and battery-swapping opportunities
- Mihaela Mitici and Ingeborg De Pater. “Online model-based Remaining-Useful-Life prognostics for aircraft cooling units using time-warping degradation clustering”. In: Aerospace 8.6 (2021), p. 168. Paper here: Online Model-Based Remaining-Useful-Life Prognostics for Aircraft Cooling Units Using Time-Warping Degradation Clustering
- Micha Zoutendijk and Mihaela Mitici. “Probabilistic flight delay predictions using machine learning and applications to the flight-to-gate assignment problem”. In: Aerospace 8.6 (2021), p. 152. Paper here: Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem
- Juseong Lee and Mihaela Mitici. “Multi-objective design of aircraft maintenance using Gaussian process learning and adaptive sampling”. In: Reliability Engineering & System Safety 218 (2022), p. 108123. Paper here: Multi-objective design of aircraft maintenance using Gaussian process learning and adaptive sampling
Publicaties
2026
Wetenschappelijke publicaties
van Oosterom, S., & Mitici, M. (2026). End-to-end predict-and-optimize dynamic predictive maintenance planning integrating prognostics - the case of short-range electric aircraft with lithium-ion batteries. Transportation Research Part C: Emerging Technologies, 188, Article 105704. [DOI]
Landau, D., de Pater, I., Mitici, M., & Saurabh, N. (2026). Federated learning framework for collaborative remaining useful life prognostics: An aircraft engine case study. Future Generation Computer Systems, 174, Article 107945. [DOI] [Repository]
2025
Wetenschappelijke publicaties
Wandelt, S., Blom, H., Krömer, M. M., Li, D., Mitici, M., Ryley, T., Stumpf, E., Wang, K., Yang, B., Zanin, M., & Sun, X. (2025). DESIGN and be SMART: Eleven engineering challenges to achieve sustainable air transportation under safety assurance in the year 2050. Journal of the Air Transport Research Society, 4, Article 100045. [DOI] [Repository]
2024
Wetenschappelijke publicaties
Manna, D., Mitici, M., & Dalla Vedova, M. D. L. (2024). System-level Probabilistic Remaining Useful Life Prognostics and Predictive Inspection Planning for Wind Turbines. In Proceedings of the 8th European Conference of the Prognostics and Health Management Society 2024 (pp. 802-814) [Repository]
Mitici, M., Jenneskens, L., Zeng, Z., & Coit, D. (2024). Predictive Maintenance Planning For Batteries Of Electric Take- Off And Landing (eVTOL) Aircraft Using State-of-Health Prognostics. In Advances in Reliability, Safety and Security (Vol. 6). Polish Safety and Reliability Association. [Repository]
van Oosterom, S., & Mitici, M. (2024). An environmentally-aware dynamic planning of electric vehicles for aircraft towing considering stochastic aircraft arrival and departure times. Transportation Research Part C: Emerging Technologies, 169, Article 104857. [DOI] [Repository]
Zoutendijk, M., & Mitici, M. (2024). Fleet scheduling for electric towing of aircraft under limited airport energy capacity. Energy, 294, Article 130924. [DOI] [Repository]
2023
Wetenschappelijke publicaties
van Oosterom, S., & Mitici, M. (2023). Optimizing the battery charging and swapping infrastructure for electric short-haul aircraft—The case of electric flight in Norway. Transportation Research Part C: Emerging Technologies, 155, Article 104313. [DOI] [Repository]
Zoutendijk, M., Mitici, M., & Hoekstra, J. (2023). Electric Taxiing with Disruption Management: Assignment of Electric Towing Vehicles to Aircraft. 1-20. Paper presented at AIAA AVIATION 2023 Forum, San Diego. [DOI]
van Oosterom, S., Mitici, M., & Hoekstra, J. (2023). Dispatching a fleet of electric towing vehicles for aircraft taxiing with conflict avoidance and efficient battery charging. Transportation Research Part C: Emerging Technologies, 147, 1-21. Article 103995. [DOI] [Repository]
Lee, J., Mitici, M., Blom, H., Bieber, P., & Freeman, F. (2023). Analyzing emerging challenges for data-driven predictive aircraft maintenance using agent-based modeling and hazard identification. Aerospace, 10(2), 1-17. Article 186. [DOI] [Repository]
Mitici, M., Hennink, B., Pavel, M., & Dong, J. (2023). Prognostics for Lithium-ion batteries for electric Vertical Take-off and Landing aircraft using data-driven machine learning. Energy and AI, 12, Article 100233. [DOI] [Repository]
Mitici, M., de Pater, I., Barros, A., & Zeng, Z. (2023). Dynamic predictive maintenance for multiple components using data-driven probabilistic RUL prognostics: The case of turbofan engines. Reliability Engineering and System Safety, 234, 1-14. Article 109199. [DOI] [Repository]
Geng, S., Yang, M., Mitici, M., & Liu, S. (2023). A resilience assessment framework for complex engineered systems using graphical evaluation and review technique (GERT). Reliability Engineering and System Safety, 236, 1-15. Article 109298. [DOI] [Repository]
Zoutendijk, M., Mitici, M., & Hoekstra, J. (2023). An investigation of operational management solutions and challenges for electric taxiing of aircraft. Research in Transportation Business and Management, 49, 1-14. Article 101019. [DOI] [Repository]
de Pater, I., & Mitici, M. (2023). A mathematical framework for improved weight initialization of neural networks using Lagrange multipliers. Neural Networks, 166, 579-594. [DOI] [Repository]
Mitici, M., & Lee, J. (2023). Deep reinforcement learning for predictive aircraft maintenance using probabilistic Remaining-Useful-Life prognostics. Reliability Engineering and System Safety, 230, Article 108908. [DOI] [Repository]
Mitici, M., & de Pater, I. (2023). Developing health indicators and RUL prognostics for systems with few failure instances and varying operating conditions using a LSTM autoencoder. Engineering Applications of Artificial Intelligence, 117(Part A), Article 105582. [DOI] [Repository]