Probabilistic models for reliability assessment of ageing equipment and maintenance optimization

Abstract

This thesis aims to propose probabilistic maintenance models for reliability assessment of ageing equipment and maintenance optimization. The proposed Markov models can represent non-periodic inspection and maintenance better than the existing models in the literature. Sensitivity analyses are performed on both models to investigate the effect of inspection and maintenance on reliability and costs. A maintenance optimization problem is formulated to find the optimal inspection and maintenance rates using a grid search algorithm. To obtain adaptive optimal inspection and maintenance policies, a Markov decision process (MDP) model is proposed. This model can explicitly incorporate inspection and maintenance delay times and combine the long term ageing process with frequently observed short term changes in equipment?s condition. System-level maintenance planning is investigated using both system-wide MDP model and through coordination of individual MDP models of each equipment. Numerical studies are conducted with the application on circuit breakers, transformers and wind power systems.