Item-based Reliability-centred Life-Cycle Costing using Monte Carlo Simulation

This paper presents a time-sequential probabilistic simulation model for the detailed design of maintenance strategies turbine critical items. The term item shall refer to any part, component, device, subsystem, or functional unit wind that can be individually described and considered. enables farm operators manufactures find most cost-effective strategy each item. Cost optimizations are realized through better adaptation item-specific failure modes, degradation processes, detection capabilities given operational configuration farm. Based on Monte Carlo technique, activities at level simulated over windfarm's lifetime, considering correlations between stochastic variables. results evaluated using statistical means, thereby, determining optimal associated parameters. developed is implemented as Python application equally applicable onshore offshore windfarms.