ABSTRACT
A number of advanced reliability, availability, and maintainability (RAM) modeling techniques for complex systems used in the railway industry are described in this chapter, which are useful for specification, assessment, and possible improvement of the RAM of products and systems throughout all phases of the life cycle of a railway project. Moreover, these methods are used in the context of functional safety. For railway applications, the systematic processes for specifying the requirements for RAM and safety and demonstrating that these requirements are achieved are given in the standard EN 50126-1. Particularly for modeling of systems with redundancy, concurrent behavior, and complex operation and maintenance strategies, Markov models (Markov chains) as well as Petri nets (in particular, generalized stochastic Petri nets) are suitable techniques. Monte Carlo simulation offers great modeling flexibility to take into account any uncertainties and to provide solutions for complex systems of any kind. Finally, Bayesian networks and influence diagrams are powerful techniques for modeling and handling uncertainties and complex dependencies in risk scenarios and decision problems.
