The International Journal of Prognostics and Health Management (IJPHM) is the premier online open access journal related to multidisciplinary research on Prognostics, Diagnostics, and System Health Management. This special issue focuses on computational methods and practical applications dealing with the representation, interpretation, quantification, and management of uncertainty in prognostics and health management.

Prognostics, the science of prediction, is inherently affected by several sources of uncertainty (natural variability, data uncertainty, and model uncertainty). It is important to rigorously account for these sources of uncertainty while predicting the behavior of engineering systems, and compute the overall uncertainty in the remaining useful life prediction. Uncertainties that exhibit complex, non-linear interactions need to be aggregated using computational methods. If there is a large uncertainty associated with the remaining useful life prediction, then such information may not be useful for meaningful decision-making. Therefore, recent research efforts have focused on developing methods to characterize, interpret, incorporate, and quantify uncertainty in prognostics, quantify the risk associated with system operation decisions, and eventually facilitate risk-informed decision-making activities such as fault mitigation, mission re-planning, etc.