Resilience engineering for space missions safety assessment

New challenges constantly affect space safety, mainly due to the complex technological, and procedural evolution of recent years. The human interaction with these factors became steadily more complex, too. Therefore, the traditional linear thinking and the static cause-effect relationship between factors may fail to represent current and future systems’ safety needs adequately. A new trend emerges in safety thinking: focusing on non-linear interactions and tight couplings among functions. In order to enhance the probability of success in future space missions, it is thus necessary to go beyond the traditional risk and safety assessment techniques. In a top-down assessment, it becomes crucial focusing on the system taken as a whole, not on parts taken as separate. In line with this approach, this paper highlights the relevance of new systemic methods, in particular the Functional Resonance Analysis Method (FRAM). FRAM recognizes the importance of paying attention both to “things that go wrong” and “things that go right”, in line with Safety-II perspective, evolving traditional Safety-I. According to Resilience Engineering concepts, FRAM therefore aims to describe how things happen rather than consider only the linear aetiology of a failure. This core concept recognizes the limits of decomposition and causality, in favour of a more complex principle, called functional resonance. It is therefore more important to understand system dynamics and performance variability rather than modelling individual technological, human or organization failures. FRAM permits thus considering inter-related patterns of events rather than simple causal sequences, in order to enhance traditional safety assessment. This paper highlights the possibility of adopting FRAM for safety assessment for future space mission, where high availability is mandatory. This paper also evolves the traditional qualitative FRAM structure, paving the way to a probabilistic FRAM that could better fit with space safety assessment needs. By Monte Carlo simulations, this innovative FRAM model highlights potential critical patterns of functions and proactively defines critical couplings, as shown in a preliminary case study relative to the Apollo lunar missions.