Spares Scaling
iOS Universel / Utilitaires
The application calculates, by Monte Carlo Simulation, the fleet availability (Service Level - SL) achieved by operating a number of fleet assets under specified scenarios. Each scenario examines a single repairable component/unit of the asset for which a specified number of spares (rotables) are kept in stock.
Inputs required are the number of fleet assets, the annual rate of fleet operational usage (e.g. 2000 hours per year), the number of installed components per asset, the number of spare components kept, the reliability of the component and finally its time Turn Around Time (TAT). This is the time needed to repair the failed component/unit and return it as serviceable back in the warehouse.
The reliability of the component is introduced into the model as stochastic variable through the associated Weibull distribution with its scale & shape parameters. Similarly, the Turn Around Time or Time To Repair (TTR) is considered as stochastic variable, having triangular probability distribution defined by the minimum, maximum & most likely durations. The service level is calculated with 95% confidence margin.
Quoi de neuf dans la dernière version ?
Bug fixes
