Dynamic reliability explicitly handles the interactions between the stochastic behaviour of system components and the deterministic behaviour of process variables. While dynamic reliability provides a more efficient and realistic way to perform probabilistic risk assessment than "static" approaches, its industrial level applications are still limited. Factors contributing to this situation are the inherent complexity of the theory and the lack of a generic platform. More recently the increased use of digital-based systems has also introduced additional modelling challenges related to specific interactions between system components. Typical examples are the "intelligent transmitters" which are able to exchange information, and to perform internal data processing and advanced functionalities. To make a contribution to solving these challenges, the mathematical framework of dynamic reliability is extended to handle the data and information which are processed and exchanged between systems components. Stochastic deviations that may affect system properties are also introduced to enhance the modelling of failures. A formalized Petri net approach is then presented to perform the corresponding reliability analyses using numerical methods. Following this formalism, a versatile model for the dynamic reliability modelling of digital-based transmitters is proposed. Finally the framework's flexibility and effectiveness is demonstrated on a substantial case study involving a simplified model of a nuclear fast reactor.