Maintenance decision making in the power industry: a case study
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New methods and tools are required in the power industry to improve the maintenance strategies and provide more profitability and added values. In this Master Thesis, a maintenance decision model and a maintenance optimization modelare proposed. A case study problem from a partner hydropower company was evaluated. The analysis object was a stator winding that is subject to different failure mechanisms and influencing factors. In addition, the system is monitored by means of visual inspections techniques. An influence diagram was developed to analyze the relations between failure mechanisms, inspection techniques, influencing factors and consequences. From the influence diagram, a model that explains the deterioration process of the system, with two dependent failure mechanisms, was obtained. To model the deterioration, a Markov model was applied. Model parameters were obtained based on expert information. By using Monte Carlo simulations, the state Markov model was implemented and developed as a “tool” in Matlab (Mathworks,2011). This simulation approach was used to compute the remaining life and the failure probability of the system. The same simulation approach, base on the Markovmodel, was used to implement an optimization model. Results from the application of the lifetime model and the maintenance optimization are presented.