Description
Aging, defects, and failures of industrial systems. Probabilistic and machine-learning-based approaches to reliability modeling. Reliability estimation using nonparametric, parametric, and regression methods. Reliability and availability of series, parallel, and complex systems. Importance measures and redundancy allocation. Failure modes and effects analysis (FMEA) and estimation of their effects and criticality. Methods for the construction and analysis of fault trees. Renewal processes: unit, superposed, and based on the shape of the failure rate. Accelerated life, proportional and competing risks reliability models. Modeling and simulation of system degradation using stochastic processes. Machine-learning-based clustering models for degradation profiles. Management and forecasting models for spare parts of a system or a fleet of systems. Warranty models for repairable, partially repairable, and non-repairable systems. Extended warranty models.