Monte Carlo Simulation of a Reliability Optimized Maintenance Concept for Systems with Limited Accessibility

Artificial satellites, space stations and offshore wind turbines are examples of systems which have limited accessibility due to hostile environment and restricted transport capability. The availability of such systems becomes more critical when the maintenance is difficult to perform i.e. the system maintenance involves extraordinary costs or is inherently challenging. The aim of this paper is to propose an adequate model considering the complicated system design (modelled using Reliability Block Diagram tool developed in-house in Airbus Defence and Space), different maintenance strategies (preventive, corrective or combined) and limited accessibility of the system. The proposed model should be able to calculate availability (point availability and mean availability) and replacement rates. The operational capability or performance of a system can be increased by maintenance of the system's sub-units. This operational capability or performance of a system is described as the availability of a system. The availability, in general is used to express the probability of a system being in functional state at any point in time within a defined period. Calculations of availability are determined by the proportion of the so called uptime (describing the operational time) and the so called downtime (describing the non-operational time) of a system. The downtime is not only owed to failures, but includes the related time for maintenance and logistics required to restore the system back to the operational state. Monte Carlo simulation is chosen for the modelling due to its simplicity and flexibility. A Monte Carlo simulation model is applied to provide system availability and replacement rates. The outcome is expected to influence decisions related to the layout of the system, the design of sub-units (like parts quality, internal redundancies, mass, volume), maintenance strategy & sparing concepts and the mission planning (launch schedules).