R. Adeline, R. Gouriveau, and N. Zerhouni, Pronostic de défaillances: Maitrise de l'erreur de prédiction, 7` eme Conference Internationale de Mobilisation et Simulation, (MOSIM'08), 2008.

D. Bansal, D. Evans, and B. Jones, Application of a real-time predictive maintenance system to a production machine system, International Journal of Machine Tools and Manufacture, vol.45, issue.10, pp.1210-1221, 2005.

M. Bouaziz, E. Zamai, and F. Duvivier, Towards bayesian network methodology for predicting the equipment health factor of complex semiconductor systems, International Journal of Production Research, issue.15, p.51, 2013.
URL : https://hal.archives-ouvertes.fr/hal-00783734

A. Bregon, M. Daigle, and I. Roychoudhury, An integrated framework for model-based distributed diagnosis and prognosis, Annual Conference of the Prognostics and Health Management Society, 2012.

F. Brissaud, B. Lanternier, D. Charpentier, and P. Lyonnet, Modélisation des taux de défaillance en mécanique, combinaison d'une loi de weibull et d'un modèle de cox pour la modélisation des taux de défaillance en fonction du temps et des facteurs d'influence, 2007.

J. Bufferne, La fiabilite des equipements industriels, vol.161, pp.28-33, 2009.

C. S. Byington, M. J. Roemer, and T. Galie, Prognostic enhancements to diagnostic systems for improved condition-based maintenance, IEEE Aerospace Conference Proceedings, vol.6, pp.2815-2824, 2002.

C. S. Byington and P. Stoelting, A model-based approach to prognostics and health management for flight control actuators, IEEE Aerospace Conference, 2004.

F. Camci and R. B. Chinnam, Health-state estimation and prognostics in machining processes, IEEE Transactions on Automation Science and Engineering, vol.7, issue.3, 2010.

S. Das, R. Hall, S. Herzog, G. Harrison, and M. Bodkin, Essential steps in prognostic health management, IEEE Conference on Prognostics and Health Management (PHM'11, pp.1-9, 2011.

M. El-koujok, R. Gouriveau, and N. Zerhouni, A neuro-fuzzy self built system for prognostics: a way to ensure good prediction accuracy by balancing complexity and generalization, International Conference on Prognostics and Health Management (PHM'10), 2010.
URL : https://hal.archives-ouvertes.fr/hal-00459285

N. Gebraeel, A. Elwany, and J. Pan, Residual life predictions in the basence of prior degradation knowledge, IEEE Transactions on Reliability, vol.58, pp.106-117, 2009.

K. Goh, B. Tjahjono, T. Baines, and S. Subramaniam, Ra review of research in manufacturing prognostics, IEEE International Conference on Industrial Informatics, pp.412-422, 2006.

F. L. Greitzer and R. A. Pawlowski, Embedded prognostics health monitoring, International instrumentation symposium on embedded health monitoring workshop, 2002.

D. Gucik-derigny, R. Outbib, and M. Ouladsine, Observer design applied to prognosis of system, International Conference on Prognostics and Health Management (PHM'11), 2011.

P. Hall and J. Strutt, Probabilistic physics-of-failure models for component reliabilities using monte carlo simulation and weibull analysis: a parametric study. Reliability Engineering and System Safety, vol.30, pp.233-242, 2003.

C. Hu, Ensemble of data-driven prognostic algorithms for robust prediction of remaining useful life, IEEE International Conference on Prognostics and Health Management (PHM'11), 2011.

K. Huynh, I. Castro, A. Barros, and C. Berenguer, On the construction of mean residual life for maintenance decision-making, 8th IFAC Symposium on Fault Detection, 2012.
URL : https://hal.archives-ouvertes.fr/hal-00793253

H. Khorasgani, C. Kulkarni, G. Biswas, J. R. Celaya, and K. Goebel, Degredation modeling and remaining useful life prediction of electrolytic capacitors under thermal overstress condition using particle filters, Annual Conference of the Prognostics and Health Management Society (PHM'13), 2013.

J. Lacaille, A. Gouby, and O. Piol, Wear prognostic on turbofan engines, Annual Conference of the Prognostics and Health Management Society (PHM'13), 2013.

N. Lahoud, J. Faucher, D. Malec, and P. Maussion, Electrical ageing modeling of the insulation of low voltage rotating machines fed by inverters with the design of experiments (doe) method, IEEE International Symposium on Diagnostics for Electric Machines, 2011.
URL : https://hal.archives-ouvertes.fr/hal-01289127

. Lawless, Covariates and random effects in a gamma process model with application to degradation and failure, Lifetime Data Analysis, vol.10, pp.213-227, 2004.

C. Letot and P. Dehombreux, Modeles de degradation pour l'estimation de la fiabilite et de la duree de vie residuelle: application la fissuration, 2009.

G. Nima, M. Lin, M. Murthy, Y. Prasad, and S. Yong, A review on degradation models in reliability analysis, Proceedings of the 4th world Congress on Engineering Asset Management, 2009.

S. Onori, G. Rizzoni, and A. Cordoba-arenas, A prognostic methodology for interconnected systems: preliminary results, 8th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, 2012.

S. Pommier, Mecanique des materiaux, ENS Cachan, 2009.
URL : https://hal.archives-ouvertes.fr/cel-01636674

A. Ray, Stochastic modeling of fatigue crack damage for risk analysis and remaining life prediction, Journal of Dynamic Systems, Measurement, and Control, issue.3, p.121, 1999.

I. Roychoudhury and M. Daigle, An integrated modelbased diagnostic and prognostic framework, The 20th International Workshop on Principles of Diagnosis (DX'11), 2011.

G. Vachtsevanos and P. Wang, Fault prognosis using dynamic wavelet neural networks, IEEE Systems Readiness Technology Conference (AUTOTESTCON ), pp.857-870, 2001.

J. Van-noortwijk, M. Kallen, and M. Pandey, Gamma processes for time-dependant reliability of structures, European Safety and Reliability Conference, 2005.

J. Van-noortwijk and H. Klatter, The use of lifetime distributions in bridge replacement modelling, 1rst International Conference on Bridge Maintenance, Safety and Management (IABMAS), 2002.

P. Venet, Hdr: Amelioration de la srete de fonctionnement des dispositifs de stockage d'energie. Unpublished doctoral dissertation, 2007.

G. Vinson, M. Combacau, and T. Prado, Permanent magnet synchronous machines faults detection and identification, 8th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes, 2012.

G. Vinson, M. Combacau, T. Prado, and P. Ribot, Synchronous machine faults detection and diagnosis for electromechanical actuators in aeronautics, 38th Annual Conference of IEEE Industrial Electronics, 2012.

G. Vinson, P. Ribot, T. Prado, and M. Combacau, A generic diagnosis and prognosis framework: application to permanent magnets synchronous machines, IEEE Prognostics and System Health Management Conference (PHM'13), 2013.
URL : https://hal.archives-ouvertes.fr/hal-00925514

P. Weber, P. Munteanu, and L. Jouffe, Dynamic bayesian networks modelling the dependability of systems with degradations and exogenous constraints, 11th IFAC Symposium on Information Control Problems in Manufacturing (INCOM'04), 2004.