Operators of complex systems, such as are found in aerospace, electric power networks, automated manufacturing, or the railways industry, impose ever more stringent availability performance constraints. At the same time, increasing attention is being paid to life-cycle cost (LCC). ALSTOM Transport Information Solutions' URBALIS automated mass transit system is confronted with this situation. This has led the RAM Department to investigating some key factors which impact availability and LCC, in order to provide designers and maintainers with guidelines for reaching availability targets at lowest cost. Redundancy needs to be managed: in particular it is crucial to be able to detect a partial loss of redundancy before the function is completely lost. This is where testability and maintenance policy come into play. In a first model, constant failure rate and perfect maintenance are assumed and Markov modelling is used. In order to contemplate the non-constant failure rate case, as well as the deterministic aspect of scheduled maintenance inspections, simulations are then run with Petri nets. Imperfect maintenance models (based on Kijima's virtual age, [2]) are also considered so that the impact of maintenance-related ageing can be taken into account. .Recommendations are thus formulated depending on relative unit costs of investment, corrective and preventive maintenance, and sensitivity analyses of system availability are performed with respect to failure rate, test coverage rate as well as percentage of perfect maintenance.