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Kontrec, N. Z., Milovanović, G. V., Panić, S. R., & Milośević, H. (2015). A reliability-based approach to nonrepairable spare part forecasting in aircraft maintenance system. Mathematical Problems in Engineering, 2015.Search in Google Scholar
Bagan, H. G. E. (2019). Use of a nominal group technique in the exploration of safety hazards arising from the outsourcing of aircraft maintenance. Safety science, 118.Search in Google Scholar
Rodrigues, Leonardo, R., Nascimento, Junior, & Cairo, et al. (2015). Use of phm information and system architecture for optimized aircraft maintenance planning. IEEE systems journal, 9(4), 1197-1207.Search in Google Scholar
Manco, P., Caterino, M., Macchiaroli, R., Rinaldi, M., & Fera, M. (2021). Aircraft maintenance: structural health monitoring influence on costs and practices. Macromolecular Symposia, 396.Search in Google Scholar
Dai, J. T., Zhao, P. Z., Su, H. B., Liu, H. D., Wang, Y. B., & Dong, S. K. (2021). Optimal design of composite material maintenance structure for aircraft based on ansys workbench. Key Engineering Materials, 871.Search in Google Scholar
Sun, J., Chaoyi, L. I., Liu, C., Gong, Z., & Wang, R. (2019). A data-driven health indicator extraction method for aircraft air conditioning system health monitoring. Chinese Journal of Aeronautics.Search in Google Scholar
Gerede, E. (2015). A study of challenges to the success of the safety management system in aircraft maintenance organizations in turkey. Safety ence, 73, 106-116.Search in Google Scholar
Cui, J., Fu, K., Chen, X., Qi, Y., & Jiang, L. (2014). Multiple attribute maintenance decision making of aircraft based on grey-fuzziness and analytical hierarchy process. Acta Aeronautica et Astronautica Sinica, 35(2), 478-486.Search in Google Scholar
Dalkilic, & Serdar. (2017). Improving aircraft safety and reliability by aircraft maintenance technician training. Engineering Failure Analysis, 687-694.Search in Google Scholar
Jiao, X., Jing, B., Huang, Y., Li, J., & Xu, G. (2017). Research on fault diagnosis of airborne fuel pump based on emd and probabilistic neural networks. Microelectronics Reliability, 75(aug.), págs. 296-308.Search in Google Scholar
Yoon, J. T., Youn, B. D., Yoo, M., Kim, Y., & Kim, S. (2019). Life-cycle maintenance cost analysis framework considering time-dependent false and missed alarms for fault diagnosis. Reliability Engineering and System Safety, 184.Search in Google Scholar
Shao, D. K. U. (2021). A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance. Information Fusion, 74(1).Search in Google Scholar
Peng, W., Li, H., Bian, G., & Zhang, E. (2020). Fault diagnosis and maintenance decision method of marine transformer: a rough set theory based study. Journal of Coastal Research, 106(sp1), 562.Search in Google Scholar
Forrai, A. (2017). System identification and fault diagnosis of an electromagnetic actuator. IEEE Transactions on Control Systems Technology(3).Search in Google Scholar
Karatug, C., & Arslanoglu, Y. (2022). Development of condition-based maintenance strategy for fault diagnosis for ship engine systems. Ocean engineering.Search in Google Scholar
Gao, Z., Ma, C., Song, D., & Liu, Y. (2017). Deep quantum inspired neural network with application to aircraft fuel system fault diagnosis. Neurocomputing, 238(MAY17), 13-23.Search in Google Scholar