processing monitoring data (CMS, SCADA, HUM, )
- Analyze surveillance data using statistical tools (ACP, AF, SVM, supervised, unsupervised classification,..., testing, dependency analysis)
- build indicators based on data analysis methods
- model health indicators with consideration of covariates and censors (time series, stochastic processes, regression,...)
- characterize the residual life span
- evaluate the prognostic indicator (FP, MCMC, EM, HMM, ...)
- estimate the uncertainty of the prognostic results (IC, probability law,...)
- apply risk analysis methods (fuzzy logic, belief)
