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: The case of turbofan engines
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
Publications
2024
Scholarly publications
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)
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.
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. https://doi.org/10.1016/j.trc.2024.104857
Zoutendijk, M., & Mitici, M. (2024). Fleet scheduling for electric towing of aircraft under limited airport energy capacity. Energy, 294, Article 130924. https://doi.org/10.1016/j.energy.2024.130924
2023
Scholarly publications
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. https://doi.org/10.1016/j.trc.2023.104313
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. https://doi.org/10.2514/6.2023-4219
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. https://doi.org/10.1016/j.trc.2022.103995
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. https://doi.org/10.3390/aerospace10020186
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. https://doi.org/10.1016/j.egyai.2023.100233
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. https://doi.org/10.1016/j.ress.2023.109199
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. https://doi.org/10.1016/j.ress.2023.109298
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. https://doi.org/10.1016/j.rtbm.2023.101019
de Pater, I., & Mitici, M. (2023). A mathematical framework for improved weight initialization of neural networks using Lagrange multipliers. Neural Networks, 166, 579-594. https://doi.org/10.1016/j.neunet.2023.07.035
https://dspace.library.uu.nl/bitstream/handle/1874/430349/1-s2.0-S0893608023003921-main.pdf?sequence=1
https://dspace.library.uu.nl/bitstream/handle/1874/430349/1-s2.0-S0893608023003921-main.pdf?sequence=1
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. https://doi.org/10.1016/j.ress.2022.108908
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. https://doi.org/10.1016/j.engappai.2022.105582